274,506 results on '"Hahn A"'
Search Results
2. Multiplicity dependent $J/\psi$ and $\psi(2S)$ production at forward and backward rapidity in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV
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PHENIX Collaboration, Abdulameer, N. J., Acharya, U., Aidala, C., Akiba, Y., Alfred, M., Andrieux, V., Antsupov, S., Apadula, N., Asano, H., Azmoun, B., Babintsev, V., Bandara, N. S., Bannikov, E., Barish, K. N., Bathe, S., Bazilevsky, A., Beaumier, M., Belmont, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Blankenship, B., Blau, D. S., Bok, J. S., Borisov, V., Brooks, M. L., Bryslawskyj, J., Bumazhnov, V., Campbell, S., Cervantes, R., Chen, D., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Citron, Z., Connors, M., Corliss, R., Cronin, N., Csanád, M., Csörgő, T., Danley, T. W., Daugherity, M. S., David, G., DeBlasio, K., Dehmelt, K., Denisov, A., Deshpande, A., Desmond, E. J., Dion, A., Dixit, D., Doomra, V., Do, J. H., Drees, A., Drees, K. A., Durham, J. M., Durum, A., En'yo, H., Enokizono, A., Esha, R., Fadem, B., Fan, W., Feege, N., Fields, D. E., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fokin, S. L., Frantz, J. E., Franz, A., Frawley, A. D., Fukuda, Y., Gallus, P., Gal, C., Garg, P., Ge, H., Giordano, F., Goto, Y., Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gunji, T., Guo, T., Guragain, H., Hachiya, T., Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hamilton, H. F., Hanks, J., Han, S. Y., Hasegawa, S., Haseler, T. O. S., Hemmick, T. K., He, X., Hill, J. C., Hill, K., Hodges, A., Hollis, R. S., Homma, K., Hong, B., Hoshino, T., Hotvedt, N., Huang, J., Imai, K., Inaba, M., Iordanova, A., Isenhower, D., Ivanishchev, D., Jacak, B., Jezghani, M., Jiang, X., Ji, Z., Johnson, B. M., Jouan, D., Jumper, D. S., Kang, J. H., Kapukchyan, D., Karthas, S., Kawall, D., Kazantsev, A. V., Khachatryan, V., Khanzadeev, A., Kim, C., Kim, E. -J., Kim, M., Kincses, D., Kistenev, E., Klatsky, J., Kline, P., Koblesky, T., Kotov, D., Kovacs, L., Kudo, S., Kurita, K., Kwon, Y., Lajoie, J. G., Lebedev, A., Lee, S., Leitch, M. J., Leung, Y. H., Lim, S. H., Liu, M. X., Li, X., Loggins, V. -R., Lökös, S., Loomis, D. A., Lovasz, K., Lynch, D., Majoros, T., Makdisi, Y. I., Makek, M., Manko, V. I., Mannel, E., McCumber, M., McGaughey, P. L., McGlinchey, D., McKinney, C., Mendoza, M., Mignerey, A. C., Milov, A., Mishra, D. K., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Mitsuka, G., Miyasaka, S., Mizuno, S., Montuenga, P., Moon, T., Morrison, D. P., Mulilo, B., Murakami, T., Murata, J., Nagai, K., Nagashima, K., Nagashima, T., Nagle, J. L., Nagy, M. I., Nakagawa, I., Nakano, K., Nattrass, C., Niida, T., Nouicer, R., Novitzky, N., Novák, T., Nukazuka, G., Nyanin, A. S., O'Brien, E., Ogilvie, C. A., Koop, J. D. Orjuela, Orosz, M., Osborn, J. D., Oskarsson, A., Ottino, G. J., Ozawa, K., Pantuev, V., Papavassiliou, V., Park, J. S., Park, S., Patel, M., Pate, S. F., Perepelitsa, D. V., Perera, G. D. N., Peressounko, D. Yu., PerezLara, C. E., Perry, J., Petti, R., Phipps, M., Pinkenburg, C., Pisani, R. P., Potekhin, M., Purschke, M. L., Read, K. F., Reynolds, D., Riabov, V., Riabov, Y., Richford, D., Rinn, T., Rolnick, S. D., Rosati, M., Rowan, Z., Safonov, A. S., Sakaguchi, T., Sako, H., Samsonov, V., Sarsour, M., Sato, S., Schaefer, B., Schmoll, B. K., Sedgwick, K., Seidl, R., Seleznev, A., Sen, A., Seto, R., Sexton, A., Sharma, D., Shein, I., Shibata, T. -A., Shigaki, K., Shimomura, M., Shioya, T., Shukla, P., Sickles, A., Silva, C. L., Silvermyr, D., Singh, B. K., Singh, C. P., Singh, V., Slunečka, M., Smith, K. L., Snowball, M., Soltz, R. A., Sondheim, W. E., Sorensen, S. P., Sourikova, I. V., Stankus, P. W., Stoll, S. P., Sugitate, T., Sukhanov, A., Sumita, T., Sun, J., Sun, Z., Sziklai, J., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Tarnai, G., Tieulent, R., Timilsina, A., Todoroki, T., Tomášek, M., Towell, C. L., Towell, R. S., Tserruya, I., Ueda, Y., Ujvari, B., van Hecke, H. W., Velkovska, J., Virius, M., Vrba, V., Vukman, N., Wang, X. R., Watanabe, Y. S., Woody, C. L., Xue, L., Xu, C., Xu, Q., Yalcin, S., Yamaguchi, Y. L., Yamamoto, H., Yanovich, A., Yoon, I., Yoo, J. H., Yushmanov, I. E., Yu, H., Zajc, W. A., Zelenski, A., and Zou, L.
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High Energy Physics - Experiment - Abstract
The $J/\psi$ and $\psi(2S)$ charmonium states, composed of $c\bar{c}$ quark pairs and known since the 1970s, are widely believed to serve as ideal probes to test quantum chromodynamics in high-energy hadronic interactions. However, there is not yet a complete understanding of the charmonium-production mechanism. Recent measurements of $J/\psi$ production as a function of event charged-particle multiplicity at the collision energies of both the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC) show enhanced $J/\psi$ production yields with increasing multiplicity. One potential explanation for this type of dependence is multiparton interactions (MPI). We carry out the first measurements of self-normalized $J/\psi$ yields and the $\psi(2S)$ to $J/\psi$ ratio at both forward and backward rapidities as a function of self-normalized charged-particle multiplicity in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV. In addition, detailed {\sc pythia} studies tuned to RHIC energies were performed to investigate the MPI impacts. We find that the PHENIX data at RHIC are consistent with recent LHC measurements and can only be described by {\sc pythia} calculations that include MPI effects. The forward and backward $\psi(2S)$ to $J/\psi$ ratio, which serves as a unique and powerful approach to study final-state effects on charmonium production, is found to be less dependent on the charged-particle multiplicity., Comment: 301 authors from 69 institutions, 8 pages, 3 figures. v1 is version submitted to Physical Review D Letters. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html
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- 2024
3. Characterisation of the Atmosphere in Very High Energy Gamma-Astronomy for Imaging Atmospheric Cherenkov Telescopes
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Prester, Dijana Dominis, Ebr, Jan, Gaug, Markus, Hahn, Alexander, Babić, Ana, Eliášek, Jiří, Janeček, Petr, Karpov, Sergey, Kolarek, Marta, Manganaro, Marina, and Mirzoyan, Razmik
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Astrophysics - Instrumentation and Methods for Astrophysics ,Astrophysics - High Energy Astrophysical Phenomena - Abstract
Ground-based observations of Very High Energy (VHE) gamma rays from extreme astrophysical sources are significantly influenced by atmospheric conditions. This is due to the atmosphere being an integral part of the detector when utilizing Imaging Atmospheric Cherenkov Telescopes (IACTs). Clouds and dust particles diminish atmospheric transmission of Cherenkov light, thereby impacting the reconstruction of the air showers and consequently the reconstructed gamma-ray spectra. Precise measurements of atmospheric transmission above Cherenkov observatories play a pivotal role in the accuracy of the analysed data, among which the corrections of the reconstructed energies and fluxes of incoming gamma rays, and in establishing observation strategies for different types of gamma-ray emitting sources. The Major Atmospheric Gamma Imaging Cherenkov (MAGIC) telescopes and the Cherenkov Telescope Array Observatory (CTAO), both located on the Observatorio del Roque de los Muchachos (ORM), La Palma, Canary Islands, use different sets of auxiliary instruments for real-time characterisation of the atmosphere. In this paper, historical data taken by MAGIC LIDAR (LIght Detection And Ranging) and CTAO FRAM (F/Photometric Robotic Telescope) are presented. From the atmospheric aerosol transmission profiles measured by the MAGIC LIDAR and CTAO FRAM aerosol optical depth maps, we obtain the characterisation of the clouds above the ORM at La Palma needed for data correction and optimal observation scheduling.
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- 2024
- Full Text
- View/download PDF
4. High-Resolution Laboratory Measurements of M-shell Fe EUV Line Emission using EBIT-I
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Fairchild, Alexander J., Hell, Natalie, Beiersdorfer, Peter, Brown, Gregory V., Eckart, Megan E., Hahn, Michael, and Savin, Daniel W.
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Astrophysics - Solar and Stellar Astrophysics - Abstract
Solar physicists routinely utilize observations of Ar-like Fe IX and Cl-like Fe X emission to study a variety of solar structures. However, unidentified lines exist in the Fe IX and Fe X spectra, greatly impeding the spectroscopic diagnostic potential of these ions. Here, we present measurements using the Lawrence Livermore National Laboratory EBIT-I electron beam ion trap in the wavelength range 238-258 A. These studies enable us to unambiguously identify the charge state associated with each of the observed lines. This wavelength range is of particular interest because it contains the Fe IX density diagnostic line ratio 241.74 A/244.91 A, which is predicted to be one of the best density diagnostics of the solar corona, as well as the Fe X 257.26 A magnetic-field-induced transition. We compare our measurements to the Fe IX and Fe X lines tabulated in CHIANTI v10.0.1, which is used for modeling the solar spectrum. In addition, we have measured previously unidentified Fe X lines that will need to be added to CHIANTI and other spectroscopic databases.
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- 2024
- Full Text
- View/download PDF
5. Lowering threshold of NaI(Tl) scintillator to 0.7 keV in the COSINE-100 experiment
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Yu, G. H., Carlin, N., Cho, J. Y., Choi, J. J., Choi, S., Ezeribe, A. C., França, L. E., Ha, C., Hahn, I. S., Hollick, S. J., Jeon, E. J., Joo, H. W., Kang, W. G., Kauer, M., Kim, B. H., Kim, H. J., Kim, J., Kim, K. W., Kim, S. H., Kim, S. K., Kim, W. K., Kim, Y. D., Kim, Y. H., Ko, Y. J., Lee, D. H., Lee, E. K., Lee, H., Lee, H. S., Lee, H. Y., Lee, I. S., Lee, J., Lee, J. Y., Lee, M. H., Lee, S. H., Lee, S. M., Lee, Y. J., Leonard, D. S., Luan, N. T., Machado, V. H. A., Manzato, B. B., Maruyama, R. H., Neal, R. J., Olsen, S. L., Park, B. J., Park, H. K., Park, H. S., Park, J. C., Park, K. S., Park, S. D., Pitta, R. L. C., Prihtiadi, H., Ra, S. J., Rott, C., Shin, K. A., Cavalcante, D. F. F. S., Son, M. K., Spooner, N. J. C., Truc, L. T., and Yang, L.
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High Energy Physics - Experiment ,Physics - Instrumentation and Detectors - Abstract
COSINE-100 is a direct dark matter search experiment, with the primary goal of testing the annual modulation signal observed by DAMA/LIBRA, using the same target material, NaI(Tl). In previous analyses, we achieved the same 1 keV energy threshold used in the DAMA/LIBRA's analysis that reported an annual modulation signal with 11.6$\sigma$ significance. In this article, we report an improved analysis that lowered the threshold to 0.7 keV, thanks to the application of Multi-Layer Perception network and a new likelihood parameter with waveforms in the frequency domain. The lower threshold would enable a better comparison of COSINE-100 with new DAMA results with a 0.75 keV threshold and account for differences in quenching factors. Furthermore the lower threshold can enhance COSINE-100's sensitivity to sub-GeV dark matter searches.
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- 2024
6. Bounds on Petz-R\'enyi Divergences and their Applications for Device-Independent Cryptography
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Hahn, Thomas A., Tan, Ernest Y. -Z., and Brown, Peter
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Quantum Physics - Abstract
Variational techniques have been recently developed to find tighter bounds on the von Neumann entropy in a completely device-independent (DI) setting. This, in turn, has led to significantly improved key rates of DI protocols, in both the asymptotic limit as well as in the finite-size regime. In this paper, we discuss two approaches towards applying these variational methods for Petz-R\'enyi divergences instead. We then show how this can be used to further improve the finite-size key rate of DI protocols, utilizing a fully-R\'enyi entropy accumulation theorem developed in a partner work. Petz-R\'enyi divergences can also be applied to study DI advantage distillation, in which two-way communication is used to improve the noise tolerance of quantum key distribution (QKD) protocols. We implement these techniques to derive increased noise tolerances for DIQKD protocols, which surpass all previous known bounds., Comment: 61 pages, 1 figure
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- 2024
7. DUNE Phase II: Scientific Opportunities, Detector Concepts, Technological Solutions
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DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Alves, T., Amar, H., Amedo, P., Anderson, J., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antic, D., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D. M., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azam, M. B., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barbu, D., Barenboim, G., Barham~Alzás, P., Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernal, J., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Bodek, A., Bogenschuetz, J., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bouet, R., Boza, J., Bracinik, J., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Bundock, A., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chakraborty, S., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chiapponi, F., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collazo, J., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cortez, A. F. V., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Curciarello, F., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., Dallaway, W., D'Amico, R., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., Sanchez, P. Del Amo, De la Torre, A., De Lauretis, G., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., De Matteis, G., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Diaz, A., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farrell, S., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Fernández-Posada, D., Ferry, G., Fialova, E., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gaba, R., Gabrielli, A., M~Gago, A., Galizzi, F., Gallagher, H., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Gazzana, S., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, L., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, F. Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Habig, A., Hadavand, H., Haegel, L., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hakenmüller, J., Hamernik, T., Hamilton, P., Hancock, J., Happacher, F., Harris, D. A., Hart, A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C. M., Hatcher, R., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Hellmuth, P., Henry, S., Hernández-García, J., Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horiuchi, S., Horton-Smith, G. A., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Ibrahim, M., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Jentz, I., Ji, X., Jiang, C., Jiang, J., Jiang, L., Jipa, A., Jo, J. H., Joaquim, F. R., Johnson, W., Jollet, C., Jones, B., Jones, R., Jovancevic, N., Judah, M., Jung, C. K., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A. C., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Kandemir, M., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kauther, A., Kazaryan, N., Ke, L., Kearns, E., Keener, P. T., Kelly, K. J., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khabibullin, M., Khan, N., Khvedelidze, A., Kim, D., Kim, J., Kim, M. J., King, B., Kirby, B., Kirby, M., Kish, A., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koch, L., Koehler, K., Koerner, L. W., Koh, D. H., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kovalcuk, M., Kozhukalov, V., Krah, W., Kralik, R., Kramer, M., Kreczko, L., Krennrich, F., Kreslo, I., Kroupova, T., Kubota, S., Kubu, M., Kudenko, Y., Kudryavtsev, V. A., Kufatty, G., Kuhlmann, S., Kulagin, S., Kumar, J., Kumar, P., Kumaran, S., Kunzmann, J., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kuźniak, M., Kvasnicka, J., Labree, T., Lackey, T., Lalău, I., Lambert, A., Land, B. J., Lane, C. E., Lane, N., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laudrain, A., Laundrie, A., Laurenti, G., Lavaut, E., Laycock, P., Lazanu, I., LaZur, R., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeCompte, T., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Silverio, D. Leon, Lepin, L. M., -Y~Li, J., Li, S. W., Li, Y., Liao, H., Lin, C. S., Lindebaum, D., Linden, S., Lineros, R. A., Lister, A., Littlejohn, B. R., Liu, H., Liu, J., Liu, Y., Lockwitz, S., Lokajicek, M., Lomidze, I., Long, K., Lopes, T. V., Lopez, J., de Rego, I. López, López-March, N., Lord, T., LoSecco, J. M., Louis, W. C., Sanchez, A. Lozano, Lu, X. -G., Luk, K. B., Lunday, B., Luo, X., Luppi, E., MacFarlane, D., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., MacMahon, M., Maddalena, A., Madera, A., Madigan, P., Magill, S., Magueur, C., Mahn, K., Maio, A., Major, A., Majumdar, K., Mameli, S., Man, M., Mandujano, R. C., Maneira, J., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Corchado, S. Manthey, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marques, F. Das Chagas, Marquet, C., Marshak, M., Marshall, C. M., Marshall, J., Martina, L., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Massari, C., Mastbaum, A., Matichard, F., Matsuno, S., Matteucci, G., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., McAskill, T., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Meazza, L., Meddage, V. C. N., Mefodiev, A., Mehta, B., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Mercuri, A. C. E. A., Meregaglia, A., Messier, M. D., Metallo, S., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Micallef, J., Miccoli, A., Michna, G., Milincic, R., Miller, F., Miller, G., Miller, W., Mineev, O., Minotti, A., Miralles, L., Miranda, O. G., Mironov, C., Miryala, S., Miscetti, S., Mishra, C. S., Mishra, P., Mishra, S. R., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Mogan, A., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Mooney, M., Moor, A. F., Moore, Z., Moreno, D., Moreno-Palacios, O., Morescalchi, L., Moretti, D., Moretti, R., Morris, C., Mossey, C., Moura, C. A., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mulhearn, M., Munford, D., Munteanu, L. J., Muramatsu, H., Muraz, J., Murphy, M., Murphy, T., Muse, J., Mytilinaki, A., Nachtman, J., Nagai, Y., Nagu, S., Nandakumar, R., Naples, D., Narita, S., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nehm, A., Nelson, J. K., Neogi, O., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, A., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Oh, S., Oh, S. B., Olivier, A., Olshevskiy, A., Olson, T., Onel, Y., Onishchuk, Y., Oranday, A., Gann, G. D. Orebi, Osbiston, M., Vélez, J. A. Osorio, O'Sullivan, L., Ormachea, L. Otiniano, Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Pan, S., Panda, P., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papaleo, R., Papanestis, A., Papoulias, D., Paramesvaran, S., Paris, A., Parke, S., Parozzi, E., Parsa, S., Parsa, Z., Parveen, S., Parvu, M., Pasciuto, D., Pascoli, S., Pasqualini, L., Pasternak, J., Patrick, C., Patrizii, L., Patterson, R. B., Patzak, T., Paudel, A., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Pec, V., Pedreschi, E., Peeters, S. J. M., Pellico, W., Perez, A. Pena, Pennacchio, E., Penzo, A., Peres, O. L. G., Gonzalez, Y. F. Perez, Pérez-Molina, L., Pernas, C., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pfaff, M., Pia, V., Pickering, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Pincha, S., Pinchault, J., Pitts, K., Plows, K., Pollack, C., Pollman, T., Pompa, F., Pons, X., Poonthottathil, N., Popov, V., Poppi, F., Porter, J., Paix{ã}o, L. G. Porto, Potekhin, M., Potenza, R., Pozimski, J., Pozzato, M., Prakash, T., Pratt, C., Prest, M., Psihas, F., Pugnere, D., Qian, X., Queen, J., Raaf, J. L., Radeka, V., Rademacker, J., Radics, B., Raffaelli, F., Rafique, A., Raguzin, E., Rai, M., Rajagopalan, S., Rajaoalisoa, M., Rakhno, I., Rakotondravohitra, L., Ralte, L., Delgado, M. A. Ramirez, Ramson, B., Rappoldi, A., Raselli, G., Ratoff, P., Ray, R., Razafinime, H., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reichenbacher, J., Reitzner, S. D., Sfar, H. Rejeb, Renner, E., Renshaw, A., Rescia, S., Resnati, F., Diego~Restrepo, Reynolds, C., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Ricol, J. S., Rigan, M., Rincón, E. V., Ritchie-Yates, A., Ritter, S., Rivera, D., Rivera, R., Robert, A., Rocha, J. L. Rocabado, Rochester, L., Roda, M., Rodrigues, P., Alonso, M. J. Rodriguez, Rondon, J. Rodriguez, Rosauro-Alcaraz, S., Rosier, P., Ross, D., Rossella, M., Rossi, M., Ross-Lonergan, M., Roy, N., Roy, P., Rubbia, C., Ruggeri, A., Ruiz, G., Russell, B., Ruterbories, D., Rybnikov, A., Sacerdoti, S., Saha, S., Sahoo, S. K., Sahu, N., Sala, P., Samios, N., Samoylov, O., Sanchez, M. C., Bravo, A. Sánchez, Sánchez-Castillo, A., Sanchez-Lucas, P., Sandberg, V., Sanders, D. A., Sanfilippo, S., Sankey, D., Santoro, D., Saoulidou, N., Sapienza, P., Sarasty, C., Sarcevic, I., Sarra, I., Savage, G., Savinov, V., Scanavini, G., Scaramelli, A., Scarff, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Schuld, B., Segade, A., Segreto, E., Selyunin, A., Senadheera, D., Senise, C. R., Sensenig, J., Seo, S. H., Shaevitz, M. H., Shanahan, P., Sharma, P., Kumar, R., Poudel, S. Sharma, Shaw, K., Shaw, T., Shchablo, K., Shen, J., Shepherd-Themistocleous, C., Sheshukov, A., Shi, J., Shi, W., Shin, S., Shivakoti, S., Shoemaker, I., Shooltz, D., Shrock, R., Siddi, B., Siden, M., Silber, J., Simard, L., Sinclair, J., Sinev, G., Singh, J., Singh, L., Singh, P., Singh, V., Chauhan, S. Singh, Sipos, R., Sironneau, C., Sirri, G., Siyeon, K., Skarpaas, K., Smedley, J., Smith, E., Smith, J., Smith, P., Smolik, J., Smy, M., Snape, M., Snider, E. L., Snopok, P., Snowden-Ifft, D., Nunes, M. Soares, Sobel, H., Soderberg, M., Sokolov, S., Salinas, C. J. Solano, Söldner-Rembold, S., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Sotnikov, A., Soto-Oton, J., Sousa, A., Soustruznik, K., Spinella, F., Spitz, J., Spooner, N. J. C., Spurgeon, K., Stalder, D., Stancari, M., Stanco, L., Steenis, J., Stein, R., Steiner, H. M., Lisbôa, A. F. Steklain, Stepanova, A., Stewart, J., Stillwell, B., Stock, J., Stocker, F., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Subash, J., Surdo, A., Suter, L., Sutera, C. M., Sutton, K., Suvorov, Y., Svoboda, R., Swain, S. K., Szczerbinska, B., Szelc, A. M., Sztuc, A., Taffara, A., Talukdar, N., Tamara, J., Tanaka, H. A., Tang, S., Taniuchi, N., Casanova, A. M. Tapia, Oregui, B. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tatar, E., Tayloe, R., Tedeschi, D., Teklu, A. M., Vidal, J. Tena, Tennessen, P., Tenti, M., Terao, K., Terranova, F., Testera, G., Thakore, T., Thea, A., Thomas, S., Thompson, A., Thorn, C., Timm, S. C., Tiras, E., Tishchenko, V., Todorović, N., Tomassetti, L., Tonazzo, A., Torbunov, D., Torti, M., Tortola, M., Tortorici, F., Tosi, N., Totani, D., Toups, M., Touramanis, C., Tran, D., Travaglini, R., Trevor, J., Triller, E., Trilov, S., Truchon, J., Truncali, D., Trzaska, W. H., Tsai, Y., Tsai, Y. -T., Tsamalaidze, Z., Tsang, K. V., Tsverava, N., Tu, S. Z., Tufanli, S., Tunnell, C., Turnberg, S., Turner, J., Tuzi, M., Tyler, J., Tyley, E., Tzanov, M., Uchida, M. A., González, J. Ureña, Urheim, J., Usher, T., Utaegbulam, H., Uzunyan, S., Vagins, M. R., Vahle, P., Valder, S., Valdiviesso, G. A., Valencia, E., Valentim, R., Vallari, Z., Vallazza, E., Valle, J. W. F., Van Berg, R., Van de Water, R. G., Forero, D. V., Vannozzi, A., Van Nuland-Troost, M., Varanini, F., Oliva, D. Vargas, Vasina, S., Vaughan, N., Vaziri, K., Vázquez-Ramos, A., Vega, J., Ventura, S., Verdugo, A., Vergani, S., Verzocchi, M., Vetter, K., Vicenzi, M., de Souza, H. Vieira, Vignoli, C., Vilela, C., Villa, E., Viola, S., Viren, B., Hernandez, A. P. Vizcaya, Vuong, Q., Waldron, A. V., Wallbank, M., Walsh, J., Walton, T., Wang, H., Wang, J., Wang, L., Wang, M. H. L. S., Wang, X., Wang, Y., Warburton, K., Warner, D., Warsame, L., Wascko, M. O., Waters, D., Watson, A., Wawrowska, K., Weber, A., Weber, C. M., Weber, M., Wei, H., Weinstein, A., Westerdale, S., Wetstein, M., Whalen, K., White, A., Whitehead, L. H., Whittington, D., Wilhlemi, J., Wilking, M. J., Wilkinson, A., Wilkinson, C., Wilson, F., Wilson, R. J., Winter, P., Wisniewski, W., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wospakrik, M., Wresilo, K., Wret, C., Wu, S., Wu, W., Wurm, M., Wyenberg, J., Xiao, Y., Xiotidis, I., Yaeggy, B., Yahlali, N., Yandel, E., Yang, J., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zapata, O., Zazueta, L., Zeller, G. P., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.
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Physics - Instrumentation and Detectors ,High Energy Physics - Experiment - Abstract
The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy toward the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the European Strategy for Particle Physics. While the construction of the DUNE Phase I is well underway, this White Paper focuses on DUNE Phase II planning. DUNE Phase-II consists of a third and fourth far detector (FD) module, an upgraded near detector complex, and an enhanced 2.1 MW beam. The fourth FD module is conceived as a "Module of Opportunity", aimed at expanding the physics opportunities, in addition to supporting the core DUNE science program, with more advanced technologies. This document highlights the increased science opportunities offered by the DUNE Phase II near and far detectors, including long-baseline neutrino oscillation physics, neutrino astrophysics, and physics beyond the standard model. It describes the DUNE Phase II near and far detector technologies and detector design concepts that are currently under consideration. A summary of key R&D goals and prototyping phases needed to realize the Phase II detector technical designs is also provided. DUNE's Phase II detectors, along with the increased beam power, will complete the full scope of DUNE, enabling a multi-decadal program of groundbreaking science with neutrinos.
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- 2024
8. Measurement of inclusive jet cross section and substructure in $p$$+$$p$ collisions at $\sqrt{s_{_{NN}}}=200$ GeV
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PHENIX Collaboration, Abdulameer, N. J., Acharya, U., Aidala, C., Ajitanand, N. N., Akiba, Y., Akimoto, R., Alexander, J., Alfred, M., Andrieux, V., Antsupov, S., Aoki, K., Apadula, N., Asano, H., Atomssa, E. T., Awes, T. C., Azmoun, B., Babintsev, V., Bai, M., Bai, X., Bandara, N. S., Bannier, B., Bannikov, E., Barish, K. N., Bathe, S., Baublis, V., Baumann, C., Baumgart, S., Bazilevsky, A., Beaumier, M., Belmont, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Black, D., Blankenship, B., Blau, D. S., Bok, J. S., Borisov, V., Boyle, K., Brooks, M. L., Bryslawskyj, J., Buesching, H., Bumazhnov, V., Butsyk, S., Campbell, S., Cervantes, R., Chen, C. -H., Chen, D., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Choi, S., Christiansen, P., Chujo, T., Cianciolo, V., Citron, Z., Cole, B. A., Connors, M., Corliss, R., Cronin, N., Crossette, N., Csanád, M., Csörgő, T., D'Orazio, L., Danley, T. W., Datta, A., Daugherity, M. S., David, G., DeBlasio, K., Dehmelt, K., Denisov, A., Deshpande, A., Desmond, E. J., Ding, L., Dion, A., Dixit, D., Doomra, V., Do, J. H., Drapier, O., Drees, A., Drees, K. A., Durham, J. M., Durum, A., En'yo, H., Engelmore, T., Enokizono, A., Esha, R., Eyser, K. O., Fadem, B., Fan, W., Feege, N., Fields, D. E., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fleuret, F., Fokin, S. L., Frantz, J. E., Franz, A., Frawley, A. D., Fukao, Y., Fukuda, Y., Fusayasu, T., Gainey, K., Gallus, P., Gal, C., Garg, P., Garishvili, A., Garishvili, I., Ge, H., Giordano, F., Glenn, A., Gong, X., Gonin, M., Goto, Y., de Cassagnac, R. Granier, Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gunji, T., Guo, T., Guragain, H., Gu, Y., Hachiya, T., Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hamilton, H. F., Hanks, J., Han, S. Y., Hasegawa, S., Haseler, T. O. S., Hashimoto, K., Hayano, R., Hemmick, T. K., Hester, T., He, X., Hill, J. C., Hill, K., Hodges, A., Hollis, R. S., Homma, K., Hong, B., Hoshino, T., Hotvedt, N., Huang, J., Ichihara, T., Ikeda, Y., Imai, K., Imazu, Y., Inaba, M., Iordanova, A., Isenhower, D., Isinhue, A., Ivanishchev, D., Jeon, S. J., Jezghani, M., Jiang, X., Ji, Z., Johnson, B. M., Joo, K. S., Jouan, D., Jumper, D. S., Kamin, J., Kanda, S., Kang, B. H., Kang, J. H., Kang, J. S., Kapukchyan, D., Kapustinsky, J., Karthas, S., Kawall, D., Kazantsev, A. V., Key, J. A., Khachatryan, V., Khandai, P. K., Khanzadeev, A., Kijima, K. M., Kim, C., Kim, D. J., Kim, E. -J., Kim, M., Kim, Y. -J., Kim, Y. K., Kincses, D., Kistenev, E., Klatsky, J., Kleinjan, D., Kline, P., Koblesky, T., Kofarago, M., Komkov, B., Koster, J., Kotchetkov, D., Kotov, D., Kovacs, L., Krizek, F., Kudo, S., Kurita, K., Kurosawa, M., Kwon, Y., Lai, Y. S., Lajoie, J. G., Lebedev, A., Lee, D. M., Lee, G. H., Lee, J., Lee, K. B., Lee, K. S., Lee, S., Lee, S. H., Leitch, M. J., Leitgab, M., Leung, Y. H., Lewis, B., Lim, S. H., Liu, M. X., Li, X., Loggins, V. -R., Lokos, S., Loomis, D. A., Lovasz, K., Lynch, D., Maguire, C. F., Majoros, T., Makdisi, Y. I., Makek, M., Manion, A., Manko, V. I., Mannel, E., McCumber, M., McGaughey, P. L., McGlinchey, D., McKinney, C., Meles, A., Mendoza, M., Meredith, B., Miake, Y., Mibe, T., Mignerey, A. C., Milov, A., Mishra, D. K., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Mitsuka, G., Miyasaka, S., Mizuno, S., Mohanty, A. K., Mohapatra, S., Montuenga, P., Moon, T., Morrison, D. P., Moskowitz, M., Moukhanova, T. V., Mulilo, B., Murakami, T., Murata, J., Mwai, A., Nagae, T., Nagai, K., Nagamiya, S., Nagashima, K., Nagashima, T., Nagle, J. L., Nagy, M. I., Nakagawa, I., Nakamiya, Y., Nakamura, K. R., Nakamura, T., Nakano, K., Nattrass, C., Netrakanti, P. K., Nihashi, M., Niida, T., Nouicer, R., Novitzky, N., Novák, T., Nukazuka, G., Nyanin, A. S., O'Brien, E., Ogilvie, C. A., Oide, H., Okada, K., Koop, J. D. Orjuela, Orosz, M., Osborn, J. D., Oskarsson, A., Ottino, G. J., Ozawa, K., Pak, R., Pantuev, V., Papavassiliou, V., Park, I. H., Park, J. S., Park, S., Park, S. K., Patel, L., Patel, M., Pate, S. F., Peng, J. -C., Perepelitsa, D. V., Perera, G. D. N., Peressounko, D. Yu., PerezLara, C. E., Perry, J., Petti, R., Phipps, M., Pinkenburg, C., Pisani, R. P., Potekhin, M., Purschke, M. L., Qu, H., Rak, J., Ravinovich, I., Read, K. F., Reynolds, D., Riabov, V., Riabov, Y., Richardson, E., Richford, D., Rinn, T., Riveli, N., Roach, D., Rolnick, S. D., Rosati, M., Rowan, Z., Ryu, M. S., Safonov, A. S., Sahlmueller, B., Saito, N., Sakaguchi, T., Sako, H., Samsonov, V., Sarsour, M., Sato, S., Sawada, S., Schaefer, B., Schmoll, B. K., Sedgwick, K., Seele, J., Seidl, R., Sekiguchi, Y., Seleznev, A., Sen, A., Seto, R., Sett, P., Sexton, A., Sharma, D., Shaver, A., Shein, I., Shibata, T. -A., Shigaki, K., Shimomura, M., Shioya, T., Shoji, K., Shukla, P., Sickles, A., Silva, C. L., Silvermyr, D., Singh, B. K., Singh, C. P., Singh, V., Skolnik, M., Slunečka, M., Smith, K. L., Snowball, M., Solano, S., Soltz, R. A., Sondheim, W. E., Sorensen, S. P., Sourikova, I. V., Stankus, P. W., Steinberg, P., Stenlund, E., Stepanov, M., Ster, A., Stoll, S. P., Stone, M. R., Sugitate, T., Sukhanov, A., Sumita, T., Sun, J., Sun, Z., Sziklai, J., Takahara, A., Taketani, A., Tanaka, Y., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Taranenko, A., Tarnai, G., Tennant, E., Tieulent, R., Timilsina, A., Todoroki, T., Tomášek, M., Torii, H., Towell, C. L., Towell, R. S., Tserruya, I., Ueda, Y., Ujvari, B., van Hecke, H. W., Vargyas, M., Vazquez-Zambrano, E., Veicht, A., Velkovska, J., Virius, M., Vrba, V., Vukman, N., Vznuzdaev, E., Vértesi, R., Wang, X. R., Watanabe, D., Watanabe, K., Watanabe, Y., Watanabe, Y. S., Wei, F., Whitaker, S., Wolin, S., Woody, C. L., Wysocki, M., Xia, B., Xue, L., Xu, C., Xu, Q., Yalcin, S., Yamaguchi, Y. L., Yamamoto, H., Yanovich, A., Yokkaichi, S., Yoon, I., Yoo, J. H., Younus, I., You, Z., Yushmanov, I. E., Yu, H., Zajc, W. A., Zelenski, A., Zhou, S., and Zou, L.
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High Energy Physics - Experiment ,Nuclear Experiment - Abstract
The jet cross-section and jet-substructure observables in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV were measured by the PHENIX Collaboration at the Relativistic Heavy Ion Collider (RHIC). Jets are reconstructed from charged-particle tracks and electromagnetic-calorimeter clusters using the anti-$k_{t}$ algorithm with a jet radius $R=0.3$ for jets with transverse momentum within $8.0
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- 2024
9. deepmriprep: Voxel-based Morphometry (VBM) Preprocessing via Deep Neural Networks
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Fisch, Lukas, Winter, Nils R., Goltermann, Janik, Barkhau, Carlotta, Emden, Daniel, Ernsting, Jan, Konowski, Maximilian, Leenings, Ramona, Borgers, Tiana, Flinkenflügel, Kira, Grotegerd, Dominik, Kraus, Anna, Leehr, Elisabeth J., Meinert, Susanne, Stein, Frederike, Teutenberg, Lea, Thomas-Odenthal, Florian, Usemann, Paula, Hermesdorf, Marco, Jamalabadi, Hamidreza, Jansen, Andreas, Nenadic, Igor, Straube, Benjamin, Kircher, Tilo, Berger, Klaus, Risse, Benjamin, Dannlowski, Udo, and Hahn, Tim
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Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Voxel-based Morphometry (VBM) has emerged as a powerful approach in neuroimaging research, utilized in over 7,000 studies since the year 2000. Using Magnetic Resonance Imaging (MRI) data, VBM assesses variations in the local density of brain tissue and examines its associations with biological and psychometric variables. Here, we present deepmriprep, a neural network-based pipeline that performs all necessary preprocessing steps for VBM analysis of T1-weighted MR images using deep neural networks. Utilizing the Graphics Processing Unit (GPU), deepmriprep is 37 times faster than CAT12, the leading VBM preprocessing toolbox. The proposed method matches CAT12 in accuracy for tissue segmentation and image registration across more than 100 datasets and shows strong correlations in VBM results. Tissue segmentation maps from deepmriprep have over 95% agreement with ground truth maps, and its non-linear registration, using supervised SYMNet, predicts smooth deformation fields comparable to CAT12. The high processing speed of deepmriprep enables rapid preprocessing of extensive datasets and thereby fosters the application of VBM analysis to large-scale neuroimaging studies and opens the door to real-time applications. Finally, deepmripreps straightforward, modular design enables researchers to easily understand, reuse, and advance the underlying methods, fostering further advancements in neuroimaging research. deepmriprep can be conveniently installed as a Python package and is publicly accessible at https://github.com/wwu-mmll/deepmriprep.
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- 2024
10. Improved background modeling for dark matter search with COSINE-100
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Yu, G. H., Carlin, N., Cho, J. Y., Choi, J. J., Choi, S., Ezeribe, A. C., Franca, L. E., Ha, C., Hahn, I. S., Hollick, S. J., Jeon, E. J., Joo, H. W., Kang, W. G., Kauer, M., Kim, B. H., Kim, H. J., Kim, J., Kim, K. W., Kim, S. H., Kim, S. K., Kim, W. K., Kim, Y. D., Kim, Y. H., Ko, Y. J., Lee, D. H., Lee, E. K., Lee, H., Lee, H. S., Lee, H. Y., Lee, I. S., Lee, J., Lee, J. Y., Lee, M. H., Lee, S. H., Lee, S. M., Lee, Y. J., Leonard, D. S., Luan, N. T., Manzato, B. B., Maruyama, R. H., Neal, R. J., Olsen, S. L., Park, B. J., Park, H. K., Park, H. S., Park, J. C., Park, K. S., Park, S. D., Pitta, R. L. C., Prihtiadi, H., Ra, S. J., Rott, C., Shin, K. A., Cavalcante, D. F. F. S., Son, M. K., Spooner, N. J. C., Truc, L. T., and Yang, L.
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Astrophysics - Instrumentation and Methods for Astrophysics ,High Energy Physics - Experiment ,Physics - Instrumentation and Detectors - Abstract
COSINE-100 aims to conclusively test the claimed dark matter annual modulation signal detected by DAMA/LIBRA collaboration. DAMA/LIBRA has released updated analysis results by lowering the energy threshold to 0.75 keV through various upgrades. They have consistently claimed to have observed the annual modulation. In COSINE-100, it is crucial to lower the energy threshold for a direct comparison with DAMA/LIBRA, which also enhances the sensitivity of the search for low-mass dark matter, enabling COSINE-100 to explore this area. Therefore, it is essential to have a precise and quantitative understanding of the background spectrum across all energy ranges. This study expands the background modeling from 0.7 to 4000 keV using 2.82 years of COSINE-100 data. The modeling has been improved to describe the background spectrum across all energy ranges accurately. Assessments of the background spectrum are presented, considering the nonproportionality of NaI(Tl) crystals at both low and high energies and the characteristic X-rays produced by the interaction of external backgrounds with materials such as copper. Additionally, constraints on the fit parameters obtained from the alpha spectrum modeling fit are integrated into this model. These improvements are detailed in the paper.
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- 2024
11. Quantitative 3D Map Accuracy Evaluation Hardware and Algorithm for LiDAR(-Inertial) SLAM
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Hahn, Sanghyun, Oh, Seunghun, Jung, Minwoo, Kim, Ayoung, and Jung, Sangwoo
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Computer Science - Robotics - Abstract
Accuracy evaluation of a 3D pointcloud map is crucial for the development of autonomous driving systems. In this work, we propose a user-independent software/hardware system that can quantitatively evaluate the accuracy of a 3D pointcloud map acquired from LiDAR(-Inertial) SLAM. We introduce a LiDAR target that functions robustly in the outdoor environment, while remaining observable by LiDAR. We also propose a software algorithm that automatically extracts representative points and calculates the accuracy of the 3D pointcloud map by leveraging GPS position data. This methodology overcomes the limitations of the manual selection method, that its result varies between users. Furthermore, two different error metrics, relative and absolute errors, are introduced to analyze the accuracy from different perspectives. Our implementations are available at: https://github.com/SangwooJung98/3D_Map_Evaluation, Comment: ICCAS 2024 accepted, 5 pages, 6 figures, 2 Tables
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- 2024
12. A New Dataset, Notation Software, and Representation for Computational Schenkerian Analysis
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Ni-Hahn, Stephen, Xu, Weihan, Yin, Jerry, Zhu, Rico, Mak, Simon, Jiang, Yue, and Rudin, Cynthia
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Computer Science - Sound ,Computer Science - Artificial Intelligence - Abstract
Schenkerian Analysis (SchA) is a uniquely expressive method of music analysis, combining elements of melody, harmony, counterpoint, and form to describe the hierarchical structure supporting a work of music. However, despite its powerful analytical utility and potential to improve music understanding and generation, SchA has rarely been utilized by the computer music community. This is in large part due to the paucity of available high-quality data in a computer-readable format. With a larger corpus of Schenkerian data, it may be possible to infuse machine learning models with a deeper understanding of musical structure, thus leading to more "human" results. To encourage further research in Schenkerian analysis and its potential benefits for music informatics and generation, this paper presents three main contributions: 1) a new and growing dataset of SchAs, the largest in human- and computer-readable formats to date (>140 excerpts), 2) a novel software for visualization and collection of SchA data, and 3) a novel, flexible representation of SchA as a heterogeneous-edge graph data structure.
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- 2024
13. Inverse designing metamaterials with programmable nonlinear functional responses in graph space
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Maurizi, Marco, Xu, Derek, Wang, Yu-Tong, Yao, Desheng, Hahn, David, Oudich, Mourad, Satpati, Anish, Bauchy, Mathieu, Wang, Wei, Sun, Yizhou, Jing, Yun, and Zheng, Xiaoyu Rayne
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Condensed Matter - Materials Science ,Computer Science - Machine Learning - Abstract
Material responses to static and dynamic stimuli, represented as nonlinear curves, are design targets for engineering functionalities like structural support, impact protection, and acoustic and photonic bandgaps. Three-dimensional metamaterials offer significant tunability due to their internal structure, yet existing methods struggle to capture their complex behavior-to-structure relationships. We present GraphMetaMat, a graph-based framework capable of designing three-dimensional metamaterials with programmable responses and arbitrary manufacturing constraints. Integrating graph networks, physics biases, reinforcement learning, and tree search, GraphMetaMat can target stress-strain curves spanning four orders of magnitude and complex behaviors, as well as viscoelastic transmission responses with varying attenuation gaps. GraphMetaMat can create cushioning materials for protective equipment and vibration-damping panels for electric vehicles, outperforming commercial materials, and enabling the automatic design of materials with on-demand functionalities., Comment: 19 pages, 5 figures
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- 2024
14. Large-scale cosmic ray anisotropies with 19 years of data from the Pierre Auger Observatory
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The Pierre Auger Collaboration, Halim, A. Abdul, Abreu, P., Aglietta, M., Allekotte, I., Cheminant, K. Almeida, Almela, A., Aloisio, R., Alvarez-Muñiz, J., Ambrosone, A., Yebra, J. Ammerman, Anastasi, G. A., Anchordoqui, L., Andrada, B., Dourado, L. Andrade, Andringa, S., Apollonio, L., Aramo, C., Ferreira, P. R. Araújo, Arnone, E., Velázquez, J. C. Arteaga, Assis, P., Avila, G., Avocone, E., Bakalova, A., Barbato, F., Mocellin, A. Bartz, Bellido, J. A., Berat, C., Bertaina, M. E., Bhatta, G., Bianciotto, M., Biermann, P. L., Binet, V., Bismark, K., Bister, T., Biteau, J., Blazek, J., Bleve, C., Blümer, J., Boháčová, M., Boncioli, D., Bonifazi, C., Arbeletche, L. Bonneau, Borodai, N., Brack, J., Orchera, P. G. Brichetto, Briechle, F. L., Bueno, A., Buitink, S., Buscemi, M., Büsken, M., Bwembya, A., Caballero-Mora, K. S., Cabana-Freire, S., Caccianiga, L., Campuzano, F., Caruso, R., Castellina, A., Catalani, F., Cataldi, G., Cazon, L., Cerda, M., Čermáková, B., Cermenati, A., Chinellato, J. A., Chudoba, J., Chytka, L., Clay, R. W., Cerutti, A. C. Cobos, Colalillo, R., Conceição, R., Condorelli, A., Consolati, G., Conte, M., Convenga, F., Santos, D. Correia dos, Costa, P. J., Covault, C. E., Cristinziani, M., Sanchez, C. S. Cruz, Dasso, S., Daumiller, K., Dawson, B. R., de Almeida, R. M., de Errico, B., de Jesús, J., de Jong, S. J., Neto, J. R. T. de Mello, De Mitri, I., de Oliveira, J., Franco, D. de Oliveira, de Palma, F., de Souza, V., De Vito, E., Del Popolo, A., Deligny, O., Denner, N., Deval, L., di Matteo, A., Dobrigkeit, C., D'Olivo, J. C., Mendes, L. M. Domingues, Dorosti, Q., Anjos, J. C. dos, Anjos, R. C. dos, Ebr, J., Ellwanger, F., Emam, M., Engel, R., Epicoco, I., Erdmann, M., Etchegoyen, A., Evoli, C., Falcke, H., Farrar, G., Fauth, A. C., Fehler, T., Feldbusch, F., Fernandes, A., Fick, B., Figueira, J. M., Filip, P., Filipčič, A., Fitoussi, T., Flaggs, B., Fodran, T., Freitas, M., Fujii, T., Fuster, A., Galea, C., García, B., Gaudu, C., Ghia, P. L., Giaccari, U., Gobbi, F., Gollan, F., Golup, G., Berisso, M. Gómez, Vitale, P. F. Gómez, Gongora, J. P., González, J. M., González, N., Góra, D., Gorgi, A., Gottowik, M., Guarino, F., Guedes, G. P., Guido, E., Gülzow, L., Hahn, S., Hamal, P., Hampel, M. R., Hansen, P., Harvey, V. M., Haungs, A., Hebbeker, T., Hojvat, C., Hörandel, J. R., Horvath, P., Hrabovský, M., Huege, T., Insolia, A., Isar, P. G., Janecek, P., Jilek, V., Jurysek, J., Kampert, K. -H., Keilhauer, B., Khakurdikar, A., Covilakam, V. V. Kizakke, Klages, H. O., Kleifges, M., Knapp, F., Köhler, J., Krieger, F., Kubatova, M., Kunka, N., Lago, B. L., Langner, N., de Oliveira, M. A. Leigui, Lema-Capeans, Y., Letessier-Selvon, A., Lhenry-Yvon, I., Lopes, L., Lundquist, J. P., Payeras, A. Machado, Mandat, D., Manning, B. C., Mantsch, P., Mariani, F. M., Mariazzi, A. G., Mariş, I. C., Marsella, G., Martello, D., Martinelli, S., Bravo, O. Martínez, Martins, M. A., Mathes, H. -J., Matthews, J., Matthiae, G., Mayotte, E., Mayotte, S., Mazur, P. O., Medina-Tanco, G., Meinert, J., Melo, D., Menshikov, A., Merx, C., Michal, S., Micheletti, M. I., Miramonti, L., Mollerach, S., Montanet, F., Morejon, L., Mulrey, K., Mussa, R., Namasaka, W. M., Negi, S., Nellen, L., Nguyen, K., Nicora, G., Niechciol, M., Nitz, D., Nosek, D., Novotny, V., Nožka, L., Nucita, A., Núñez, L. A., Oliveira, C., Palatka, M., Pallotta, J., Panja, S., Parente, G., Paulsen, T., Pawlowsky, J., Pech, M., Pękala, J., Pelayo, R., Pelgrims, V., Pereira, L. A. S., Martins, E. E. Pereira, Bertolli, C. Pérez, Perrone, L., Petrera, S., Petrucci, C., Pierog, T., Pimenta, M., Platino, M., Pont, B., Pothast, M., Shahvar, M. Pourmohammad, Privitera, P., Prouza, M., Querchfeld, S., Rautenberg, J., Ravignani, D., Akim, J. V. Reginatto, Reuzki, A., Ridky, J., Riehn, F., Risse, M., Rizi, V., Rodriguez, E., Rojo, J. Rodriguez, Roncoroni, M. J., Rossoni, S., Roth, M., Roulet, E., Rovero, A. C., Saftoiu, A., Saharan, M., Salamida, F., Salazar, H., Salina, G., Sampathkumar, P., Gomez, J. D. Sanabria, Sánchez, F., Santos, E. M., Santos, E., Sarazin, F., Sarmento, R., Sato, R., Schäfer, C. M., Scherini, V., Schieler, H., Schimassek, M., Schimp, M., Schmidt, D., Scholten, O., Schoorlemmer, H., Schovánek, P., Schröder, F. G., Schulte, J., Schulz, T., Sciutto, S. J., Scornavacche, M., Sedoski, A., Segreto, A., Sehgal, S., Shivashankara, S. U., Sigl, G., Simkova, K., Simon, F., Šmída, R., Sommers, P., Squartini, R., Stadelmaier, M., Stanič, S., Stasielak, J., Stassi, P., Strähnz, S., Straub, M., Suomijärvi, T., Supanitsky, A. D., Svozilikova, Z., Szadkowski, Z., Tairli, F., Tapia, A., Taricco, C., Timmermans, C., Tkachenko, O., Tobiska, P., Peixoto, C. J. Todero, Tomé, B., Torrès, Z., Travaini, A., Travnicek, P., Tueros, M., Unger, M., Uzeiroska, R., Vaclavek, L., Vacula, M., Galicia, J. F. Valdés, Valore, L., Varela, E., Vašíčková, V., Vásquez-Ramírez, A., Veberič, D., Quispe, I. D. Vergara, Verzi, V., Vicha, J., Vink, J., Vorobiov, S., Watanabe, C., Watson, A. A., Weindl, A., Weitz, M., Wiencke, L., Wilczyński, H., Wittkowski, D., Wundheiler, B., Yue, B., Yushkov, A., Zapparrata, O., Zas, E., Zavrtanik, D., and Zavrtanik, M.
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Astrophysics - High Energy Astrophysical Phenomena - Abstract
Results are presented for the measurement of large-scale anisotropies in the arrival directions of ultra-high-energy cosmic rays detected at the Pierre Auger Observatory during 19 years of operation, prior to AugerPrime, the upgrade of the Observatory. The 3D dipole amplitude and direction are reconstructed above $4\,$EeV in four energy bins. Besides the established dipolar anisotropy in right ascension above $8\,$EeV, the Fourier amplitude of the $8$ to $16\,$EeV energy bin is now also above the $5\sigma$ discovery level. No time variation of the dipole moment above $8\,$EeV is found, setting an upper limit to the rate of change of such variations of $0.3\%$ per year at the $95\%$ confidence level. Additionally, the results for the angular power spectrum are shown, demonstrating no other statistically significant multipoles. The results for the equatorial dipole component down to $0.03\,$EeV are presented, using for the first time a data set obtained with a trigger that has been optimized for lower energies. Finally, model predictions are discussed and compared with observations, based on two source emission scenarios obtained in the combined fit of spectrum and composition above $0.6\,$EeV.
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- 2024
15. On the Liouville-von Neumann equation for unbounded Hamiltonians
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Lonigro, Davide, Hahn, Alexander, and Burgarth, Daniel
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Quantum Physics ,Mathematical Physics - Abstract
The evolution of mixed states of a closed quantum system is described by a group of evolution superoperators whose infinitesimal generator (the quantum Liouville superoperator, or Liouvillian) determines the mixed-state counterpart of the Schr\"odinger equation: the Liouville-von Neumann equation. When the state space of the system is infinite-dimensional, the Liouville superoperator is unbounded whenever the corresponding Hamiltonian is. In this paper, we provide a rigorous, pedagogically-oriented, and self-contained introduction to the quantum Liouville formalism in the presence of unbounded operators. We present and discuss a characterization of the domain of the Liouville superoperator originally due to M. Courbage; starting from that, we develop some simpler characterizations of the domain of the Liouvillian and its square. We also provide, with explicit proofs, some domains of essential self-adjointness (cores) of the Liouvillian., Comment: 22 pages
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- 2024
16. Reasoning about Study Regulations in Answer Set Programming
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Hahn, Susana, Martens, Cedric, Nemes, Amade, Otunuya, Henry, Romero, Javier, Schaub, Torsten, and Schellhorn, Sebastian
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Computer Science - Artificial Intelligence - Abstract
We are interested in automating reasoning with and about study regulations, catering to various stakeholders, ranging from administrators, over faculty, to students at different stages. Our work builds on an extensive analysis of various study programs at the University of Potsdam. The conceptualization of the underlying principles provides us with a formal account of study regulations. In particular, the formalization reveals the properties of admissible study plans. With these at end, we propose an encoding of study regulations in Answer Set Programming that produces corresponding study plans. Finally, we show how this approach can be extended to a generic user interface for exploring study plans., Comment: To appear in Theory and Practise of Logic Programming
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- 2024
17. Electron-beam-induced modification of gold microparticles in an SEM
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Weinel, Kristina, Hahn, Marc Benjamin, Lubk, Axel, Feng, Wen, Martinez, Ignacio Gonzalez, Büchner, Bernd, and Jácome, Leonardo Agudo
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Condensed Matter - Materials Science - Abstract
Electron-beam-induced conversion of materials in a transmission electron microscope uses the high power density of a localized electron beam of acceleration voltages above 100 kV as an energy source to transform matter at the sub-micron scale. Here, the e-beam-induced transformation of precursor microparticles employing a low-energy e-beam with an acceleration voltage of 30 kV in a scanning electron microscope is developed to increase the versatility and efficiency of the technique. Under these conditions, the technique can be classified between e-beam lithography, where the e-beam is used to mill holes in or grow some different material onto a substrate, and e-beam welding, where matter can be welded together when overcoming the melting phase. Modifying gold microparticles on an amorphous SiOx substrate reveals the dominant role of inelastic electron-matter interaction and subsequent localized heating for the observed melting and vaporization of the precursor microparticles under the electron beam. Monte-Carlo scattering simulations and thermodynamic modeling further support the findings.
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- 2024
18. First Measurement of the Total Inelastic Cross-Section of Positively-Charged Kaons on Argon at Energies Between 5.0 and 7.5 GeV
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DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Alves, T., Amar, H., Amedo, P., Anderson, J., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antic, D., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azam, M. B., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barbu, D., Barenboim, G., Barham~Alzás, P., Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernal, J., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Bodek, A., Bogenschuetz, J., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bouet, R., Boza, J., Bracinik, J., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Bundock, A., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chakraborty, S., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chiapponi, F., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collazo, J., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Curciarello, F., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., Dallaway, W., D'Amico, R., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., Sanchez, P. Del Amo, De la Torre, A., De Lauretis, G., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., De Matteis, G., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Diaz, A., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farrell, S., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferry, G., Fialova, E., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gaba, R., Gabrielli, A., M~Gago, A., Galizzi, F., Gallagher, H., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. 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High Energy Physics - Experiment ,Physics - Instrumentation and Detectors - Abstract
ProtoDUNE Single-Phase (ProtoDUNE-SP) is a 770-ton liquid argon time projection chamber that operated in a hadron test beam at the CERN Neutrino Platform in 2018. We present a measurement of the total inelastic cross section of charged kaons on argon as a function of kaon energy using 6 and 7 GeV/$c$ beam momentum settings. The flux-weighted average of the extracted inelastic cross section at each beam momentum setting was measured to be 380$\pm$26 mbarns for the 6 GeV/$c$ setting and 379$\pm$35 mbarns for the 7 GeV/$c$ setting.
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- 2024
19. Algorithms for Collaborative Machine Learning under Statistical Heterogeneity
- Author
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Hahn, Seok-Ju
- Subjects
Statistics - Machine Learning ,Computer Science - Distributed, Parallel, and Cluster Computing ,Computer Science - Machine Learning - Abstract
Learning from distributed data without accessing them is undoubtedly a challenging and non-trivial task. Nevertheless, the necessity for distributed training of a statistical model has been increasing, due to the privacy concerns of local data owners and the cost in centralizing the massively distributed data. Federated learning (FL) is currently the de facto standard of training a machine learning model across heterogeneous data owners, without leaving the raw data out of local silos. Nevertheless, several challenges must be addressed in order for FL to be more practical in reality. Among these challenges, the statistical heterogeneity problem is the most significant and requires immediate attention. From the main objective of FL, three major factors can be considered as starting points -- \textit{parameter}, textit{mixing coefficient}, and \textit{local data distributions}. In alignment with the components, this dissertation is organized into three parts. In Chapter II, a novel personalization method, \texttt{SuPerFed}, inspired by the mode-connectivity is introduced. In Chapter III, an adaptive decision-making algorithm, \texttt{AAggFF}, is introduced for inducing uniform performance distributions in participating clients, which is realized by online convex optimization framework. Finally, in Chapter IV, a collaborative synthetic data generation method, \texttt{FedEvg}, is introduced, leveraging the flexibility and compositionality of an energy-based modeling approach. Taken together, all of these approaches provide practical solutions to mitigate the statistical heterogeneity problem in data-decentralized settings, paving the way for distributed systems and applications using collaborative machine learning methods., Comment: Doctoral Dissertation. For the conference version of Chapter II, see arXiv:2109.07628v3, and for the conference version of Chapter III, see arXiv:2405.20821v1
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- 2024
20. The Llama 3 Herd of Models
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Dubey, Abhimanyu, Jauhri, Abhinav, Pandey, Abhinav, Kadian, Abhishek, Al-Dahle, Ahmad, Letman, Aiesha, Mathur, Akhil, Schelten, Alan, Yang, Amy, Fan, Angela, Goyal, Anirudh, Hartshorn, Anthony, Yang, Aobo, Mitra, Archi, Sravankumar, Archie, Korenev, Artem, Hinsvark, Arthur, Rao, Arun, Zhang, Aston, Rodriguez, Aurelien, Gregerson, Austen, Spataru, Ava, Roziere, Baptiste, Biron, Bethany, Tang, Binh, Chern, Bobbie, Caucheteux, Charlotte, Nayak, Chaya, Bi, Chloe, Marra, Chris, McConnell, Chris, Keller, Christian, Touret, Christophe, Wu, Chunyang, Wong, Corinne, Ferrer, Cristian Canton, Nikolaidis, Cyrus, Allonsius, Damien, Song, Daniel, Pintz, Danielle, Livshits, Danny, Esiobu, David, Choudhary, Dhruv, Mahajan, Dhruv, Garcia-Olano, Diego, Perino, Diego, Hupkes, Dieuwke, Lakomkin, Egor, AlBadawy, Ehab, Lobanova, Elina, Dinan, Emily, Smith, Eric Michael, Radenovic, Filip, Zhang, Frank, Synnaeve, Gabriel, Lee, Gabrielle, Anderson, Georgia Lewis, Nail, Graeme, Mialon, Gregoire, Pang, Guan, Cucurell, Guillem, Nguyen, Hailey, Korevaar, Hannah, Xu, Hu, Touvron, Hugo, Zarov, Iliyan, Ibarra, Imanol Arrieta, Kloumann, Isabel, Misra, Ishan, Evtimov, Ivan, Copet, Jade, Lee, Jaewon, Geffert, Jan, Vranes, Jana, Park, Jason, Mahadeokar, Jay, Shah, Jeet, van der Linde, Jelmer, Billock, Jennifer, Hong, Jenny, Lee, Jenya, Fu, Jeremy, Chi, Jianfeng, Huang, Jianyu, Liu, Jiawen, Wang, Jie, Yu, Jiecao, Bitton, Joanna, Spisak, Joe, Park, Jongsoo, Rocca, Joseph, Johnstun, Joshua, Saxe, Joshua, Jia, Junteng, Alwala, Kalyan Vasuden, Upasani, Kartikeya, Plawiak, Kate, Li, Ke, Heafield, Kenneth, Stone, Kevin, El-Arini, Khalid, Iyer, Krithika, Malik, Kshitiz, Chiu, Kuenley, Bhalla, Kunal, Rantala-Yeary, Lauren, van der Maaten, Laurens, Chen, Lawrence, Tan, Liang, Jenkins, Liz, Martin, Louis, Madaan, Lovish, Malo, Lubo, Blecher, Lukas, Landzaat, Lukas, de Oliveira, Luke, Muzzi, Madeline, Pasupuleti, Mahesh, Singh, Mannat, Paluri, Manohar, Kardas, Marcin, Oldham, Mathew, Rita, Mathieu, Pavlova, Maya, Kambadur, Melanie, Lewis, Mike, Si, Min, Singh, Mitesh Kumar, Hassan, Mona, Goyal, Naman, Torabi, Narjes, Bashlykov, Nikolay, Bogoychev, Nikolay, Chatterji, Niladri, Duchenne, Olivier, Çelebi, Onur, Alrassy, Patrick, Zhang, Pengchuan, Li, Pengwei, Vasic, Petar, Weng, Peter, Bhargava, Prajjwal, Dubal, Pratik, Krishnan, Praveen, Koura, Punit Singh, Xu, Puxin, He, Qing, Dong, Qingxiao, Srinivasan, Ragavan, Ganapathy, Raj, Calderer, Ramon, Cabral, Ricardo Silveira, Stojnic, Robert, Raileanu, Roberta, Girdhar, Rohit, Patel, Rohit, Sauvestre, Romain, Polidoro, Ronnie, Sumbaly, Roshan, Taylor, Ross, Silva, Ruan, Hou, Rui, Wang, Rui, Hosseini, Saghar, Chennabasappa, Sahana, Singh, Sanjay, Bell, Sean, Kim, Seohyun Sonia, Edunov, Sergey, Nie, Shaoliang, Narang, Sharan, Raparthy, Sharath, Shen, Sheng, Wan, Shengye, Bhosale, Shruti, Zhang, Shun, Vandenhende, Simon, Batra, Soumya, Whitman, Spencer, Sootla, Sten, Collot, Stephane, Gururangan, Suchin, Borodinsky, Sydney, Herman, Tamar, Fowler, Tara, Sheasha, Tarek, Georgiou, Thomas, Scialom, Thomas, Speckbacher, Tobias, Mihaylov, Todor, Xiao, Tong, Karn, Ujjwal, Goswami, Vedanuj, Gupta, Vibhor, Ramanathan, Vignesh, Kerkez, Viktor, Gonguet, Vincent, Do, Virginie, Vogeti, Vish, Petrovic, Vladan, Chu, Weiwei, Xiong, Wenhan, Fu, Wenyin, Meers, Whitney, Martinet, Xavier, Wang, Xiaodong, Tan, Xiaoqing Ellen, Xie, Xinfeng, Jia, Xuchao, Wang, Xuewei, Goldschlag, Yaelle, Gaur, Yashesh, Babaei, Yasmine, Wen, Yi, Song, Yiwen, Zhang, Yuchen, Li, Yue, Mao, Yuning, Coudert, Zacharie Delpierre, Yan, Zheng, Chen, Zhengxing, Papakipos, Zoe, Singh, Aaditya, Grattafiori, Aaron, Jain, Abha, Kelsey, Adam, Shajnfeld, Adam, Gangidi, Adithya, Victoria, Adolfo, Goldstand, Ahuva, Menon, Ajay, Sharma, Ajay, Boesenberg, Alex, Vaughan, Alex, Baevski, Alexei, Feinstein, Allie, Kallet, Amanda, Sangani, Amit, Yunus, Anam, Lupu, Andrei, Alvarado, Andres, Caples, Andrew, Gu, Andrew, Ho, Andrew, Poulton, Andrew, Ryan, Andrew, Ramchandani, Ankit, Franco, Annie, Saraf, Aparajita, Chowdhury, Arkabandhu, Gabriel, Ashley, Bharambe, Ashwin, Eisenman, Assaf, Yazdan, Azadeh, James, Beau, Maurer, Ben, Leonhardi, Benjamin, Huang, Bernie, Loyd, Beth, De Paola, Beto, Paranjape, Bhargavi, Liu, Bing, Wu, Bo, Ni, Boyu, Hancock, Braden, Wasti, Bram, Spence, Brandon, Stojkovic, Brani, Gamido, Brian, Montalvo, Britt, Parker, Carl, Burton, Carly, Mejia, Catalina, Wang, Changhan, Kim, Changkyu, Zhou, Chao, Hu, Chester, Chu, Ching-Hsiang, Cai, Chris, Tindal, Chris, Feichtenhofer, Christoph, Civin, Damon, Beaty, Dana, Kreymer, Daniel, Li, Daniel, Wyatt, Danny, Adkins, David, Xu, David, Testuggine, Davide, David, Delia, Parikh, Devi, Liskovich, Diana, Foss, Didem, Wang, Dingkang, Le, Duc, Holland, Dustin, Dowling, Edward, Jamil, Eissa, Montgomery, Elaine, Presani, Eleonora, Hahn, Emily, Wood, Emily, Brinkman, Erik, Arcaute, Esteban, Dunbar, Evan, Smothers, Evan, Sun, Fei, Kreuk, Felix, Tian, Feng, Ozgenel, Firat, Caggioni, Francesco, Guzmán, Francisco, Kanayet, Frank, Seide, Frank, Florez, Gabriela Medina, Schwarz, Gabriella, Badeer, Gada, Swee, Georgia, Halpern, Gil, Thattai, Govind, Herman, Grant, Sizov, Grigory, Guangyi, Zhang, Lakshminarayanan, Guna, Shojanazeri, Hamid, Zou, Han, Wang, Hannah, Zha, Hanwen, Habeeb, Haroun, Rudolph, Harrison, Suk, Helen, Aspegren, Henry, Goldman, Hunter, Damlaj, Ibrahim, Molybog, Igor, Tufanov, Igor, Veliche, Irina-Elena, Gat, Itai, Weissman, Jake, Geboski, James, Kohli, James, Asher, Japhet, Gaya, Jean-Baptiste, Marcus, Jeff, Tang, Jeff, Chan, Jennifer, Zhen, Jenny, Reizenstein, Jeremy, Teboul, Jeremy, Zhong, Jessica, Jin, Jian, Yang, Jingyi, Cummings, Joe, Carvill, Jon, Shepard, Jon, McPhie, Jonathan, Torres, Jonathan, Ginsburg, Josh, Wang, Junjie, Wu, Kai, U, Kam Hou, Saxena, Karan, Prasad, Karthik, Khandelwal, Kartikay, Zand, Katayoun, Matosich, Kathy, Veeraraghavan, Kaushik, Michelena, Kelly, Li, Keqian, Huang, Kun, Chawla, Kunal, Lakhotia, Kushal, Huang, Kyle, Chen, Lailin, Garg, Lakshya, A, Lavender, Silva, Leandro, Bell, Lee, Zhang, Lei, Guo, Liangpeng, Yu, Licheng, Moshkovich, Liron, Wehrstedt, Luca, Khabsa, Madian, Avalani, Manav, Bhatt, Manish, Tsimpoukelli, Maria, Mankus, Martynas, Hasson, Matan, Lennie, Matthew, Reso, Matthias, Groshev, Maxim, Naumov, Maxim, Lathi, Maya, Keneally, Meghan, Seltzer, Michael L., Valko, Michal, Restrepo, Michelle, Patel, Mihir, Vyatskov, Mik, Samvelyan, Mikayel, Clark, Mike, Macey, Mike, Wang, Mike, Hermoso, Miquel Jubert, Metanat, Mo, Rastegari, Mohammad, Bansal, Munish, Santhanam, Nandhini, Parks, Natascha, White, Natasha, Bawa, Navyata, Singhal, Nayan, Egebo, Nick, Usunier, Nicolas, Laptev, Nikolay Pavlovich, Dong, Ning, Zhang, Ning, Cheng, Norman, Chernoguz, Oleg, Hart, Olivia, Salpekar, Omkar, Kalinli, Ozlem, Kent, Parkin, Parekh, Parth, Saab, Paul, Balaji, Pavan, Rittner, Pedro, Bontrager, Philip, Roux, Pierre, Dollar, Piotr, Zvyagina, Polina, Ratanchandani, Prashant, Yuvraj, Pritish, Liang, Qian, Alao, Rachad, Rodriguez, Rachel, Ayub, Rafi, Murthy, Raghotham, Nayani, Raghu, Mitra, Rahul, Li, Raymond, Hogan, Rebekkah, Battey, Robin, Wang, Rocky, Maheswari, Rohan, Howes, Russ, Rinott, Ruty, Bondu, Sai Jayesh, Datta, Samyak, Chugh, Sara, Hunt, Sara, Dhillon, Sargun, Sidorov, Sasha, Pan, Satadru, Verma, Saurabh, Yamamoto, Seiji, Ramaswamy, Sharadh, Lindsay, Shaun, Feng, Sheng, Lin, Shenghao, Zha, Shengxin Cindy, Shankar, Shiva, Zhang, Shuqiang, Wang, Sinong, Agarwal, Sneha, Sajuyigbe, Soji, Chintala, Soumith, Max, Stephanie, Chen, Stephen, Kehoe, Steve, Satterfield, Steve, Govindaprasad, Sudarshan, Gupta, Sumit, Cho, Sungmin, Virk, Sunny, Subramanian, Suraj, Choudhury, Sy, Goldman, Sydney, Remez, Tal, Glaser, Tamar, Best, Tamara, Kohler, Thilo, Robinson, Thomas, Li, Tianhe, Zhang, Tianjun, Matthews, Tim, Chou, Timothy, Shaked, Tzook, Vontimitta, Varun, Ajayi, Victoria, Montanez, Victoria, Mohan, Vijai, Kumar, Vinay Satish, Mangla, Vishal, Albiero, Vítor, Ionescu, Vlad, Poenaru, Vlad, Mihailescu, Vlad Tiberiu, Ivanov, Vladimir, Li, Wei, Wang, Wenchen, Jiang, Wenwen, Bouaziz, Wes, Constable, Will, Tang, Xiaocheng, Wang, Xiaofang, Wu, Xiaojian, Wang, Xiaolan, Xia, Xide, Wu, Xilun, Gao, Xinbo, Chen, Yanjun, Hu, Ye, Jia, Ye, Qi, Ye, Li, Yenda, Zhang, Yilin, Zhang, Ying, Adi, Yossi, Nam, Youngjin, Yu, Wang, Hao, Yuchen, Qian, Yundi, He, Yuzi, Rait, Zach, DeVito, Zachary, Rosnbrick, Zef, Wen, Zhaoduo, Yang, Zhenyu, and Zhao, Zhiwei
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Computer Science - Artificial Intelligence ,Computer Science - Computation and Language ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3, including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety. The paper also presents the results of experiments in which we integrate image, video, and speech capabilities into Llama 3 via a compositional approach. We observe this approach performs competitively with the state-of-the-art on image, video, and speech recognition tasks. The resulting models are not yet being broadly released as they are still under development.
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- 2024
21. Accurate, Precise, and Physically Self-consistent Ages and Metallicities for 400,000 Solar Neighborhood Subgiant Branch Stars
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Nataf, David M., Schlaufman, Kevin C., Reggiani, Henrique, and Hahn, Isabel
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Astrophysics - Solar and Stellar Astrophysics ,Astrophysics - Astrophysics of Galaxies - Abstract
Age is the most difficult fundamental stellar parameter to infer for isolated stars. While isochrone-based ages are in general imprecise for both main sequence dwarfs and red giants, precise isochrone-based ages can be obtained for stars on the subgiant branch transitioning from core to shell hydrogen burning. We synthesize Gaia DR3-based distance inferences, multiwavelength photometry from the ultraviolet to the mid infrared, and three-dimensional extinction maps to construct a sample of 289,759 solar-metallicity stars amenable to accurate, precise, and physically self-consistent age inferences. Using subgiants in the solar-metallicity open clusters NGC 2682 (i.e., M 67) and NGC 188, we show that our approach yields accurate and physically self-consistent ages and metallicities with median statistical precisions of 8\% and 0.06 dex. The inclusion of systematic uncertainties resulting from non-single or variable stars results in age and metallicity precisions of 9\% and 0.12 dex. We supplement this solar-metallicity sample with an additional 112,062 metal-poor subgiants, including over 3,000 stars with $[\text{Fe/H}]\lesssim-1.50$, 7\% age precisions, and apparent Gaia $G$-band magnitudes $G<14$. We further demonstrate that our inferred metallicities agree with those produced by multiplexed spectroscopic surveys. As an example of the scientific potential of this catalog, we show that the solar neighborhood star-formation history has three components at $([\text{Fe/H}],\tau/\text{Gyr}) \approx (+0.0,4)$, $(+0.2,7)$, and a roughly linear sequence in age--metallicity space beginning at $([\text{Fe/H}],\tau/\text{Gyr})\approx(+0.2,7)$ and extending to $(-0.5,13)$. Our analyses indicate that the solar neighborhood includes stars on disk-like orbits even at the oldest ages and lowest metallicities accessible by our samples., Comment: 31 pages, 13 figures, accepted for publication in the AAS Journals. Our input data tables, output tables of derived parameters, and an animation of the derived relationship between the dynamics and the star-formation history of solar neighbourhood subgiants, are available at: https://github.com/DavidMoiseNataf/Subgiants/
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- 2024
22. TCAD Simulations of Radiation Damage in 4H-SiC
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Burin, Jürgen, Hahn, Christopher, Gaggl, Philipp, Gsponer, Andreas, Waid, Simon, and Bergauer, Thomas
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Physics - Instrumentation and Detectors - Abstract
To increase the scientific output of particle physics experiments, upgrades are underway at all major accelerator facilities to significantly improve the luminosity. Consequently, the solid-state detectors used in the experiments will exhibit more severe radiation-induced damage. To ensure sufficiently long sensor lifetimes, alternative materials to the established silicon sensors, with improved resilience to radiation, are investigated. For one of the promising candidate materials, silicon carbide, only recently a model describing the radiation damage in technology aided computer design (TCAD) simulations has been proposed. In this paper we present our latest achievements towards modeling radiation damage of 4H-SiC in TCAD tools. We first verify the utilized TCAD framework against published silicon data and then use it to approximate measurements of neutron-irradiated 4H-SiC particle detectors. We are able to confirm in simulations the measurement results, i.e., an almost flat capacitance as a function of bias voltage and a decreasing forward current with increasing particle fluence. Based on our simulations we are able to explain the latter by trapped charge carriers that create a space charge region within the device., Comment: 4 pages, 4 figures
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- 2024
23. Modified BART for Learning Heterogeneous Effects in Regression Discontinuity Designs
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Alcantara, Rafael, Wang, Meijia, Hahn, P. Richard, and Lopes, Hedibert
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Statistics - Methodology - Abstract
This paper introduces BART-RDD, a sum-of-trees regression model built around a novel regression tree prior, which incorporates the special covariate structure of regression discontinuity designs. Specifically, the tree splitting process is constrained to ensure overlap within a narrow band surrounding the running variable cutoff value, where the treatment effect is identified. It is shown that unmodified BART-based models estimate RDD treatment effects poorly, while our modified model accurately recovers treatment effects at the cutoff. Specifically, BART-RDD is perhaps the first RDD method that effectively learns conditional average treatment effects. The new method is investigated in thorough simulation studies as well as an empirical application looking at the effect of academic probation on student performance in subsequent terms (Lindo et al., 2010).
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- 2024
24. Supernova Pointing Capabilities of DUNE
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DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Aimard, B., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Alves, T., Amar, H., Amedo, P., Anderson, J., Andrade, D. A., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barenboim, G., Alzás, P. Barham, Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernal, J., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Bogenschuetz, J., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bracinik, J., Braga, D., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calin, M., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chakraborty, S., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chiapponi, F., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collazo, J., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Curciarello, F., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., Dallaway, W., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., Sanchez, P. Del Amo, De la Torre, A., De Lauretis, G., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., De Matteis, G., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Diaz, A., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farrell, S., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferry, G., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gaba, R., Gabrielli, A., Gago, A. M, Galizzi, F., Gallagher, H., Gallas, A., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Gazzana, S., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, L., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerard, E., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Habig, A., Hadavand, H., Haegel, L., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hakenmüller, J., Hamernik, T., Hamilton, P., Hancock, J., Happacher, F., Harris, D. A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C., Hatcher, R., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Henry, S., Morquecho, M. A. Hernandez, Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horiuchi, S., Horton-Smith, G. A., Hostert, M., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Ibrahim, M., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Jentz, I., Ji, X., Jiang, C., Jiang, J., Jiang, L., Jipa, A., Joaquim, F. 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- Subjects
High Energy Physics - Experiment ,Astrophysics - High Energy Astrophysical Phenomena ,Astrophysics - Instrumentation and Methods for Astrophysics ,Astrophysics - Solar and Stellar Astrophysics ,Nuclear Experiment ,Physics - Instrumentation and Detectors - Abstract
The determination of the direction of a stellar core collapse via its neutrino emission is crucial for the identification of the progenitor for a multimessenger follow-up. A highly effective method of reconstructing supernova directions within the Deep Underground Neutrino Experiment (DUNE) is introduced. The supernova neutrino pointing resolution is studied by simulating and reconstructing electron-neutrino charged-current absorption on $^{40}$Ar and elastic scattering of neutrinos on electrons. Procedures to reconstruct individual interactions, including a newly developed technique called ``brems flipping'', as well as the burst direction from an ensemble of interactions are described. Performance of the burst direction reconstruction is evaluated for supernovae happening at a distance of 10 kpc for a specific supernova burst flux model. The pointing resolution is found to be 3.4 degrees at 68% coverage for a perfect interaction-channel classification and a fiducial mass of 40 kton, and 6.6 degrees for a 10 kton fiducial mass respectively. Assuming a 4% rate of charged-current interactions being misidentified as elastic scattering, DUNE's burst pointing resolution is found to be 4.3 degrees (8.7 degrees) at 68% coverage., Comment: 25 pages, 16 figures
- Published
- 2024
25. Centrality dependence of L\'evy-stable two-pion Bose-Einstein correlations in $\sqrt{s_{_{NN}}}=200$ GeV Au$+$Au collisions
- Author
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PHENIX Collaboration, Abdulameer, N. J., Acharya, U., Adare, A., Aidala, C., Ajitanand, N. N., Akiba, Y., Akimoto, R., Al-Ta'ani, H., Alexander, J., Angerami, A., Aoki, K., Apadula, N., Aramaki, Y., Asano, H., Aschenauer, E. C., Atomssa, E. T., Awes, T. C., Azmoun, B., Babintsev, V., Bai, M., Bannier, B., Barish, K. N., Bassalleck, B., Bathe, S., Baublis, V., Baumgart, S., Bazilevsky, A., Belmont, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Blankenship, B., Blau, D. S., Bok, J. S., Borisov, V., Boyle, K., Brooks, M. L., Buesching, H., Bumazhnov, V., Butsyk, S., Campbell, S., Castera, P., Chen, C. -H., Chen, D., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Choi, S., Choudhury, R. K., Christiansen, P., Chujo, T., Chvala, O., Cianciolo, V., Citron, Z., Cole, B. A., Connors, M., Corliss, R., Csanád, M., Csörgő, T., D'Orazio, L., Dairaku, S., Datta, A., Daugherity, M. S., David, G., Denisov, A., Deshpande, A., Desmond, E. J., Dharmawardane, K. V., Dietzsch, O., Ding, L., Dion, A., Donadelli, M., Doomra, V., Drapier, O., Drees, A., Drees, K. A., Durham, J. M., Durum, A., Edwards, S., Efremenko, Y. V., Engelmore, T., Enokizono, A., Esha, R., Eyser, K. O., Fadem, B., Fields, D. E., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fleuret, F., Fokin, S. L., Frantz, J. E., Franz, A., Frawley, A. D., Fukao, Y., Fusayasu, T., Gainey, K., Gal, C., Garishvili, A., Garishvili, I., Glenn, A., Gong, X., Gonin, M., Goto, Y., de Cassagnac, R. Granier, Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gunji, T., Guo, L., Guo, T., Gustafsson, H. -Å., Hachiya, T., Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hanks, J., Hashimoto, K., Haslum, E., Hayano, R., Hemmick, T. K., Hester, T., He, X., Hill, J. C., Hodges, A., Hollis, R. S., Homma, K., Hong, B., Horaguchi, T., Hori, Y., Ichihara, T., Iinuma, H., Ikeda, Y., Imrek, J., Inaba, M., Iordanova, A., Isenhower, D., Issah, M., Ivanishchev, D., Jacak, B. V., Javani, M., Jiang, X., Ji, Z., Johnson, B. M., Joo, K. S., Jouan, D., Jumper, D. S., Kamin, J., Kaneti, S., Kang, B. H., Kang, J. H., Kang, J. S., Kapustinsky, J., Karatsu, K., Kasai, M., Kasza, G., Kawall, D., Kazantsev, A. V., Kempel, T., Khanzadeev, A., Kijima, K. M., Kim, B. I., Kim, C., Kim, D. J., Kim, E. -J., Kim, H. J., Kim, K. -B., Kim, Y. -J., Kim, Y. K., Kinney, E., Kiss, Á., Kistenev, E., Klatsky, J., Kleinjan, D., Kline, P., Komatsu, Y., Komkov, B., Koster, J., Kotchetkov, D., Kotov, D., Kovacs, L., Krizek, F., Král, A., Kunde, G. J., Kurgyis, B., Kurita, K., Kurosawa, M., Kwon, Y., Kyle, G. S., Lai, Y. S., Lajoie, J. G., Lebedev, A., Lee, B., Lee, D. M., Lee, J., Lee, K. B., Lee, K. S., Lee, S. H., Lee, S. R., Leitch, M. J., Leite, M. A. L., Leitgab, M., Lewis, B., Lim, S. H., Levy, L. A. Linden, Liu, M. X., Lökös, S., Loomis, D. A., Love, B., Maguire, C. F., Makdisi, Y. I., Makek, M., Manion, A., Manko, V. I., Mannel, E., Masumoto, S., McCumber, M., McGaughey, P. L., McGlinchey, D., McKinney, C., Mendoza, M., Meredith, B., Miake, Y., Mibe, T., Mignerey, A. C., Milov, A., Mishra, D. K., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Miyachi, Y., Miyasaka, S., Mohanty, A. K., Mohapatra, S., Moon, H. J., Morrison, D. P., Motschwiller, S., Moukhanova, T. V., Mulilo, B., Murakami, T., Murata, J., Mwai, A., Nagae, T., Nagamiya, S., Nagle, J. L., Nagy, M. I., Nakagawa, I., Nakamiya, Y., Nakamura, K. R., Nakamura, T., Nakano, K., Nattrass, C., Nederlof, A., Nihashi, M., Nouicer, R., Novák, T., Novitzky, N., Nukazuka, G., Nyanin, A. S., O'Brien, E., Ogilvie, C. A., Okada, K., Orosz, M., Oskarsson, A., Ouchida, M., Ozawa, K., Pak, R., Pantuev, V., Papavassiliou, V., Park, B. H., Park, I. H., Park, J. S., Park, S., Park, S. K., Patel, L., Pate, S. F., Pei, H., Peng, J. -C., Pereira, H., Peressounko, D. Yu., Petti, R., Pinkenburg, C., Pisani, R. P., Potekhin, M., Proissl, M., Purschke, M. L., Qu, H., Rak, J., Ravinovich, I., Read, K. F., Reynolds, D., Riabov, V., Riabov, Y., Richardson, E., Richford, D., Roach, D., Roche, G., Rolnick, S. D., Rosati, M., Sahlmueller, B., Saito, N., Sakaguchi, T., Samsonov, V., Sano, M., Sarsour, M., Sawada, S., Sedgwick, K., Seidl, R., Sen, A., Seto, R., Sharma, D., Shein, I., Shibata, T. -A., Shigaki, K., Shimomura, M., Shoji, K., Shukla, P., Sickles, A., Silva, C. L., Silvermyr, D., Sim, K. S., Singh, B. K., Singh, C. P., Singh, V., Slunečka, M., Smith, K. L., Soltz, R. A., Sondheim, W. E., Sorensen, S. P., Sourikova, I. V., Stankus, P. W., Stenlund, E., Stepanov, M., Ster, A., Stoll, S. P., Sugitate, T., Sukhanov, A., Sun, J., Sun, Z., Sziklai, J., Takagui, E. M., Takahara, A., Taketani, A., Tanaka, Y., Taneja, S., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Taranenko, A., Tennant, E., Themann, H., Todoroki, T., Tomášek, L., Tomášek, M., Torii, H., Towell, R. S., Tserruya, I., Tsuchimoto, Y., Tsuji, T., Ujvari, B., Vale, C., van Hecke, H. W., Vargyas, M., Vazquez-Zambrano, E., Veicht, A., Velkovska, J., Virius, M., Vossen, A., Vrba, V., Vznuzdaev, E., Vértesi, R., Wang, X. R., Watanabe, D., Watanabe, K., Watanabe, Y., Watanabe, Y. S., Wei, F., Wei, R., White, S. N., Winter, D., Wolin, S., Woody, C. L., Wysocki, M., Xia, B., Yamaguchi, Y. L., Yang, R., Yanovich, A., Ying, J., Yokkaichi, S., Younus, I., You, Z., Yushmanov, I. E., Zajc, W. A., and Zelenski, A.
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Nuclear Experiment - Abstract
The PHENIX experiment measured the centrality dependence of two-pion Bose-Einstein correlation functions in $\sqrt{s_{_{NN}}}=200$~GeV Au$+$Au collisions at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The data are well represented by L\'evy-stable source distributions. The extracted source parameters are the correlation-strength parameter $\lambda$, the L\'evy index of stability $\alpha$, and the L\'evy-scale parameter $R$ as a function of transverse mass $m_T$ and centrality. The $\lambda(m_T)$ parameter is constant at larger values of $m_T$, but decreases as $m_T$ decreases. The L\'evy scale parameter $R(m_T)$ decreases with $m_T$ and exhibits proportionality to the length scale of the nuclear overlap region. The L\'evy exponent $\alpha(m_T)$ is independent of $m_T$ within uncertainties in each investigated centrality bin, but shows a clear centrality dependence. At all centralities, the L\'evy exponent $\alpha$ is significantly different from that of Gaussian ($\alpha=2$) or Cauchy ($\alpha=1$) source distributions. Comparisons to the predictions of Monte-Carlo simulations of resonance-decay chains show that in all but the most peripheral centrality class (50%-60%), the obtained results are inconsistent with the measurements, unless a significant reduction of the in-medium mass of the $\eta'$ meson is included. In each centrality class, the best value of the in-medium $\eta'$ mass is compared to the mass of the $\eta$ meson, as well as to several theoretical predictions that consider restoration of $U_A(1)$ symmetry in hot hadronic matter., Comment: 401 authors from 75 institutions, 20 pages, 15 figures, 2 tables. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html
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- 2024
26. The flux of ultra-high-energy cosmic rays along the supergalactic plane measured at the Pierre Auger Observatory
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The Pierre Auger Collaboration, Halim, A. Abdul, Abreu, P., Aglietta, M., Allekotte, I., Cheminant, K. Almeida, Almela, A., Aloisio, R., Alvarez-Muñiz, J., Yebra, J. Ammerman, Anastasi, G. A., Anchordoqui, L., Andrada, B., Dourado, L. Andrade, Andringa, S., Apollonio, L., Aramo, C., Ferreira, P. R. Araújo, Arnone, E., Velázquez, J. C. Arteaga, Assis, P., Avila, G., Avocone, E., Bakalova, A., Barbato, F., Mocellin, A. Bartz, Bellido, J. A., Berat, C., Bertaina, M. E., Bhatta, G., Bianciotto, M., Biermann, P. L., Binet, V., Bismark, K., Bister, T., Biteau, J., Blazek, J., Bleve, C., Blümer, J., Boháčová, M., Boncioli, D., Bonifazi, C., Arbeletche, L. Bonneau, Borodai, N., Brack, J., Orchera, P. G. Brichetto, Briechle, F. L., Bueno, A., Buitink, S., Buscemi, M., Büsken, M., Bwembya, A., Caballero-Mora, K. S., Cabana-Freire, S., Caccianiga, L., Campuzano, F., Caruso, R., Castellina, A., Catalani, F., Cataldi, G., Cazon, L., Cerda, M., Čermáková, B., Cermenati, A., Chinellato, J. A., Chudoba, J., Chytka, L., Clay, R. W., Cerutti, A. C. Cobos, Colalillo, R., Coluccia, M. R., Conceição, R., Condorelli, A., Consolati, G., Conte, M., Convenga, F., Santos, D. Correia dos, Costa, P. J., Covault, C. E., Cristinziani, M., Sanchez, C. S. Cruz, Dasso, S., Daumiller, K., Dawson, B. R., de Almeida, R. M., de Errico, B., de Jesús, J., de Jong, S. J., Neto, J. R. T. de Mello, De Mitri, I., de Oliveira, J., Franco, D. de Oliveira, de Palma, F., de Souza, V., De Vito, E., Del Popolo, A., Deligny, O., Denner, N., Deval, L., di Matteo, A., Dobre, M., Dobrigkeit, C., D'Olivo, J. C., Mendes, L. M. Domingues, Dorosti, Q., Anjos, J. C. dos, Anjos, R. C. dos, Ebr, J., Ellwanger, F., Emam, M., Engel, R., Epicoco, I., Erdmann, M., Etchegoyen, A., Evoli, C., Falcke, H., Farrar, G., Fauth, A. C., Fehler, T., Feldbusch, F., Fenu, F., Fernandes, A., Fick, B., Figueira, J. M., Filip, P., Filipčič, A., Fitoussi, T., Flaggs, B., Fodran, T., Fujii, T., Fuster, A., Galea, C., García, B., Gaudu, C., Gherghel-Lascu, A., Ghia, P. L., Giaccari, U., Glombitza, J., Gobbi, F., Gollan, F., Golup, G., Berisso, M. Gómez, Vitale, P. F. Gómez, Gongora, J. P., González, J. M., González, N., Góra, D., Gorgi, A., Gottowik, M., Guarino, F., Guedes, G. P., Guido, E., Gülzow, L., Hahn, S., Hamal, P., Hampel, M. R., Hansen, P., Harari, D., Harvey, V. M., Haungs, A., Hebbeker, T., Hojvat, C., Hörandel, J. R., Horvath, P., Hrabovský, M., Huege, T., Insolia, A., Isar, P. G., Janecek, P., Jilek, V., Johnsen, J. A., Jurysek, J., Kampert, K. -H., Keilhauer, B., Khakurdikar, A., Covilakam, V. V. Kizakke, Klages, H. O., Kleifges, M., Knapp, F., Köhler, J., Krieger, F., Kunka, N., Lago, B. L., Langner, N., de Oliveira, M. A. Leigui, Lema-Capeans, Y., Letessier-Selvon, A., Lhenry-Yvon, I., Lopes, L., Lu, L., Luce, Q., Lundquist, J. P., Payeras, A. Machado, Majercakova, M., Mandat, D., Manning, B. C., Mantsch, P., Mariani, F. M., Mariazzi, A. G., Mariş, I. C., Marsella, G., Martello, D., Martinelli, S., Bravo, O. Martínez, Martins, M. A., Mathes, H. -J., Matthews, J., Matthiae, G., Mayotte, E., Mayotte, S., Mazur, P. O., Medina-Tanco, G., Meinert, J., Melo, D., Menshikov, A., Merx, C., Michal, S., Micheletti, M. I., Miramonti, L., Mollerach, S., Montanet, F., Morejon, L., Mulrey, K., Mussa, R., Namasaka, W. M., Negi, S., Nellen, L., Nguyen, K., Nicora, G., Niechciol, M., Nitz, D., Nosek, D., Novotny, V., Nožka, L., Nucita, A., Núñez, L. A., Oliveira, C., Palatka, M., Pallotta, J., Panja, S., Parente, G., Paulsen, T., Pawlowsky, J., Pech, M., Pękala, J., Pelayo, R., Pelgrims, V., Pereira, L. A. S., Martins, E. E. Pereira, Bertolli, C. Pérez, Perrone, L., Petrera, S., Petrucci, C., Pierog, T., Pimenta, M., Platino, M., Pont, B., Pothast, M., Shahvar, M. Pourmohammad, Privitera, P., Prouza, M., Querchfeld, S., Rautenberg, J., Ravignani, D., Akim, J. V. Reginatto, Reininghaus, M., Reuzki, A., Ridky, J., Riehn, F., Risse, M., Rizi, V., de Carvalho, W. Rodrigues, Rodriguez, E., Rojo, J. Rodriguez, Roncoroni, M. J., Rossoni, S., Roth, M., Roulet, E., Rovero, A. C., Saftoiu, A., Saharan, M., Salamida, F., Salazar, H., Salina, G., Gomez, J. D. Sanabria, Sánchez, F., Santos, E. M., Santos, E., Sarazin, F., Sarmento, R., Sato, R., Savina, P., Schäfer, C. M., Scherini, V., Schieler, H., Schimassek, M., Schimp, M., Schmidt, D., Scholten, O., Schoorlemmer, H., Schovánek, P., Schröder, F. G., Schulte, J., Schulz, T., Sciutto, S. J., Scornavacche, M., Sedoski, A., Segreto, A., Sehgal, S., Shivashankara, S. U., Sigl, G., Simkova, K., Simon, F., Smau, R., Šmída, R., Sommers, P., Squartini, R., Stadelmaier, M., Stanič, S., Stasielak, J., Stassi, P., Strähnz, S., Straub, M., Suomijärvi, T., Supanitsky, A. D., Svozilikova, Z., Szadkowski, Z., Tairli, F., Tapia, A., Taricco, C., Timmermans, C., Tkachenko, O., Tobiska, P., Peixoto, C. J. Todero, Tomé, B., Torrès, Z., Travaini, A., Travnicek, P., Tueros, M., Unger, M., Uzeiroska, R., Vaclavek, L., Vacula, M., Galicia, J. F. Valdés, Valore, L., Varela, E., Vašíčková, V., Vásquez-Ramírez, A., Veberič, D., Quispe, I. D. Vergara, Verzi, V., Vicha, J., Vink, J., Vorobiov, S., Watanabe, C., Watson, A. A., Weindl, A., Wiencke, L., Wilczyński, H., Wittkowski, D., Wundheiler, B., Yue, B., Yushkov, A., Zapparrata, O., Zas, E., Zavrtanik, D., and Zavrtanik, M.
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Astrophysics - High Energy Astrophysical Phenomena - Abstract
Ultra-high-energy cosmic rays are known to be mainly of extragalactic origin, and their propagation is limited by energy losses, so their arrival directions are expected to correlate with the large-scale structure of the local Universe. In this work, we investigate the possible presence of intermediate-scale excesses in the flux of the most energetic cosmic rays from the direction of the supergalactic plane region using events with energies above 20 EeV recorded with the surface detector array of the Pierre Auger Observatory up to 31 December 2022, with a total exposure of 135,000 km^2 sr yr. The strongest indication for an excess that we find, with a post-trial significance of 3.1{\sigma}, is in the Centaurus region, as in our previous reports, and it extends down to lower energies than previously studied. We do not find any strong hints of excesses from any other region of the supergalactic plane at the same angular scale. In particular, our results do not confirm the reports by the Telescope Array collaboration of excesses from two regions in the Northern Hemisphere at the edge of the field of view of the Pierre Auger Observatory. With a comparable exposure, our results in those regions are in good agreement with the expectations from an isotropic distribution., Comment: submitted to ApJ
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- 2024
27. Integrating AI in College Education: Positive yet Mixed Experiences with ChatGPT
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Song, Xinrui, Zhang, Jiajin, Yan, Pingkun, Hahn, Juergen, Kruger, Uwe, Mohamed, Hisham, and Wang, Ge
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Computer Science - Artificial Intelligence ,Computer Science - Human-Computer Interaction - Abstract
The integration of artificial intelligence (AI) chatbots into higher education marks a shift towards a new generation of pedagogical tools, mirroring the arrival of milestones like the internet. With the launch of ChatGPT-4 Turbo in November 2023, we developed a ChatGPT-based teaching application (https://chat.openai.com/g/g-1imx1py4K-chatge-medical-imaging) and integrated it into our undergraduate medical imaging course in the Spring 2024 semester. This study investigates the use of ChatGPT throughout a semester-long trial, providing insights into students' engagement, perception, and the overall educational effectiveness of the technology. We systematically collected and analyzed data concerning students' interaction with ChatGPT, focusing on their attitudes, concerns, and usage patterns. The findings indicate that ChatGPT offers significant advantages such as improved information access and increased interactivity, but its adoption is accompanied by concerns about the accuracy of the information provided and the necessity for well-defined guidelines to optimize its use.
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- 2024
28. Spectroscopy of deeply bound orbitals in neutron-rich Ca isotopes
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Li, P. J., Lee, J., Doornenbal, P., Chen, S., Wang, S., Obertelli, A., Chazono, Y., Holt, J. D., Hu, B. S., Ogata, K., Utsuno, Y., Yoshida, K., Achouri, N. L., Baba, H., Browne, F., Calvet, D., Château, F., Chiga, N., Corsi, A., Cortés, M. L., Delbart, A., Gheller, J-M., Giganon, A., Gillibert, A., Hilaire, C., Isobe, T., Kobayashi, T., Kubota, Y., Lapoux, V., Liu, H. N., Motobayashi, T., Murray, I., Otsu, H., Panin, V., Paul, N., Rodriguez, W., Sakurai, H., Sasano, M., Steppenbeck, D., Stuhl, L., Sun, Y. L., Togano, Y., Uesaka, T., Wimmer, K., Yoneda, K., Aktas, O., Aumann, T., Boretzky, K., Caesar, C., Chung, L. X., Flavigny, F., Franchoo, S., Gasparic, I., Gerst, R. -B., Gibelin, J., Hahn, K. I., Kahlbow, J., Kim, D., Koiwai, T., Kondo, Y., Körper, D., Koseoglou, P., Lehr, C., Linh, B. D., Lokotko, T., MacCormick, M., Miki, K., Moschner, K., Nakamura, T., Park, S. Y., Rossi, D., Sahin, E., Schindler, F., Simon, H., Söderström, P-A., Sohler, D., Takeuchi, S., Toernqvist, H., Tscheuschner, J., Vaquero, V., Wagner, V., Werner, V., Xu, X., Yamada, H., Yan, D., Yang, Z., Yasuda, M., and Zanetti, L.
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Nuclear Experiment ,Nuclear Theory - Abstract
The calcium isotopes are an ideal system to investigate the evolution of shell structure and magic numbers. Although the properties of surface nucleons in calcium have been well studied, probing the structure of deeply bound nucleons remains a challenge. Here, we report on the first measurement of unbound states in $^{53}$Ca and $^{55}$Ca, populated from \ts{54,56}Ca($p,pn$) reactions at a beam energy of around 216 MeV/nucleon at the RIKEN Radioactive Isotopes Beam Factory. The resonance properties, partial cross sections, and momentum distributions of these unbound states were analyzed. Orbital angular momentum $l$ assignments were extracted from momentum distributions based on calculations using the distorted wave impulse approximation (DWIA) reaction model. The resonances at excitation energies of 5516(41)\,keV in $^{53}$Ca and 6000(250)\,keV in $^{55}$Ca indicate a significant $l$\, =\,3 component, providing the first experimental evidence for the $\nu 0f_{7/2}$ single-particle strength of unbound hole states in the neutron-rich Ca isotopes. The observed excitation energies and cross-sections point towards extremely localized and well separated strength distributions, with some fragmentation for the $\nu 0f_{7/2}$ orbital in $^{55}$Ca. These results are in good agreement with predictions from shell-model calculations using the effective GXPF1Bs interaction and \textit{ab initio} calculations and diverge markedly from the experimental distributions in the nickel isotones at $Z=28$., Comment: 13 pages, 7 figures
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- 2024
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29. Quantum Electrodynamics in Strong Electromagnetic Fields: Substate Resolved K$\alpha$ Transition Energies in Helium-like Uranium
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Pfäfflein, Philip, Weber, Günter, Allgeier, Steffen, Andelkovic, Zoran, Bernitt, Sonja, Bondarev, Andrey I., Borovik, Alexander, Duval, Louis, Fleischmann, Andreas, Forstner, Oliver, Friedrich, Marvin, Glorius, Jan, Gumberidze, Alexandre, Hahn, Christoph, Hengstler, Daniel, Herdrich, Marc Oliver, Herfurth, Frank, Hillenbrand, Pierre-Michel, Kalinin, Anton, Kiffer, Markus, Kröger, Felix Martin, Kubullek, Maximilian, Kuntz, Patricia, Lestinsky, Michael, Litvinov, Yuri A., Löher, Bastian, Menz, Esther Babette, Over, Tobias, Petridis, Nikolaos, Ringleb, Stefan, Sighu, Ragandeep Singh, Spillmann, Uwe, Trotsenko, Sergiy, Warczak, Andrzej, Zhu, Binghui, Enss, Christian, and Stöhlker, Thomas
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Physics - Atomic Physics - Abstract
Using novel metallic magnetic calorimeter detectors at the CRYRING@ESR, we recorded X-ray spectra of stored and electron cooled helium-like uranium (U$^{90+}$) with an unmatched spectral resolution of close to 90 eV. This allowed for an accurate determination of the energies of all four components of the K$\alpha$ transitions in U$^{90+}$. We find good agreement with state-of-the-art bound-state QED calculations for the strong-field regime. Our results do not support any systematic deviation between experiment and theory in helium-like systems, the presence of which was subject of intense debates in recent years.
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- 2024
30. Universal piecewise polynomiality for counting curves in toric surfaces
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Hahn, Marvin Anas and Reda, Vincenzo
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Mathematics - Algebraic Geometry ,Mathematics - Combinatorics ,14N10, 14T90, 14N35 - Abstract
Inspired by piecewise polynomiality results of double Hurwitz numbers, Ardila and Brugall\'e introduced an enumerative problem which they call double Gromov--Witten invariants of Hirzebruch surfaces. These invariants serve as a two-dimensional analogue and satisfy a similar piecewise polynomial structure. More precisely, they introduced the enumeration of curves in Hirzebruch surfaces satisfying point conditions and tangency conditions on the two parallel toric boundaries. These conditions are stored in four partitions and the resulting invariants are piecewise polynomial in their entries. Moreover, they found that these expressions also behave polynomially with respect to the parameter determining the underlying Hirzebruch surfaces. Based on work of Ardila and Block, they proposed that such a polynomiality could also hold while changing between more general toric surfaces corresponding to $h$-transverse polygons. In this work, we answer this question affirmatively. Moreover, we express the resulting invariants for $h$-transverse polygons as matrix elements in the two-dimensional bosonic Fock space., Comment: 24 pages, 8 figures, 3 tables. arXiv admin note: text overlap with arXiv:1412.4563 by other authors
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- 2024
31. A detailed study of the very-high-energy Crab pulsar emission with the LST-1
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Project, CTA-LST, Abe, K., Abe, S., Abhishek, A., Acero, F., Aguasca-Cabot, A., Agudo, I., Crespo, N. Alvarez, Antonelli, L. A., Aramo, C., Arbet-Engels, A., Arcaro, C., Artero, M., Asano, K., Aubert, P., Baktash, A., Bamba, A., Larriva, A. Baquero, Baroncelli, L., de Almeida, U. Barres, Barrio, J. A., Batkovic, I., Baxter, J., González, J. Becerra, Bernardini, E., Medrano, J. Bernete, Berti, A., Bhattacharjee, P., Bigongiari, C., Bissaldi, E., Blanch, O., Bonnoli, G., Bordas, P., Brunelli, G., Bulgarelli, A., Burelli, I., Burmistrov, L., Buscemi, M., Cardillo, M., Caroff, S., Carosi, A., Carrasco, M. S., Cassol, F., Castrejón, N., Cauz, D., Cerasole, D., Ceribella, G., Chai, Y., Cheng, K., Chiavassa, A., Chikawa, M., Chon, G., Chytka, L., Cicciari, G. M., Cifuentes, A., Contreras, J. L., Cortina, J., Costantini, H., Da Vela, P., Dalchenko, M., Dazzi, F., De Angelis, A., de Lavergne, M. de Bony, De Lotto, B., de Menezes, R., Del Peral, L., Delgado, C., Mengual, J. Delgado, della Volpe, D., Dellaiera, M., Di Piano, A., Di Pierro, F., Di Tria, R., Di Venere, L., Díaz, C., Dominik, R. M., Prester, D. Dominis, Donini, A., Dorner, D., Doro, M., Eisenberger, L., Elsässer, D., Emery, G., Escudero, J., Ramazani, V. Fallah, Ferrarotto, F., Fiasson, A., Foffano, L., Coromina, L. Freixas, Fröse, S., Fukazawa, Y., López, R. Garcia, Gasbarra, C., Gasparrini, D., Gavira, L., Geyer, D., Paiva, J. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Godinovic, N., Grau, R., Green, D., Green, J., Gunji, S., Günther, P., Hackfeld, J., Hadasch, D., Hahn, A., Hassan, T., Hayashi, K., Heckmann, L., Heller, M., Llorente, J. Herrera, Hirotani, K., Hoffmann, D., Horns, D., Houles, J., Hrabovsky, M., Hrupec, D., Hui, D., Iarlori, M., Imazawa, R., Inada, T., Inome, Y., Ioka, K., Iori, M., Martinez, I. Jimenez, Quiles, J. Jiménez, Jurysek, J., Kagaya, M., Karas, V., Katagiri, H., Kataoka, J., Kerszberg, D., Kobayashi, Y., Kohri, K., Kong, A., Kubo, H., Kushida, J., Lainez, M., Lamanna, G., Lamastra, A., Lemoigne, L., Linhoff, M., Longo, F., López-Coto, R., López-Moya, M., López-Oramas, A., Loporchio, S., Lorini, A., Bahilo, J. Lozano, Luque-Escamilla, P. L., Majumdar, P., Makariev, M., Mallamaci, M., Mandat, D., Manganaro, M., Manicò, G., Mannheim, K., Marchesi, S., Mariotti, M., Marquez, P., Marsella, G., Martí, J., Martinez, O., Martínez, G., Martínez, M., Mas-Aguilar, A., Maurin, G., Mazin, D., Guillen, E. Mestre, Micanovic, S., Miceli, D., Miener, T., Miranda, J. M., Mirzoyan, R., Mizuno, T., Gonzalez, M. Molero, Molina, E., Montaruli, T., Moralejo, A., Morcuende, D., Morselli, A., Moya, V., Muraishi, H., Nagataki, S., Nakamori, T., Neronov, A., Nickel, L., Rosillo, M. Nievas, Nikolic, L., Nishijima, K., Noda, K., Nosek, D., Novotny, V., Nozaki, S., Ohishi, M., Ohtani, Y., Oka, T., Okumura, A., Orito, R., Otero-Santos, J., Ottanelli, P., Owen, E., Palatiello, M., Paneque, D., Pantaleo, F. R., Paoletti, R., Paredes, J. M., Pech, M., Pecimotika, M., Peresano, M., Pfeiffle, F., Pietropaolo, E., Pihet, M., Pirola, G., Plard, C., Podobnik, F., Pons, E., Prandini, E., Priyadarshi, C., Prouza, M., Rando, R., Rhode, W., Ribó, M., Righi, C., Rizi, V., Fernandez, G. Rodriguez, Frías, M. D. Rodríguez, Saito, T., Sakurai, S., Sanchez, D. A., Sano, H., Šarić, T., Sato, Y., Saturni, F. G., Savchenko, V., Schiavone, F., Schleicher, B., Schmuckermaier, F., Schubert, J. L., Schussler, F., Schweizer, T., Arroyo, M. Seglar, Siegert, T., Silvia, R., Sitarek, J., Sliusar, V., Strišković, J., Strzys, M., Suda, Y., Tajima, H., Takahashi, H., Takahashi, M., Takata, J., Takeishi, R., Tam, P. H. T., Tanaka, S. J., Tateishi, D., Tavernier, T., Temnikov, P., Terada, Y., Terauchi, K., Terzic, T., Teshima, M., Tluczykont, M., Tokanai, F., Torres, D. F., Travnicek, P., Truzzi, S., Tutone, A., Vacula, M., Vallania, P., van Scherpenberg, J., Acosta, M. Vázquez, Verna, G., Viale, I., Vigliano, A., Vigorito, C. F., Visentin, E., Vitale, V., Voitsekhovskyi, V., Voutsinas, G., Vovk, I., Vuillaume, T., Walter, R., Wan, L., Will, M., Yamamoto, T., Yamazaki, R., Yeung, P. K. H., Yoshida, T., Yoshikoshi, T., Zhang, W., and Zywucka, N.
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Astrophysics - High Energy Astrophysical Phenomena - Abstract
Context: There are currently three pulsars firmly detected by imaging atmospheric Cherenkov telescopes (IACTs), two of them reaching TeV energies, challenging models of very-high-energy (VHE) emission in pulsars. More precise observations are needed to better characterize pulsar emission at these energies. The LST-1 is the prototype of the Large-Sized Telescope, that will be part of the Cherenkov Telescope Array Observatory (CTAO). Its improved performance over previous IACTs makes it well suited for studying pulsars. Aims: To study the Crab pulsar emission with the LST-1, improving and complementing the results from other telescopes. These observations can also be used to characterize the potential of the LST-1 to study other pulsars and detect new ones. Methods: We analyzed a total of $\sim$103 hours of gamma-ray observations of the Crab pulsar conducted with the LST-1 in the period from September 2020 to January 2023. The observations were carried out at zenith angles less than 50 degrees. A new analysis of the Fermi-LAT data was also performed, including $\sim$14 years of observations. Results: The Crab pulsar phaseogram, long-term light-curve, and phase-resolved spectra are reconstructed with the LST-1 from 20 GeV to 450 GeV for P1 and up to 700 GeV for P2. The pulsed emission is detected with a significance of 15.2$\sigma$. The two characteristic emission peaks of the Crab pulsar are clearly detected (>10$\sigma$), as well as the so-called bridge emission (5.7$\sigma$). We find that both peaks are well described by power laws, with spectral indices of $\sim$3.44 and $\sim$3.03 respectively. The joint analysis of Fermi-LAT and LST-1 data shows a good agreement between both instruments in the overlapping energy range. The detailed results obtained in the first observations of the Crab pulsar with LST-1 show the potential that CTAO will have to study this type of sources., Comment: Accepted by A&A
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- 2024
32. Inconsistency of parsimony under the multispecies coalescent
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Rickert, Daniel, Fan, Wai-Tong Louis, and Hahn, Matthew
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Quantitative Biology - Populations and Evolution - Abstract
While it is known that parsimony can be statistically inconsistent under certain models of evolution due to high levels of homoplasy, the consistency of parsimony under the multispecies coalescent (MSC) is less well studied. Previous studies have shown the consistency of concatenated parsimony (parsimony applied to concatenated alignments) under the MSC for the rooted 4-taxa case under an infinite-sites model of mutation; on the other hand, other work has also established the inconsistency of concatenated parsimony for the unrooted 6-taxa case. These seemingly contradictory results suggest that concatenated parsimony may fail to be consistent for trees with more than 5 taxa, for all unrooted trees, or for some combination of the two. Here, we present a technique for computing the expected internal branch lengths of gene trees under the MSC. This technique allows us to determine the regions of the parameter space of the species tree under which concatenated parsimony fails for different numbers of taxa, for rooted or unrooted trees. We use our new approach to demonstrate that there are always regions of statistical inconsistency for concatenated parsimony for the 5- and 6-taxa cases, regardless of rooting. Our results therefore suggest that parsimony is not generally dependable under the MSC., Comment: 19 pages, 8 figures, 1 table (v2: resolved PDF error; removed endfloat)
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- 2024
33. Vortex confinement through an unquantized magnetic flux
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Kim, Geunyong, Yun, Jinyoung, Yang, Jinho, Yang, Ilkyu, Wulferding, Dirk, Movshovich, Roman, Cho, Gil Young, Kim, Ki-Seok, Hahn, Garam, and Kim, Jeehoon
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Condensed Matter - Superconductivity - Abstract
Geometrically confined superconductors often experience a breakdown in the quantization of magnetic flux owing to the incomplete screening of the supercurrent against the field penetration. In this study, we report that the confinement of a magnetic field occurs regardless of the dimensionality of the system, extending even to 1D linear potential systems. By utilizing a vector-field magnetic force microscope, we successfully create a vortex-antivortex pair connected by a 1D unquantized magnetic flux in ultra-thin superconducting films. Through an investigation of the manipulation and thermal behavior of the vortex pair, we uncover a long-range interaction mediated by the unquantized magnetic flux. These findings suggest a universal phenomenon of unquantized magnetic flux formation, independent of the geometry of the system. Our results present an experimental route for probing the impact of confinement on superconducting properties and order parameters in unconventional superconductors characterized by extremely low dimensionality.
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- 2024
34. An Experimental Test of the Big-Fish-Little-Pond Effect Using an Immersive Virtual Reality Classroom
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Lisa Hasenbein, Ulrich Trautwein, Jens-Uwe Hahn, Stephan Soller, and Richard Göllner
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Academic self-concept plays a central role in successful learning and is substantially shaped by social comparisons. Research on the so-called Big-Fish-Little-Pond Effect (BFLPE) has yielded a highly robust and generalizable pattern of negative effects of higher class/school average achievement on students' self-concept when controlling for individual achievement. However, most BFLPE studies have not provided information about the causes behind or the mechanisms underlying the proposed effects. To address this, we used a fully immersive virtual reality (IVR) classroom to experimentally test the extent to which students recognized performance-related classroom behavior as implicit social comparison information and how these perceptions explained differences in students' self-concepts. Participants (N = 381 sixth-grade students) experienced an authentic yet standardized IVR teaching situation with virtual classmates who exhibited different performance levels (operationalized as 20% vs. 35% vs. 65% vs. 80% of classmates raising their hands). Hand-raising behavior had a significant positive effect on students' perceptions of the class' performance level (d[subscript 20% vs. 65%] = 0.60; d[subscript 20% vs. 80%] = 1.24). In line with the BFLPE, results showed a negative effect of higher performing classmates on students' situational self-concept (d[subscript 20% vs. 80%] = 0.30). Students' perceptions of the class' performance level fully explained the effect of classmates' hand-raising behavior on students' situational self-concept. The study's experimental approach provided new insights into the emergence of social comparison effects in the classroom, highlighting the major role of students' perceptions of their classmates' performance-related behavior, and moreover demonstrated the general potential of using IVR in classroom research.
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- 2024
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35. Measuring the Conditional Luminosity and Stellar Mass Functions of Galaxies by Combining the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 Data
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Wang, Yirong, Yang, Xiaohu, Gu, Yizhou, Xu, Xiaoju, Xu, Haojie, Wang, Yuyu, Katsianis, Antonios, Han, Jiaxin, He, Min, Zheng, Yunliang, Li, Qingyang, Wang, Yaru, Hong, Wensheng, Wang, Jiaqi, Tan, Zhenlin, Zou, Hu, Lange, Johannes Ulf, Hahn, ChangHoon, Behroozi, Peter, Aguilar, Jessica Nicole, Ahlen, Steven, Brooks, David, Claybaugh, Todd, Cole, Shaun, de la Macorra, Axel, Dey, Biprateep, Doel, Peter, Forero-Romero, Jaime E, Honscheid, Klaus, Kehoe, Robert, Kisner, Theodore, Lambert, Andrew, Manera, Marc, Meisner, Aaron, Miquel, Ramon, Moustakas, John, Nie, Jundan, Poppett, Claire, Rezaie, Mehdi, Rossi, Graziano, Sanchez, Eusebio, Schubnell, Michael, Tarlé, Gregory, Weaver, Benjamin Alan, and Zhou, Zhimin
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Astronomical Sciences ,Physical Sciences ,Astronomical and Space Sciences ,Atomic ,Molecular ,Nuclear ,Particle and Plasma Physics ,Physical Chemistry (incl. Structural) ,Astronomy & Astrophysics ,Astronomical sciences ,Particle and high energy physics ,Space sciences - Abstract
In this investigation, we leverage the combination of the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 9, Survey Validation 3, and Year 1 data sets to estimate the conditional luminosity functions and conditional stellar mass functions (CLFs and CSMFs) of galaxies across various halo mass bins and redshift ranges. To support our analysis, we utilize a realistic DESI mock galaxy redshift survey (MGRS) generated from a high-resolution Jiutian simulation. An extended halo-based group finder is applied to both MGRS catalogs and DESI observation. By comparing the r- and z-band luminosity functions (LFs) and stellar mass functions (SMFs) derived using both photometric and spectroscopic data, we quantified the impact of photometric redshift (photo-z) errors on the galaxy LFs and SMFs, especially in the low-redshift bin at the low-luminosity/mass end. By conducting prior evaluations of the group finder using MGRS, we successfully obtain a set of CLF and CSMF measurements from observational data. We find that at low redshift, the faint-end slopes of CLFs and CSMFs below ∼109 h −2 L ⊙ (or h −2 M ⊙) evince a compelling concordance with the subhalo mass functions. After correcting the cosmic variance effect of our local Universe following Chen et al., the faint-end slopes of the LFs/SMFs turn out to also be in good agreement with the slope of the halo mass function.
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- 2024
36. Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm.
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Jiang, Yuchao, Luo, Cheng, Wang, Jijun, Palaniyappan, Lena, Chang, Xiao, Xiang, Shitong, Zhang, Jie, Duan, Mingjun, Huang, Huan, Gaser, Christian, Nemoto, Kiyotaka, Miura, Kenichiro, Hashimoto, Ryota, Westlye, Lars, Richard, Genevieve, Fernandez-Cabello, Sara, Parker, Nadine, Andreassen, Ole, Kircher, Tilo, Nenadić, Igor, Stein, Frederike, Thomas-Odenthal, Florian, Teutenberg, Lea, Usemann, Paula, Dannlowski, Udo, Hahn, Tim, Grotegerd, Dominik, Meinert, Susanne, Lencer, Rebekka, Tang, Yingying, Zhang, Tianhong, Li, Chunbo, Yue, Weihua, Zhang, Yuyanan, Yu, Xin, Zhou, Enpeng, Lin, Ching-Po, Tsai, Shih-Jen, Rodrigue, Amanda, Glahn, David, Pearlson, Godfrey, Blangero, John, Karuk, Andriana, Pomarol-Clotet, Edith, Salvador, Raymond, Fuentes-Claramonte, Paola, Garcia-León, María, Spalletta, Gianfranco, Piras, Fabrizio, Vecchio, Daniela, Banaj, Nerisa, Cheng, Jingliang, Liu, Zhening, Yang, Jie, Gonul, Ali, Uslu, Ozgul, Burhanoglu, Birce, Uyar Demir, Aslihan, Rootes-Murdy, Kelly, Calhoun, Vince, Sim, Kang, Green, Melissa, Quidé, Yann, Chung, Young, Kim, Woo-Sung, Sponheim, Scott, Demro, Caroline, Ramsay, Ian, Iasevoli, Felice, de Bartolomeis, Andrea, Barone, Annarita, Ciccarelli, Mariateresa, Brunetti, Arturo, Cocozza, Sirio, Pontillo, Giuseppe, Tranfa, Mario, Park, Min, Kirschner, Matthias, Georgiadis, Foivos, Kaiser, Stefan, Van Rheenen, Tamsyn, Rossell, Susan, Hughes, Matthew, Woods, William, Carruthers, Sean, Sumner, Philip, Ringin, Elysha, Spaniel, Filip, Skoch, Antonin, Tomecek, David, Homan, Philipp, Homan, Stephanie, Omlor, Wolfgang, Cecere, Giacomo, Nguyen, Dana, Preda, Adrian, Thomopoulos, Sophia, Jahanshad, Neda, Cui, Long-Biao, and Yao, Dezhong
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Humans ,Schizophrenia ,Male ,Female ,Adult ,Algorithms ,Magnetic Resonance Imaging ,Gray Matter ,Machine Learning ,Middle Aged ,Brain ,Cross-Sectional Studies ,Europe ,Neuroimaging ,Reproducibility of Results ,North America ,Hippocampus - Abstract
Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.
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- 2024
37. Brain‐age prediction: Systematic evaluation of site effects, and sample age range and size
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Yu, Yuetong, Cui, Hao‐Qi, Haas, Shalaila S, New, Faye, Sanford, Nicole, Yu, Kevin, Zhan, Denghuang, Yang, Guoyuan, Gao, Jia‐Hong, Wei, Dongtao, Qiu, Jiang, Banaj, Nerisa, Boomsma, Dorret I, Breier, Alan, Brodaty, Henry, Buckner, Randy L, Buitelaar, Jan K, Cannon, Dara M, Caseras, Xavier, Clark, Vincent P, Conrod, Patricia J, Crivello, Fabrice, Crone, Eveline A, Dannlowski, Udo, Davey, Christopher G, de Haan, Lieuwe, de Zubicaray, Greig I, Di Giorgio, Annabella, Fisch, Lukas, Fisher, Simon E, Franke, Barbara, Glahn, David C, Grotegerd, Dominik, Gruber, Oliver, Gur, Raquel E, Gur, Ruben C, Hahn, Tim, Harrison, Ben J, Hatton, Sean, Hickie, Ian B, Pol, Hilleke E Hulshoff, Jamieson, Alec J, Jernigan, Terry L, Jiang, Jiyang, Kalnin, Andrew J, Kang, Sim, Kochan, Nicole A, Kraus, Anna, Lagopoulos, Jim, Lazaro, Luisa, McDonald, Brenna C, McDonald, Colm, McMahon, Katie L, Mwangi, Benson, Piras, Fabrizio, Rodriguez‐Cruces, Raul, Royer, Jessica, Sachdev, Perminder S, Satterthwaite, Theodore D, Saykin, Andrew J, Schumann, Gunter, Sevaggi, Pierluigi, Smoller, Jordan W, Soares, Jair C, Spalletta, Gianfranco, Tamnes, Christian K, Trollor, Julian N, Ent, Dennis Van't, Vecchio, Daniela, Walter, Henrik, Wang, Yang, Weber, Bernd, Wen, Wei, Wierenga, Lara M, Williams, Steven CR, Wu, Mon‐Ju, Zunta‐Soares, Giovana B, Bernhardt, Boris, Thompson, Paul, Frangou, Sophia, Ge, Ruiyang, and Group, ENIGMA‐Lifespan Working
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Biological Psychology ,Psychology ,Aging ,Clinical Research ,Neurosciences ,Neurological ,Mental health ,Humans ,Adolescent ,Female ,Aged ,Adult ,Child ,Young Adult ,Male ,Brain ,Aged ,80 and over ,Child ,Preschool ,Middle Aged ,Magnetic Resonance Imaging ,Neuroimaging ,Sample Size ,benchmarking ,brain aging ,brainAGE ,ENIGMA‐Lifespan Working Group ,Cognitive Sciences ,Experimental Psychology ,Biological psychology ,Cognitive and computational psychology - Abstract
Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.
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- 2024
38. Trends in volumes and survival after hematopoietic cell transplantation in racial/ethnic minorities.
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Khera, Nandita, Ailawadhi, Sikander, Brazauskas, Ruta, Patel, Jinalben, Jacobs, Benjamin, Ustun, Celalettin, Ballen, Karen, Abid, Muhammad, Diaz Perez, Miguel, Al-Homsi, A, Hashem, Hasan, Hong, Sanghee, Munker, Reinhold, Schears, Raquel, Lazarus, Hillard, Ciurea, Stefan, Badawy, Sherif, Savani, Bipin, Wirk, Baldeep, LeMaistre, C, Bhatt, Neel, Beitinjaneh, Amer, Aljurf, Mahmoud, Sharma, Akshay, Cerny, Jan, Knight, Jennifer, Kelkar, Amar, Yared, Jean, Kindwall-Keller, Tamila, Winestone, Lena, Steinberg, Amir, Arnold, Staci, Seo, Sachiko, Preussler, Jaime, Hossain, Nasheed, Fingrut, Warren, Agrawal, Vaibhav, Hashmi, Shahrukh, Lehmann, Leslie, Wood, William, Rangarajan, Hemalatha, Saber, Wael, and Hahn, Theresa
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Humans ,Hematopoietic Stem Cell Transplantation ,Male ,Female ,Adult ,Middle Aged ,Ethnic and Racial Minorities ,Adolescent ,Child ,Aged ,Young Adult ,Child ,Preschool - Abstract
There has been an increase in volume as well as an improvement in overall survival (OS) after hematopoietic cell transplantation (HCT) for hematologic disorders. It is unknown if these changes have affected racial/ethnic minorities equally. In this observational study from the Center for International Blood and Marrow Transplant Research of 79 904 autologous (auto) and 65 662 allogeneic (allo) HCTs, we examined the volume and rates of change of autoHCT and alloHCT over time and trends in OS in 4 racial/ethnic groups: non-Hispanic Whites (NHWs), non-Hispanic African Americans (NHAAs), and Hispanics across 5 2-year cohorts from 2009 to 2018. Rates of change were compared using Poisson model. Adjusted and unadjusted Cox proportional hazards models examined trends in mortality in the 4 racial/ethnic groups over 5 study time periods. The rates of increase in volume were significantly higher for Hispanics and NHAAs vs NHW for both autoHCT and alloHCT. Adjusted overall mortality after autoHCT was comparable across all racial/ethnic groups. NHAA adults (hazard ratio [HR] 1.13; 95% confidence interval [CI] 1.04-1.22; P = .004) and pediatric patients (HR 1.62; 95% CI 1.3-2.03; P < .001) had a higher risk of mortality after alloHCT than NHWs. Improvement in OS over time was seen in all 4 groups after both autoHCT and alloHCT. Our study shows the rate of change for the use of autoHCT and alloHCT is higher in NHAAs and Hispanics than in NHWs. Survival after autoHCT and alloHCT improved over time; however, NHAAs have worse OS after alloHCT, which has persisted. Continued efforts are needed to mitigate disparities for patients requiring alloHCT.
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- 2024
39. Current State of Open Source Force Fields in Protein-Ligand Binding Affinity Predictions.
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Hahn, David, Gapsys, Vytautas, de Groot, Bert, Mobley, David, and Tresadern, Gary
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Ligands ,Proteins ,Molecular Dynamics Simulation ,Protein Binding ,Thermodynamics ,Drug Discovery ,Protein Conformation - Abstract
In drug discovery, the in silico prediction of binding affinity is one of the major means to prioritize compounds for synthesis. Alchemical relative binding free energy (RBFE) calculations based on molecular dynamics (MD) simulations are nowadays a popular approach for the accurate affinity ranking of compounds. MD simulations rely on empirical force field parameters, which strongly influence the accuracy of the predicted affinities. Here, we evaluate the ability of six different small-molecule force fields to predict experimental protein-ligand binding affinities in RBFE calculations on a set of 598 ligands and 22 protein targets. The public force fields OpenFF Parsley and Sage, GAFF, and CGenFF show comparable accuracy, while OPLS3e is significantly more accurate. However, a consensus approach using Sage, GAFF, and CGenFF leads to accuracy comparable to OPLS3e. While Parsley and Sage are performing comparably based on aggregated statistics across the whole dataset, there are differences in terms of outliers. Analysis of the force field reveals that improved parameters lead to significant improvement in the accuracy of affinity predictions on subsets of the dataset involving those parameters. Lower accuracy can not only be attributed to the force field parameters but is also dependent on input preparation and sampling convergence of the calculations. Especially large perturbations and nonconverged simulations lead to less accurate predictions. The input structures, Gromacs force field files, as well as the analysis Python notebooks are available on GitHub.
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- 2024
40. Alkali‐Ion‐Assisted Activation of ε‐VOPO4 as a Cathode Material for Mg‐Ion Batteries
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Sari, Dogancan, Rutt, Ann, Kim, Jiyoon, Chen, Qian, Hahn, Nathan T, Kim, Haegyeom, Persson, Kristin A, and Ceder, Gerbrand
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Engineering ,Materials Engineering ,Chemical Sciences ,Physical Chemistry ,Affordable and Clean Energy ,cathodes ,diffusion ,energy storage ,magnesium batteries ,multivalent batteries - Abstract
Rechargeable multivalent-ion batteries are attractive alternatives to Li-ion batteries to mitigate their issues with metal resources and metal anodes. However, many challenges remain before they can be practically used due to the low solid-state mobility of multivalent ions. In this study, a promising material identified by high-throughput computational screening is investigated, ε-VOPO4, as a Mg cathode. The experimental and computational evaluation of ε-VOPO4 suggests that it may provide an energy density of >200 Wh kg-1 based on the average voltage of a complete cycle, significantly more than that of well-known Chevrel compounds. Furthermore, this study finds that Mg-ion diffusion can be enhanced by co-intercalation of Li or Na, pointing at interesting correlation dynamics of slow and fast ions.
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- 2024
41. 12C+12C Reaction Rates and the Evolution of a Massive Star
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Seong, Gwangeon, Kim, Yubin, Kwak, Kyujin, Ahn, Sunghoon, Park, Chaeyeon, Hahn, Kevin Insik, and Kim, Chunglee
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Astrophysics - Solar and Stellar Astrophysics - Abstract
Carbon fusion is important to understand the late stages in the evolution of a massive star. Astronomically interesting energy ranges for the 12C+12C reactions have been, however, poorly constrained by experiments. Theoretical studies on stellar evolution have relied on reaction rates that are extrapolated from those measured in higher energies. In this work, we update the carbon fusion reaction rates by fitting the astrophysical S-factor data obtained from direct measurements based on the Fowler, Caughlan, & Zimmerman (1975) formula. We examine the evolution of a 20 M_sun star with the updated 12C+12C reaction rates performing simulations with the MESA (Modules for Experiments for Stellar Astrophysics) code. Between 0.5 and 1 GK, the updated reaction rates are 0.35 to 0.5 times less than the rates suggested by Caughlan and Fowler (1988). The updated rates result in the increase of core temperature by about 7% and of the neutrino cooling by about a factor of three. Moreover, the carbon-burning lifetime is reduced by a factor of 2.7. The updated carbon fusion reaction rates lead to some changes in the details of the stellar evolution model, their impact seems relatively minor compared to other uncertain physical factors like convection, overshooting, rotation, and mass-loss history. The astrophysical S-factor measurements in lower energies have large errors below the Coulomb barrier. More precise measurements in lower energies for the carbon burning would be useful to improve our study and to understand the evolution of a massive star., Comment: 8 pages, 6 figures
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- 2024
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- View/download PDF
42. Distinguishing Graph States by the Properties of Their Marginals
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Vandré, Lina, de Jong, Jarn, Hahn, Frederik, Burchardt, Adam, Gühne, Otfried, and Pappa, Anna
- Subjects
Quantum Physics - Abstract
Graph states are a class of multi-partite entangled quantum states that are ubiquitous in many networking applications; the study of equivalence relations between graph states under local operations aims to provide methods to relate graph states in networked settings. The problem of determining local unitary (LU) equivalence of graph states is in NP, and it remains an open question if efficient general methods are possible. We introduce a family of easy-to-compute LU-invariants based on the marginal structure of the graphs that allow to rule out equivalence of graph states. We show that these invariants can uniquely identify all LU-orbits and entanglement classes of every graph state of 8 qubits or less and discuss how reliable the methods are for more qubit graph states. We also discuss examples of entanglement classes with more nodes, where their marginal structure does not allow us to tell them apart. Additionally, we generalise tools to test local clifford (LC) equivalence of graph states that work by condensing graphs into other graphs of smaller size. We show that statements on the equivalence of the smaller graphs (which are easier to compute) can be used to infer statements on the equivalence of the original, larger graphs., Comment: 12 pages of main text + 5 pages of appendices, 10+2 figures, 3 tables
- Published
- 2024
43. Separations in the Representational Capabilities of Transformers and Recurrent Architectures
- Author
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Bhattamishra, Satwik, Hahn, Michael, Blunsom, Phil, and Kanade, Varun
- Subjects
Computer Science - Machine Learning ,Statistics - Machine Learning - Abstract
Transformer architectures have been widely adopted in foundation models. Due to their high inference costs, there is renewed interest in exploring the potential of efficient recurrent architectures (RNNs). In this paper, we analyze the differences in the representational capabilities of Transformers and RNNs across several tasks of practical relevance, including index lookup, nearest neighbor, recognizing bounded Dyck languages, and string equality. For the tasks considered, our results show separations based on the size of the model required for different architectures. For example, we show that a one-layer Transformer of logarithmic width can perform index lookup, whereas an RNN requires a hidden state of linear size. Conversely, while constant-size RNNs can recognize bounded Dyck languages, we show that one-layer Transformers require a linear size for this task. Furthermore, we show that two-layer Transformers of logarithmic size can perform decision tasks such as string equality or disjointness, whereas both one-layer Transformers and recurrent models require linear size for these tasks. We also show that a log-size two-layer Transformer can implement the nearest neighbor algorithm in its forward pass; on the other hand recurrent models require linear size. Our constructions are based on the existence of $N$ nearly orthogonal vectors in $O(\log N)$ dimensional space and our lower bounds are based on reductions from communication complexity problems. We supplement our theoretical results with experiments that highlight the differences in the performance of these architectures on practical-size sequences., Comment: Preprint
- Published
- 2024
44. Jet modification via $\pi^0$-hadron correlations in Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV
- Author
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PHENIX Collaboration, Abdulameer, N. J., Acharya, U., Adare, A., Afanasiev, S., Aidala, C., Ajitanand, N. N., Akiba, Y., Al-Bataineh, H., Alexander, J., Alfred, M., Aoki, K., Apadula, N., Aphecetche, L., Asai, J., Asano, H., Atomssa, E. T., Averbeck, R., Awes, T. C., Azmoun, B., Babintsev, V., Bai, M., Baksay, G., Baksay, L., Baldisseri, A., Bandara, N. S., Bannier, B., Barish, K. N., Barnes, P. D., Bassalleck, B., Basye, A. T., Bathe, S., Batsouli, S., Baublis, V., Baumann, C., Bazilevsky, A., Beaumier, M., Beckman, S., Belikov, S., Belmont, R., Bennett, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Bickley, A. A., Blankenship, B., Blau, D. S., Boissevain, J. G., Bok, J. S., Borel, H., Borisov, V., Boyle, K., Brooks, M. L., Bryslawskyj, J., Buesching, H., Bumazhnov, V., Bunce, G., Butsyk, S., Camacho, C. M., Campbell, S., Chang, B. S., Chang, W. C., Charvet, J. L., Chen, C. -H., Chen, D., Chernichenko, S., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Choudhury, R. K., Chujo, T., Chung, P., Churyn, A., Cianciolo, V., Citron, Z., Cole, B. A., Connors, M., Constantin, P., Corliss, R., Csanád, M., Csörgő, T., d'Enterria, D., Dahms, T., Dairaku, S., Danley, T. W., Das, K., Datta, A., Daugherity, M. S., David, G., DeBlasio, K., Dehmelt, K., Denisov, A., Deshpande, A., Desmond, E. J., Dietzsch, O., Dion, A., Diss, P. B., Donadelli, M., Doomra, V., Do, J. H., Drapier, O., Drees, A., Drees, K. A., Dubey, A. K., Durham, J. M., Durum, A., Dutta, D., Dzhordzhadze, V., Efremenko, Y. V., Ellinghaus, F., En'yo, H., Engelmore, T., Enokizono, A., Esha, R., Eyser, K. O., Fadem, B., Feege, N., Fields, D. E., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fleuret, F., Fokin, S. L., Fraenkel, Z., Frantz, J. E., Franz, A., Frawley, A. D., Fujiwara, K., Fukao, Y., Fusayasu, T., Gallus, P., Gal, C., Garg, P., Garishvili, I., Ge, H., Giordano, F., Glenn, A., Gong, H., Gonin, M., Gosset, J., Goto, Y., de Cassagnac, R. Granier, Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gunji, T., Guo, T., Gustafsson, H. -Å., Hachiya, T., Henni, A. Hadj, Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hamilton, H. F., Hanks, J., Han, R., Han, S. Y., Hartouni, E. P., Haruna, K., Hasegawa, S., Haseler, T. O. S., Hashimoto, K., Haslum, E., Hayano, R., Heffner, M., Hemmick, T. K., Hester, T., He, X., Hill, J. C., Hodges, A., Hohlmann, M., Hollis, R. S., Holzmann, W., Homma, K., Hong, B., Horaguchi, T., Hornback, D., Hoshino, T., Hotvedt, N., Huang, J., Ichihara, T., Ichimiya, R., Iinuma, H., Ikeda, Y., Imai, K., Imrek, J., Inaba, M., Iordanova, A., Isenhower, D., Ishihara, M., Isobe, T., Issah, M., Isupov, A., Ivanishchev, D., Jacak, B. V., Jezghani, M., Jiang, X., Jin, J., Ji, Z., Johnson, B. M., Joo, K. S., Jouan, D., Jumper, D. S., Kajihara, F., Kametani, S., Kamihara, N., Kamin, J., Kanda, S., Kang, J. H., Kapustinsky, J., Kawall, D., Kazantsev, A. V., Kempel, T., Key, J. A., Khachatryan, V., Khanzadeev, A., Kijima, K. M., Kikuchi, J., Kimelman, B., Kim, B. I., Kim, C., Kim, D. H., Kim, D. J., Kim, E., Kim, E. -J., Kim, G. W., Kim, M., Kim, S. H., Kinney, E., Kiriluk, K., Kiss, Á., Kistenev, E., Kitamura, R., Klatsky, J., Klay, J., Klein-Boesing, C., Kleinjan, D., Kline, P., Koblesky, T., Kochenda, L., Komkov, B., Konno, M., Koster, J., Kotov, D., Kovacs, L., Kozlov, A., Kravitz, A., Král, A., Kunde, G. J., Kurgyis, B., Kurita, K., Kurosawa, M., Kweon, M. J., Kwon, Y., Kyle, G. S., Lai, Y. S., Lajoie, J. G., Layton, D., Lebedev, A., Lee, D. M., Lee, K. B., Lee, S., Lee, S. H., Lee, T., Leitch, M. J., Leite, M. A. L., Lenzi, B., Liebing, P., Lim, S. H., Litvinenko, A., Liu, H., Liu, M. X., Liška, T., Li, X., Lokos, S., Loomis, D. A., Love, B., Lynch, D., Maguire, C. F., Makdisi, Y. I., Makek, M., Malakhov, A., Malik, M. D., Manion, A., Manko, V. I., Mannel, E., Mao, Y., Masui, H., Matathias, F., Mašek, L., McCumber, M., McGaughey, P. L., McGlinchey, D., McKinney, C., Means, N., Meles, A., Mendoza, M., Meredith, B., Miake, Y., Mignerey, A. C., Mikeš, P., Miki, K., Milov, A., Mishra, D. K., Mishra, M., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Miyasaka, S., Mizuno, S., Mohanty, A. K., Montuenga, P., Moon, T., Morino, Y., Morreale, A., Morrison, D. P., Moukhanova, T. V., Mukhopadhyay, D., Mulilo, B., Murakami, T., Murata, J., Mwai, A., Nagamiya, S., Nagashima, K., Nagle, J. L., Naglis, M., Nagy, M. I., Nakagawa, I., Nakagomi, H., Nakamiya, Y., Nakamura, T., Nakano, K., Nattrass, C., Netrakanti, P. K., Newby, J., Nguyen, M., Niida, T., Nishimura, S., Nouicer, R., Novitzky, N., Novák, T., Nukazuka, G., Nyanin, A. S., O'Brien, E., Oda, S. X., Ogilvie, C. A., Okada, K., Oka, M., Onuki, Y., Koop, J. D. Orjuela, Orosz, M., Osborn, J. D., Oskarsson, A., Ouchida, M., Ozawa, K., Pak, R., Palounek, A. P. T., Pantuev, V., Papavassiliou, V., Park, J., Park, J. S., Park, S., Park, W. J., Patel, M., Pate, S. F., Pei, H., Peng, J. -C., Pereira, H., Perepelitsa, D. V., Perera, G. D. N., Peresedov, V., Peressounko, D. Yu., Perry, J., Petti, R., Pinkenburg, C., Pinson, R., Pisani, R. P., Potekhin, M., Purschke, M. L., Purwar, A. K., Qu, H., Rakotozafindrabe, A., Rak, J., Ramson, B. J., Ravinovich, I., Read, K. F., Rembeczki, S., Reygers, K., Reynolds, D., Riabov, V., Riabov, Y., Richford, D., Rinn, T., Roach, D., Roche, G., Rolnick, S. D., Rosati, M., Rosendahl, S. S. E., Rosnet, P., Rowan, Z., Rubin, J. G., Rukoyatkin, P., Ružička, P., Rykov, V. L., Sahlmueller, B., Saito, N., Sakaguchi, T., Sakai, S., Sakashita, K., Sako, H., Samsonov, V., Sarsour, M., Sato, S., Sato, T., Sawada, S., Schaefer, B., Schmoll, B. K., Sedgwick, K., Seele, J., Seidl, R., Semenov, A. Yu., Semenov, V., Sen, A., Seto, R., Sett, P., Sexton, A., Sharma, D., Shein, I., Shibata, T. -A., Shigaki, K., Shimomura, M., Shoji, K., Shukla, P., Sickles, A., Silva, C. L., Silvermyr, D., Silvestre, C., Sim, K. S., Singh, B. K., Singh, C. P., Singh, V., Slunečka, M., Smith, K. L., Snowball, M., Soldatov, A., Soltz, R. A., Sondheim, W. E., Sorensen, S. P., Sourikova, I. V., Staley, F., Stankus, P. W., Stenlund, E., Stepanov, M., Ster, A., Stoll, S. P., Sugitate, T., Suire, C., Sukhanov, A., Sumita, T., Sun, J., Sun, Z., Sziklai, J., Takagui, E. M., Taketani, A., Tanabe, R., Tanaka, Y., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Taranenko, A., Tarján, P., Themann, H., Thomas, T. L., Tieulent, R., Timilsina, A., Todoroki, T., Togawa, M., Toia, A., Tomita, Y., Tomášek, L., Tomášek, M., Torii, H., Towell, C. L., Towell, R., Towell, R. S., Tram, V-N., Tserruya, I., Tsuchimoto, Y., Ujvari, B., Vale, C., Valle, H., van Hecke, H. W., Veicht, A., Velkovska, J., Vinogradov, A. A., Virius, M., Vrba, V., Vznuzdaev, E., Vértesi, R., Wang, X. R., Watanabe, Y., Watanabe, Y. S., Wei, F., Wessels, J., White, A. S., White, S. N., Winter, D., Woody, C. L., Wysocki, M., Xia, B., Xie, W., Xue, L., Yalcin, S., Yamaguchi, Y. L., Yamaura, K., Yang, R., Yanovich, A., Ying, J., Yokkaichi, S., Yoon, I., Yoo, J. H., Young, G. R., Younus, I., Yushmanov, I. E., Yu, H., Zajc, W. A., Zaudtke, O., Zelenski, A., Zhang, C., Zhou, S., Zolin, L., and Zou, L.
- Subjects
Nuclear Experiment - Abstract
High-momentum two-particle correlations are a useful tool for studying jet-quenching effects in the quark-gluon plasma. Angular correlations between neutral-pion triggers and charged hadrons with transverse momenta in the range 4--12~GeV/$c$ and 0.5--7~GeV/$c$, respectively, have been measured by the PHENIX experiment in 2014 for Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$~GeV. Suppression is observed in the yield of high-momentum jet fragments opposite the trigger particle, which indicates jet suppression stemming from in-medium partonic energy loss, while enhancement is observed for low-momentum particles. The ratio and differences between the yield in Au$+$Au collisions and $p$$+$$p$ collisions, $I_{AA}$ and $\Delta_{AA}$, as a function of the trigger-hadron azimuthal separation, $\Delta\phi$, are measured for the first time at the Relativistic Heavy Ion Collider. These results better quantify how the yield of low-$p_T$ associated hadrons is enhanced at wide angle, which is crucial for studying energy loss as well as medium-response effects., Comment: 534 authors from 83 institutions, 12 pages, 7 figures. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html
- Published
- 2024
45. Discrete Single-Parameter Optimal Auction Design
- Author
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Giannakopoulos, Yiannis and Hahn, Johannes
- Subjects
Computer Science - Computer Science and Game Theory ,Computer Science - Discrete Mathematics - Abstract
We study the classic single-item auction setting of Myerson, but under the assumption that the buyers' values for the item are distributed over finite supports. Using strong LP duality and polyhedral theory, we rederive various key results regarding the revenue-maximizing auction, including the characterization through virtual welfare maximization and the optimality of deterministic mechanisms, as well as a novel, generic equivalence between dominant-strategy and Bayesian incentive compatibility. Inspired by this, we abstract our approach to handle more general auction settings, where the feasibility space can be given by arbitrary convex constraints, and the objective is a convex combination of revenue and social welfare. We characterize the optimal auctions of such systems as generalized virtual welfare maximizers, by making use of their KKT conditions, and we present an analogue of Myerson's payment formula for general discrete single-parameter auction settings. Additionally, we prove that total unimodularity of the feasibility space is a sufficient condition to guarantee the optimality of auctions with integral allocation rules. Finally, we demonstrate this KKT approach by applying it to a setting where bidders are interested in buying feasible flows on trees with capacity constraints, and provide a combinatorial description of the (randomized, in general) optimal auction.
- Published
- 2024
46. Search for photons above 10$^{18}$ eV by simultaneously measuring the atmospheric depth and the muon content of air showers at the Pierre Auger Observatory
- Author
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The Pierre Auger Collaboration, Halim, A. Abdul, Abreu, P., Aglietta, M., Allekotte, I., Cheminant, K. Almeida, Almela, A., Aloisio, R., Alvarez-Muñiz, J., Yebra, J. Ammerman, Anastasi, G. A., Anchordoqui, L., Andrada, B., Dourado, L. Andrade, Andringa, S., Apollonio, L., Aramo, C., Ferreira, P. R. Araújo, Arnone, E., Velázquez, J. C. Arteaga, Assis, P., Avila, G., Avocone, E., Bakalova, A., Barbato, F., Mocellin, A. Bartz, Berat, C., Bertaina, M. E., Bhatta, G., Bianciotto, M., Biermann, P. L., Binet, V., Bismark, K., Bister, T., Biteau, J., Blazek, J., Bleve, C., Blümer, J., Boháčová, M., Boncioli, D., Bonifazi, C., Arbeletche, L. Bonneau, Borodai, N., Brack, J., Orchera, P. G. Brichetto, Briechle, F. L., Bueno, A., Buitink, S., Buscemi, M., Büsken, M., Bwembya, A., Caballero-Mora, K. S., Cabana-Freire, S., Caccianiga, L., Campuzano, F., Caruso, R., Castellina, A., Catalani, F., Cataldi, G., Cazon, L., Cerda, M., Čermáková, B., Cermenati, A., Chinellato, J. A., Chudoba, J., Chytka, L., Clay, R. W., Cerutti, A. C. Cobos, Colalillo, R., Coluccia, M. R., Conceição, R., Condorelli, A., Consolati, G., Conte, M., Convenga, F., Santos, D. Correia dos, Costa, P. J., Covault, C. E., Cristinziani, M., Sanchez, C. S. Cruz, Dasso, S., Daumiller, K., Dawson, B. R., de Almeida, R. M., de Errico, B., de Jesús, J., de Jong, S. J., Neto, J. R. T. de Mello, De Mitri, I., de Oliveira, J., Franco, D. de Oliveira, de Palma, F., de Souza, V., De Vito, E., Del Popolo, A., Deligny, O., Denner, N., Deval, L., di Matteo, A., do, J. A., Dobre, M., Dobrigkeit, C., D'Olivo, J. C., Mendes, L. M. Domingues, Dorosti, Q., Anjos, J. C. dos, Anjos, R. C. dos, Ebr, J., Ellwanger, F., Emam, M., Engel, R., Epicoco, I., Erdmann, M., Etchegoyen, A., Evoli, C., Falcke, H., Farrar, G., Fauth, A. C., Fehler, T., Feldbusch, F., Fenu, F., Fernandes, A., Fick, B., Figueira, J. M., Filip, P., Filipčič, A., Fitoussi, T., Flaggs, B., Fodran, T., Fujii, T., Fuster, A., Galea, C., García, B., Gaudu, C., Gherghel-Lascu, A., Ghia, P. L., Giaccari, U., Glombitza, J., Gobbi, F., Gollan, F., Golup, G., Berisso, M. Gómez, Vitale, P. F. Gómez, Gongora, J. P., González, J. M., González, N., Góra, D., Gorgi, A., Gottowik, M., Guarino, F., Guedes, G. P., Guido, E., Gülzow, L., Hahn, S., Hamal, P., Hampel, M. R., Hansen, P., Harari, D., Harvey, V. M., Haungs, A., Hebbeker, T., Hojvat, C., Hörandel, J. R., Horvath, P., Hrabovský, M., Huege, T., Insolia, A., Isar, P. G., Janecek, P., Jilek, V., Johnsen, J. A., Jurysek, J., Kampert, K. -H., Keilhauer, B., Khakurdikar, A., Covilakam, V. V. Kizakke, Klages, H. O., Kleifges, M., Knapp, F., Köhler, J., Krieger, F., Kunka, N., Lago, B. L., Langner, N., de Oliveira, M. A. Leigui, Lema-Capeans, Y., Letessier-Selvon, A., Lhenry-Yvon, I., Lopes, L., Lu, L., Luce, Q., Lundquist, J. P., Payeras, A. Machado, Majercakova, M., Mandat, D., Manning, B. C., Mantsch, P., Mariani, F. M., Mariazzi, A. G., Mariş, I. C., Marsella, G., Martello, D., Martinelli, S., Bravo, O. Martínez, Martins, M. A., Mathes, H. -J., Matthews, J., Matthiae, G., Mayotte, E., Mayotte, S., Mazur, P. O., Medina-Tanco, G., Meinert, J., Melo, D., Menshikov, A., Merx, C., Michal, S., Micheletti, M. I., Miramonti, L., Mollerach, S., Montanet, F., Morejon, L., Mulrey, K., Mussa, R., Namasaka, W. M., Negi, S., Nellen, L., Nguyen, K., Nicora, G., Niechciol, M., Nitz, D., Nosek, D., Novotny, V., Nožka, L., Nucita, A., Núñez, L. A., Oliveira, C., Palatka, M., Pallotta, J., Panja, S., Parente, G., Paulsen, T., Pawlowsky, J., Pech, M., Pękala, J., Pelayo, R., Pelgrims, V., Pereira, L. A. S., Martins, E. E. Pereira, Bertolli, C. Pérez, Perrone, L., Petrera, S., Petrucci, C., Pierog, T., Pimenta, M., Platino, M., Pont, B., Pothast, M., Shahvar, M. Pourmohammad, Privitera, P., Prouza, M., Querchfeld, S., Rautenberg, J., Ravignani, D., Akim, J. V. Reginatto, Reininghaus, M., Reuzki, A., Ridky, J., Riehn, F., Risse, M., Rizi, V., de Carvalho, W. Rodrigues, Rodriguez, E., Rojo, J. Rodriguez, Roncoroni, M. J., Rossoni, S., Roth, M., Roulet, E., Rovero, A. C., Saftoiu, A., Saharan, M., Salamida, F., Salazar, H., Salina, G., Gomez, J. D. Sanabria, Sánchez, F., Santos, E. M., Santos, E., Sarazin, F., Sarmento, R., Sato, R., Savina, P., Schäfer, C. M., Scherini, V., Schieler, H., Schimassek, M., Schimp, M., Schmidt, D., Scholten, O., Schoorlemmer, H., Schovánek, P., Schröder, F. G., Schulte, J., Schulz, T., Sciutto, S. J., Scornavacche, M., Sedoski, A., Segreto, A., Sehgal, S., Shivashankara, S. U., Sigl, G., Simkova, K., Simon, F., Smau, R., Šmída, R., Sommers, P., Squartini, R., Stadelmaier, M., Stanič, S., Stasielak, J., Stassi, P., Strähnz, S., Straub, M., Suomijärvi, T., Supanitsky, A. D., Svozilikova, Z., Szadkowski, Z., Tairli, F., Tapia, A., Taricco, C., Timmermans, C., Tkachenko, O., Tobiska, P., Peixoto, C. J. Todero, Tomé, B., Torrès, Z., Travaini, A., Travnicek, P., Tueros, M., Unger, M., Uzeiroska, R., Vaclavek, L., Vacula, M., Galicia, J. F. Valdés, Valore, L., Varela, E., Vašíčková, V., Vásquez-Ramírez, A., Veberič, D., Quispe, I. D. Vergara, Verzi, V., Vicha, J., Vink, J., Vorobiov, S., Watanabe, C., Watson, A. A., Weindl, A., Wiencke, L., Wilczyński, H., Wittkowski, D., Wundheiler, B., Yue, B., Yushkov, A., Zapparrata, O., Zas, E., Zavrtanik, D., and Zavrtanik, M.
- Subjects
Astrophysics - High Energy Astrophysical Phenomena - Abstract
The Pierre Auger Observatory is the most sensitive instrument to detect photons with energies above $10^{17}$ eV. It measures extensive air showers generated by ultra high energy cosmic rays using a hybrid technique that exploits the combination of a fluorescence detector with a ground array of particle detectors. The signatures of a photon-induced air shower are a larger atmospheric depth of the shower maximum ($X_{max}$) and a steeper lateral distribution function, along with a lower number of muons with respect to the bulk of hadron-induced cascades. In this work, a new analysis technique in the energy interval between 1 and 30 EeV (1 EeV = $10^{18}$ eV) has been developed by combining the fluorescence detector-based measurement of $X_{max}$ with the specific features of the surface detector signal through a parameter related to the air shower muon content, derived from the universality of the air shower development. No evidence of a statistically significant signal due to photon primaries was found using data collected in about 12 years of operation. Thus, upper bounds to the integral photon flux have been set using a detailed calculation of the detector exposure, in combination with a data-driven background estimation. The derived 95% confidence level upper limits are 0.0403, 0.01113, 0.0035, 0.0023, and 0.0021 km$^{-2}$ sr$^{-1}$ yr$^{-1}$ above 1, 2, 3, 5, and 10 EeV, respectively, leading to the most stringent upper limits on the photon flux in the EeV range. Compared with past results, the upper limits were improved by about 40% for the lowest energy threshold and by a factor 3 above 3 EeV, where no candidates were found and the expected background is negligible. The presented limits can be used to probe the assumptions on chemical composition of ultra-high energy cosmic rays and allow for the constraint of the mass and lifetime phase space of super-heavy dark matter particles., Comment: 19 pages, 22 figures
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- 2024
47. Undecided State Dynamics with Stubborn Agents
- Author
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Berenbrink, Petra, Biermeier, Felix, and Hahn, Christopher
- Subjects
Computer Science - Distributed, Parallel, and Cluster Computing - Abstract
In the classical Approximate Majority problem with two opinions there are agents with Opinion 1 and with Opinion 2. The goal is to reach consensus and to agree on the majority opinion if the bias is sufficiently large. It is well known that the problem can be solved efficiently using the Undecided State Dynamics (USD) where an agent interacting with an agent of the opposite opinion becomes undecided. In this paper, we consider a variant of the USD with a preferred Opinion 1. That is, agents with Opinion 1 behave stubbornly -- they preserve their opinion with probability $p$ whenever they interact with an agent having Opinion 2. Our main result shows a phase transition around the stubbornness parameter $p \approx 1-x_1/x_2$. If $x_1 = \Theta(n)$ and $p \geq 1-x_1/x_2 + o(1)$, then all agents agree on Opinion 1 after $O(n\cdot \log n)$ interactions. On the other hand, for $p \leq 1-x_1/x_2 - o(1)$, all agents agree on Opinion 2, again after $O(n\cdot \log n)$ interactions. Finally, if $p \approx 1-x_1/x_2$, then all agents do agree on one opinion after $O(n\cdot \log^2 n)$ interactions, but either of the two opinions can survive. All our results hold with high probability.
- Published
- 2024
48. Constraints on Lorentz invariance violation from the extraordinary Mrk 421 flare of 2014 using a novel analysis method
- Author
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MAGIC Collaboration, Abe, S., Abhir, J., Abhishek, A., Acciari, V. A., Aguasca-Cabot, A., Agudo, I., Aniello, T., Ansoldi, S., Antonelli, L. A., Engels, A. Arbet, Arcaro, C., Artero, M., Asano, K., Babić, A., Baquero, A., de Almeida, U. Barres, Barrio, J. A., Batković, I., Bautista, A., Baxter, J., González, J. Becerra, Bednarek, W., Bernardini, E., Bernete, J., Berti, A., Besenrieder, J., Bigongiari, C., Biland, A., Blanch, O., Bonnoli, G., Bošnjak, Ž., Bronzini, E., Burelli, I., Busetto, G., Campoy-Ordaz, A., Carosi, A., Carosi, R., Carretero-Castrillo, M., Castro-Tirado, A. J., Cerasole, D., Ceribella, G., Chai, Y., Cifuentes, A., Colombo, E., Contreras, J. L., Cortina, J., Covino, S., D'Amico, G., D'Elia, V., Da Vela, P., Dazzi, F., De Angelis, A., De Lotto, B., de Menezes, R., Del Popolo, A., Delfino, M., Delgado, J., Mendez, C. Delgado, Di Pierro, F., Di Tria, R., Di Venere, L., Donini, A., Dorner, D., Doro, M., Elsaesser, D., Emery, G., Escudero, J., Fariña, L., Fattorini, A., Foffano, L., Font, L., Fröse, S., Fukami, S., Fukazawa, Y., López, R. J. García, Garczarczyk, M., Gasparyan, S., Gaug, M., Paiva, J. G. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Godinović, N., Gradetzke, T., Grau, R., Green, D., Green, J. G., Günther, P., Hadasch, D., Hahn, A., Hassan, T., Heckmann, L., Llorente, J. Herrera, Hrupec, D., Hütten, M., Imazawa, R., Ishio, K., Martínez, I. Jiménez, Jormanainen, J., Kankkunen, S., Kayanoki, T., Kerszberg, D., Kluge, G. W., Kobayashi, Y., Kouch, P. M., Kubo, H., Kushida, J., Láinez, M., Lamastra, A., Leone, F., Lindfors, E., Linhoff, L., Lombardi, S., Longo, F., López-Coto, R., López-Moya, M., López-Oramas, A., Loporchio, S., Lorini, A., Lyard, E., Fraga, B. Machado de Oliveira, Majumdar, P., Makariev, M., Maneva, G., Manganaro, M., Mangano, S., Mannheim, K., Mariotti, M., Martínez, M., Martínez-Chicharro, M., Mas-Aguilar, A., Mazin, D., Menchiari, S., Mender, S., Miceli, D., Miener, T., Miranda, J. M., Mirzoyan, R., González, M. Molero, Molina, E., Mondal, H. A., Moralejo, A., Morcuende, D., Nakamori, T., Nanci, C., Neustroev, V., Nickel, L., Rosillo, M. Nievas, Nigro, C., Nikolić, L., Nilsson, K., Nishijima, K., Ekoume, T. Njoh, Noda, K., Nogues, L., Nozaki, S., Ohtani, Y., Okumura, A., Otero-Santos, J., Paiano, S., Palatiello, M., Paneque, D., Paoletti, R., Paredes, J. M., Peresano, M., Persic, M., Pihet, M., Pirola, G., Podobnik, F., Moroni, P. G. Prada, Prandini, E., Principe, G., Priyadarshi, C., Rhode, W., Ribó, M., Rico, J., Righi, C., Sahakyan, N., Saito, T., Saturni, F. G., Schleicher, B., Schmidt, K., Schmuckermaier, F., Schubert, J. L., Schweizer, T., Sciaccaluga, A., Silvestri, G., Sitarek, J., Sliusar, V., Sobczynska, D., Stamerra, A., Strišković, J., Strom, D., Suda, Y., Tajima, H., Takahashi, M., Takeishi, R., Tavecchio, F., Temnikov, P., Terauchi, K., Terzić, T., Teshima, M., Truzzi, S., Tutone, A., Ubach, S., van Scherpenberg, J., Acosta, M. Vazquez, Ventura, S., Viale, I., Vigorito, C. F., Vitale, V., Vovk, I., Walter, R., Will, M., Wunderlich, C., and Yamamoto, T.
- Subjects
Astrophysics - High Energy Astrophysical Phenomena ,High Energy Physics - Phenomenology - Abstract
The Lorentz Invariance Violation (LIV), a proposed consequence of certain quantum gravity (QG) scenarios, could instigate an energy-dependent group velocity for ultra-relativistic particles. This energy dependence, although suppressed by the massive QG energy scale $E_\mathrm{QG}$, expected to be on the level of the Planck energy $1.22 \times 10^{19}$ GeV, is potentially detectable in astrophysical observations. In this scenario, the cosmological distances traversed by photons act as an amplifier for this effect. By leveraging the observation of a remarkable flare from the blazar Mrk\,421, recorded at energies above 100 GeV by the MAGIC telescopes on the night of April 25 to 26, 2014, we look for time delays scaling linearly and quadratically with the photon energies. Using for the first time in LIV studies a binned-likelihood approach we set constraints on the QG energy scale. For the linear scenario, we set $95\%$ lower limits $E_\mathrm{QG}>2.7\times10^{17}$ GeV for the subluminal case and $E_\mathrm{QG}> 3.6 \times10^{17}$ GeV for the superluminal case. For the quadratic scenario, the $95\%$ lower limits for the subluminal and superluminal cases are $E_\mathrm{QG}>2.6 \times10^{10}$ GeV and $E_\mathrm{QG}>2.5\times10^{10}$ GeV, respectively.
- Published
- 2024
49. Bridging magic and non-Gaussian resources via Gottesman-Kitaev-Preskill encoding
- Author
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Hahn, Oliver, Ferrini, Giulia, and Takagi, Ryuji
- Subjects
Quantum Physics - Abstract
Although the similarity between non-stabilizer states -- also known as magic states -- in discrete-variable systems and non-Gaussian states in continuous-variable systems has widely been recognized, the precise connections between these two notions have still been unclear. We establish a fundamental link between these two quantum resources via the Gottesman-Kitaev-Preskill (GKP) encoding. We show that the negativity of the continuous-variable Wigner function for an encoded GKP state coincides with a magic measure we introduce, which matches the negativity of the discrete Wigner function for odd dimensions. We also provide a continuous-variable representation of the stabilizer R\'enyi entropy -- a recent proposal for a magic measure for multi-qubit states. With this in hand, we give a classical simulation algorithm with runtime scaling with the resource contents, quantified by our magic measures. We also employ our results to prove that implementing a multi-qubit logical non-Clifford operation in the GKP code subspace requires a non-Gaussian operation even at the limit of perfect encoding, despite the fact that the ideal GKP states already come with a large amount of non-Gaussianity.
- Published
- 2024
50. Measurement of the Depth of Maximum of Air-Shower Profiles with energies between $\mathbf{10^{18.5}}$ and $\mathbf{10^{20}}$ eV using the Surface Detector of the Pierre Auger Observatory and Deep Learning
- Author
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The Pierre Auger Collaboration, Halim, A. Abdul, Abreu, P., Aglietta, M., Allekotte, I., Cheminant, K. Almeida, Almela, A., Aloisio, R., Alvarez-Muñiz, J., Yebra, J. Ammerman, Anastasi, G. A., Anchordoqui, L., Andrada, B., Dourado, L. Andrade, Andringa, S., Apollonio, L., Aramo, C., Ferreira, P. R. Araújo, Arnone, E., Velázquez, J. C. Arteaga, Assis, P., Avila, G., Avocone, E., Bakalova, A., Barbato, F., Mocellin, A. Bartz, Berat, C., Bertaina, M. E., Bhatta, G., Bianciotto, M., Biermann, P. L., Binet, V., Bismark, K., Bister, T., Biteau, J., Blazek, J., Bleve, C., Blümer, J., Boháčová, M., Boncioli, D., Bonifazi, C., Arbeletche, L. Bonneau, Borodai, N., Brack, J., Orchera, P. G. Brichetto, Briechle, F. L., Bueno, A., Buitink, S., Buscemi, M., Büsken, M., Bwembya, A., Caballero-Mora, K. S., Cabana-Freire, S., Caccianiga, L., Campuzano, F., Caruso, R., Castellina, A., Catalani, F., Cataldi, G., Cazon, L., Cerda, M., Čermáková, B., Cermenati, A., Chinellato, J. A., Chudoba, J., Chytka, L., Clay, R. W., Cerutti, A. C. Cobos, Colalillo, R., Coluccia, M. R., Conceição, R., Condorelli, A., Consolati, G., Conte, M., Convenga, F., Santos, D. Correia dos, Costa, P. J., Covault, C. E., Cristinziani, M., Sanchez, C. S. Cruz, Dasso, S., Daumiller, K., Dawson, B. R., de Almeida, R. M., de Errico, B., de Jesús, J., de Jong, S. J., Neto, J. R. T. de Mello, De Mitri, I., de Oliveira, J., Franco, D. de Oliveira, de Palma, F., de Souza, V., De Vito, E., Del Popolo, A., Deligny, O., Denner, N., Deval, L., di Matteo, A., do, J. A., Dobre, M., Dobrigkeit, C., D'Olivo, J. C., Mendes, L. M. Domingues, Dorosti, Q., Anjos, J. C. dos, Anjos, R. C. dos, Ebr, J., Ellwanger, F., Emam, M., Engel, R., Epicoco, I., Erdmann, M., Etchegoyen, A., Evoli, C., Falcke, H., Farrar, G., Fauth, A. C., Fehler, T., Feldbusch, F., Fenu, F., Fernandes, A., Fick, B., Figueira, J. M., Filip, P., Filipčič, A., Fitoussi, T., Flaggs, B., Fodran, T., Fujii, T., Fuster, A., Galea, C., García, B., Gaudu, C., Gherghel-Lascu, A., Ghia, P. L., Giaccari, U., Glombitza, J., Gobbi, F., Gollan, F., Golup, G., Berisso, M. Gómez, Vitale, P. F. Gómez, Gongora, J. P., González, J. M., González, N., Góra, D., Gorgi, A., Gottowik, M., Guarino, F., Guedes, G. P., Guido, E., Gülzow, L., Hahn, S., Hamal, P., Hampel, M. R., Hansen, P., Harari, D., Harvey, V. M., Haungs, A., Hebbeker, T., Hojvat, C., Hörandel, J. R., Horvath, P., Hrabovský, M., Huege, T., Insolia, A., Isar, P. G., Janecek, P., Jilek, V., Johnsen, J. A., Jurysek, J., Kampert, K. -H., Keilhauer, B., Khakurdikar, A., Covilakam, V. V. Kizakke, Klages, H. O., Kleifges, M., Knapp, F., Köhler, J., Krieger, F., Kunka, N., Lago, B. L., Langner, N., de Oliveira, M. A. Leigui, Lema-Capeans, Y., Letessier-Selvon, A., Lhenry-Yvon, I., Lopes, L., Lu, L., Luce, Q., Lundquist, J. P., Payeras, A. Machado, Majercakova, M., Mandat, D., Manning, B. C., Mantsch, P., Mariani, F. M., Mariazzi, A. G., Mariş, I. C., Marsella, G., Martello, D., Martinelli, S., Bravo, O. Martínez, Martins, M. A., Mathes, H. -J., Matthews, J., Matthiae, G., Mayotte, E., Mayotte, S., Mazur, P. O., Medina-Tanco, G., Meinert, J., Melo, D., Menshikov, A., Merx, C., Michal, S., Micheletti, M. I., Miramonti, L., Mollerach, S., Montanet, F., Morejon, L., Mulrey, K., Mussa, R., Namasaka, W. M., Negi, S., Nellen, L., Nguyen, K., Nicora, G., Niechciol, M., Nitz, D., Nosek, D., Novotny, V., Nožka, L., Nucita, A., Núñez, L. A., Oliveira, C., Palatka, M., Pallotta, J., Panja, S., Parente, G., Paulsen, T., Pawlowsky, J., Pech, M., Pękala, J., Pelayo, R., Pelgrims, V., Pereira, L. A. S., Martins, E. E. Pereira, Bertolli, C. Pérez, Perrone, L., Petrera, S., Petrucci, C., Pierog, T., Pimenta, M., Platino, M., Pont, B., Pothast, M., Shahvar, M. Pourmohammad, Privitera, P., Prouza, M., Querchfeld, S., Rautenberg, J., Ravignani, D., Akim, J. V. Reginatto, Reininghaus, M., Reuzki, A., Ridky, J., Riehn, F., Risse, M., Rizi, V., de Carvalho, W. Rodrigues, Rodriguez, E., Rojo, J. Rodriguez, Roncoroni, M. J., Rossoni, S., Roth, M., Roulet, E., Rovero, A. C., Saftoiu, A., Saharan, M., Salamida, F., Salazar, H., Salina, G., Gomez, J. D. Sanabria, Sánchez, F., Santos, E. M., Santos, E., Sarazin, F., Sarmento, R., Sato, R., Savina, P., Schäfer, C. M., Scherini, V., Schieler, H., Schimassek, M., Schimp, M., Schmidt, D., Scholten, O., Schoorlemmer, H., Schovánek, P., Schröder, F. G., Schulte, J., Schulz, T., Sciutto, S. J., Scornavacche, M., Sedoski, A., Segreto, A., Sehgal, S., Shivashankara, S. U., Sigl, G., Simkova, K., Simon, F., Smau, R., Šmída, R., Sommers, P., Squartini, R., Stadelmaier, M., Stanič, S., Stasielak, J., Stassi, P., Strähnz, S., Straub, M., Suomijärvi, T., Supanitsky, A. D., Svozilikova, Z., Szadkowski, Z., Tairli, F., Tapia, A., Taricco, C., Timmermans, C., Tkachenko, O., Tobiska, P., Peixoto, C. J. Todero, Tomé, B., Torrès, Z., Travaini, A., Travnicek, P., Tueros, M., Unger, M., Uzeiroska, R., Vaclavek, L., Vacula, M., Galicia, J. F. Valdés, Valore, L., Varela, E., Vašíčková, V., Vásquez-Ramírez, A., Veberič, D., Quispe, I. D. Vergara, Verzi, V., Vicha, J., Vink, J., Vorobiov, S., Watanabe, C., Watson, A. A., Weindl, A., Wiencke, L., Wilczyński, H., Wittkowski, D., Wundheiler, B., Yue, B., Yushkov, A., Zapparrata, O., Zas, E., Zavrtanik, D., and Zavrtanik, M.
- Subjects
Astrophysics - High Energy Astrophysical Phenomena ,Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
We report an investigation of the mass composition of cosmic rays with energies from 3 to 100 EeV (1 EeV=$10^{18}$ eV) using the distributions of the depth of shower maximum $X_\mathrm{max}$. The analysis relies on ${\sim}50,000$ events recorded by the Surface Detector of the Pierre Auger Observatory and a deep-learning-based reconstruction algorithm. Above energies of 5 EeV, the data set offers a 10-fold increase in statistics with respect to fluorescence measurements at the Observatory. After cross-calibration using the Fluorescence Detector, this enables the first measurement of the evolution of the mean and the standard deviation of the $X_\mathrm{max}$ distributions up to 100 EeV. Our findings are threefold: (1.) The evolution of the mean logarithmic mass towards a heavier composition with increasing energy can be confirmed and is extended to 100 EeV. (2.) The evolution of the fluctuations of $X_\mathrm{max}$ towards a heavier and purer composition with increasing energy can be confirmed with high statistics. We report a rather heavy composition and small fluctuations in $X_\mathrm{max}$ at the highest energies. (3.) We find indications for a characteristic structure beyond a constant change in the mean logarithmic mass, featuring three breaks that are observed in proximity to the ankle, instep, and suppression features in the energy spectrum., Comment: submitted to Phys. Rev. D, 28 pages, 18 figures, 5 tables
- Published
- 2024
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