191,004 results on '"Desai AN"'
Search Results
202. Implementation of New Education Policy in India and the Prospects of Transformational Female Leadership in Indian Higher Education
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Falguni P. Desai and P. S. Desai
- Abstract
Aim: To investigate to what extent the stakeholders believe in females having attributes of transformational leadership to rise at higher positions in institutions of higher education in India while implementing New Education Policy in India. To know where we are right now and where we need to go in terms of promoting female leaders in Indian higher education. Methods: Both qualitative and quantitative methods are used. Qualitative responses from 10 Indian women leaders are collected from those 03 qualitative responses are quoted in the paper and considered in the analysis. MLQ* tool (Multifactor leadership Questionnaire) used to collect responses of 51 different stakeholders of higher education. Findings: The study shows that female leadership can be trailblazing in organizational management in institutions of Higher Education in India while implementing the New Education Policy. The results anticipate providing insights to initiate Indian policymakers and recruiting bodies to motivate women to take up leadership positions. Originality and Cognitive Value: The area of the prospects of transformational female leadership in Indian higher education in the context of implementation of New Education Policy in India is a novel exploration as education policy is implemented recently in 2020 and gender equity is a major aspect of concern in achieving Sustainable development Goals. [For the full proceedings, see ED654100.]
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- 2023
203. A Study with Simulation Implementation of Field Failure Protection on Synchronous Generator
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Desai, Jigneshkumar P., Desai, Ankurkumar, Purohit, Kishor, Bajag, Rahul, and Parmar, Chirag
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- 2024
- Full Text
- View/download PDF
204. The Dark Energy Survey 5-year photometrically classified type Ia supernovae without host-galaxy redshifts
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Möller, A., Wiseman, P., Smith, M., Lidman, C., Davis, T. M., Kessler, R., Sako, M., Sullivan, M., Galbany, L., Lee, J., Nichol, R. C., Sánchez, B. O., Vincenzi, M., Tucker, B. E., Abbott, T. M. C., Aguena, M., Allam, S., Alves, O., Andrade-Oliveira, F., Bacon, D., Bertin, E., Brooks, D., Rosell, A. Carnero, Castander, F. J., Desai, S., Diehl, H. T., Everett, S., Ferrero, I., Friedel, D., Frieman, J., García-Bellido, J., Gaztanaga, E., Giannini, G., Gruendl, R. A., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lahav, O., Lee, S., Marshall, J. L., Mena-Fernández, J., Menanteau, F., Miquel, R., Myles, J., Ogando, R. L. C., Palmese, A., Pieres, A., Malagón, A. A. Plazas, Roodman, A., Sanchez, E., Cid, D. Sanchez, Sevilla-Noarbe, I., Suchyta, E., Swanson, M. E. C., Tarle, G., Tucker, D. L., Walker, A. R., Weaverdyck, N., da Costa, L. N., and Pereira, M. E. S.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
Current and future Type Ia Supernova (SN Ia) surveys will need to adopt new approaches to classifying SNe and obtaining their redshifts without spectra if they wish to reach their full potential. We present here a novel approach that uses only photometry to identify SNe Ia in the 5-year Dark Energy Survey (DES) dataset using the SuperNNova classifier. Our approach, which does not rely on any information from the SN host-galaxy, recovers SNe Ia that might otherwise be lost due to a lack of an identifiable host. We select 2,298 high-quality SNe Ia from the DES 5-year dataset an almost complete sample of detected SNe Ia. More than 700 of these have no spectroscopic host redshift and are potentially new SNIa compared to the DES-SN5YR cosmology analysis. To analyse these SNe Ia, we derive their redshifts and properties using only their light-curves with a modified version of the SALT2 light-curve fitter. Compared to other DES SN Ia samples with spectroscopic redshifts, our new sample has in average higher redshift, bluer and broader light-curves, and fainter host-galaxies. Future surveys such as LSST will also face an additional challenge, the scarcity of spectroscopic resources for follow-up. When applying our novel method to DES data, we reduce the need for follow-up by a factor of four and three for host-galaxy and live SN respectively compared to earlier approaches. Our novel method thus leads to better optimisation of spectroscopic resources for follow-up., Comment: Accepted MNRAS
- Published
- 2024
205. Characterization of the Astrophysical Diffuse Neutrino Flux using Starting Track Events in IceCube
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Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Blot, S., Bontempo, F., Book, J. Y., Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Busse, R. S., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Corley, R., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neumann, M., Niederhausen, H., Nisa, M. U., Noell, A., Novikov, A., Nowicki, S. C., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
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Astrophysics - High Energy Astrophysical Phenomena ,Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
A measurement of the diffuse astrophysical neutrino spectrum is presented using IceCube data collected from 2011-2022 (10.3 years). We developed novel detection techniques to search for events with a contained vertex and exiting track induced by muon neutrinos undergoing a charged-current interaction. Searching for these starting track events allows us to not only more effectively reject atmospheric muons but also atmospheric neutrino backgrounds in the southern sky, opening a new window to the sub-100 TeV astrophysical neutrino sky. The event selection is constructed using a dynamic starting track veto and machine learning algorithms. We use this data to measure the astrophysical diffuse flux as a single power law flux (SPL) with a best-fit spectral index of $\gamma = 2.58 ^{+0.10}_{-0.09}$ and per-flavor normalization of $\phi^{\mathrm{Astro}}_{\mathrm{per-flavor}} = 1.68 ^{+0.19}_{-0.22} \times 10^{-18} \times \mathrm{GeV}^{-1} \mathrm{cm}^{-2} \mathrm{s}^{-1} \mathrm{sr}^{-1}$ (at 100 TeV). The sensitive energy range for this dataset is 3 - 550 TeV under the SPL assumption. This data was also used to measure the flux under a broken power law, however we did not find any evidence of a low energy cutoff., Comment: 27 pages, 28 figures
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- 2024
- Full Text
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206. Between Copyright and Computer Science: The Law and Ethics of Generative AI
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Desai, Deven R. and Riedl, Mark
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Computer Science - Computers and Society - Abstract
Copyright and computer science continue to intersect and clash, but they can coexist. The advent of new technologies such as digitization of visual and aural creations, sharing technologies, search engines, social media offerings, and more challenge copyright-based industries and reopen questions about the reach of copyright law. Breakthroughs in artificial intelligence research, especially Large Language Models that leverage copyrighted material as part of training models, are the latest examples of the ongoing tension between copyright and computer science. The exuberance, rush-to-market, and edge problem cases created by a few misguided companies now raises challenges to core legal doctrines and may shift Open Internet practices for the worse. That result does not have to be, and should not be, the outcome. This Article shows that, contrary to some scholars' views, fair use law does not bless all ways that someone can gain access to copyrighted material even when the purpose is fair use. Nonetheless, the scientific need for more data to advance AI research means access to large book corpora and the Open Internet is vital for the future of that research. The copyright industry claims, however, that almost all uses of copyrighted material must be compensated, even for non-expressive uses. The Article's solution accepts that both sides need to change. It is one that forces the computer science world to discipline its behaviors and, in some cases, pay for copyrighted material. It also requires the copyright industry to abandon its belief that all uses must be compensated or restricted to uses sanctioned by the copyright industry. As part of this re-balancing, the Article addresses a problem that has grown out of this clash and under theorized., Comment: Northwestern Journal of Technology and Intellectual Property, Vol. 22
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- 2024
207. Neutrino Rate Predictions for FASER
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FASER Collaboration, Abraham, Roshan Mammen, Anders, John, Antel, Claire, Ariga, Akitaka, Ariga, Tomoko, Atkinson, Jeremy, Bernlochner, Florian U., Boeckh, Tobias, Boyd, Jamie, Brenner, Lydia, Burger, Angela, Cadoux, Franck, Cardella, Roberto, Casper, David W., Cavanagh, Charlotte, Chen, Xin, Coccaro, Andrea, Débieux, Stephane, D'Onofrio, Monica, Desai, Ansh, Dmitrievsky, Sergey, Eley, Sinead, Favre, Yannick, Fellers, Deion, Feng, Jonathan L., Fenoglio, Carlo Alberto, Ferrere, Didier, Fieg, Max, Filali, Wissal, Gibson, Stephen, Gonzalez-Sevilla, Sergio, Gornushkin, Yuri, Gwilliam, Carl, Hayakawa, Daiki, Hsu, Shih-Chieh, Hu, Zhen, Iacobucci, Giuseppe, Inada, Tomohiro, Iodice, Luca, Jakobsen, Sune, Joos, Hans, Kajomovitz, Enrique, Kawahara, Hiroaki, Keyken, Alex, Kling, Felix, Köck, Daniela, Kontaxakis, Pantelis, Kose, Umut, Kotitsa, Rafaella, Kuehn, Susanne, Kugathasan, Thanushan, Lefebvre, Helena, Levinson, Lorne, Li, Ke, Liu, Jinfeng, Lutz, Margaret S., MacDonald, Jack, Magliocca, Chiara, Martinelli, Fulvio, McCoy, Lawson, McFayden, Josh, Medina, Andrea Pizarro, Milanesio, Matteo, Moretti, Théo, Munker, Magdalena, Nakamura, Mitsuhiro, Nakano, Toshiyuki, Neuhaus, Friedemann, Nevay, Laurie, Ohashi, Ken, Otono, Hidetoshi, Pang, Hao, Paolozzi, Lorenzo, Petersen, Brian, Prim, Markus, Queitsch-Maitland, Michaela, Rokujo, Hiroki, Ruiz-Choliz, Elisa, Rubbia, André, Sabater-Iglesias, Jorge, Sato, Osamu, Scampoli, Paola, Schmieden, Kristof, Schott, Matthias, Sfyrla, Anna, Shamim, Mansoora, Shively, Savannah, Takubo, Yosuke, Tarannum, Noshin, Theiner, Ondrej, Torrence, Eric, Vasina, Svetlana, Vormwald, Benedikt, Wang, Di, Wang, Yuxiao, Welch, Eli, Zahorec, Samuel, Zambito, Stefano, and Zhang, Shunliang
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High Energy Physics - Experiment ,High Energy Physics - Phenomenology - Abstract
The Forward Search Experiment (FASER) at CERN's Large Hadron Collider (LHC) has recently directly detected the first collider neutrinos. Neutrinos play an important role in all FASER analyses, either as signal or background, and it is therefore essential to understand the neutrino event rates. In this study, we update previous simulations and present prescriptions for theoretical predictions of neutrino fluxes and cross sections, together with their associated uncertainties. With these results, we discuss the potential for possible measurements that could be carried out in the coming years with the FASER neutrino data to be collected in LHC Run 3 and Run 4., Comment: 19 pages, 10 figures
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- 2024
208. Prospector Heads: Generalized Feature Attribution for Large Models & Data
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Machiraju, Gautam, Derry, Alexander, Desai, Arjun, Guha, Neel, Karimi, Amir-Hossein, Zou, James, Altman, Russ, Ré, Christopher, and Mallick, Parag
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Quantitative Biology - Quantitative Methods - Abstract
Feature attribution, the ability to localize regions of the input data that are relevant for classification, is an important capability for ML models in scientific and biomedical domains. Current methods for feature attribution, which rely on "explaining" the predictions of end-to-end classifiers, suffer from imprecise feature localization and are inadequate for use with small sample sizes and high-dimensional datasets due to computational challenges. We introduce prospector heads, an efficient and interpretable alternative to explanation-based attribution methods that can be applied to any encoder and any data modality. Prospector heads generalize across modalities through experiments on sequences (text), images (pathology), and graphs (protein structures), outperforming baseline attribution methods by up to 26.3 points in mean localization AUPRC. We also demonstrate how prospector heads enable improved interpretation and discovery of class-specific patterns in input data. Through their high performance, flexibility, and generalizability, prospectors provide a framework for improving trust and transparency for ML models in complex domains., Comment: 30 pages, 16 figures, 8 tables. Accepted to ICML 2024
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- 2024
209. Generalized Lomb-Scargle Analysis of 22 years of Super-Kamiokande solar $^8$B neutrino data
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Pasumarti, Vibhavasu and Desai, Shantanu
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High Energy Physics - Experiment ,Astrophysics - High Energy Astrophysical Phenomena - Abstract
We apply the generalized Lomb-Scargle periodogram to 22 years data of solar $^{8}$B neutrino fluxes detected by Super-Kamiokande. The primary motivation of this work was to check if the sinusoidal modulation at a frequency of 9.43/year (with a period of 38 days), which we had found to be marginally significant with the first five years of Super-K data, persists, with the accumulated data. We use four different metrics for the calculation of significance. We do not find any evidence for periodicity at the aforementioned frequency or any other frequency with the updated data. Therefore the marginally detected periodicity at 9.43/year with the first five years of data was only a statistical fluctuation., Comment: 8 pages, 3 figures. Accepted for publication in EPJC
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- 2024
- Full Text
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210. Private PAC Learning May be Harder than Online Learning
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Bun, Mark, Cohen, Aloni, and Desai, Rathin
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Computer Science - Machine Learning ,Computer Science - Cryptography and Security ,Computer Science - Data Structures and Algorithms - Abstract
We continue the study of the computational complexity of differentially private PAC learning and how it is situated within the foundations of machine learning. A recent line of work uncovered a qualitative equivalence between the private PAC model and Littlestone's mistake-bounded model of online learning, in particular, showing that any concept class of Littlestone dimension $d$ can be privately PAC learned using $\mathrm{poly}(d)$ samples. This raises the natural question of whether there might be a generic conversion from online learners to private PAC learners that also preserves computational efficiency. We give a negative answer to this question under reasonable cryptographic assumptions (roughly, those from which it is possible to build indistinguishability obfuscation for all circuits). We exhibit a concept class that admits an online learner running in polynomial time with a polynomial mistake bound, but for which there is no computationally-efficient differentially private PAC learner. Our construction and analysis strengthens and generalizes that of Bun and Zhandry (TCC 2016-A), who established such a separation between private and non-private PAC learner.
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- 2024
211. Dark Energy Survey: Galaxy Sample for the Baryonic Acoustic Oscillation Measurement from the Final Dataset
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Mena-Fernández, J., Rodríguez-Monroy, M., Avila, S., Porredon, A., Chan, K. C., Camacho, H., Weaverdyck, N., Sevilla-Noarbe, I., Sanchez, E., Cipriano, L. Toribio San, De Vicente, J., Ferrero, I., Cawthon, R., Rosell, A. Carnero, Elvin-Poole, J., Giannini, G., Adamow, M., Bechtol, K., Drlica-Wagner, A., Gruendl, R. A., Hartley, W. G., Pieres, A., Ross, A. J., Rykoff, E. S., Sheldon, E., Yanny, B., Abbott, T. M. C., Aguena, M., Allam, S., Alves, O., Amon, A., Andrade-Oliveira, F., Annis, J., Bacon, D., Blazek, J., Bocquet, S., Brooks, D., Carretero, J., Castander, F. J., Conselice, C., Crocce, M., da Costa, L. N., Pereira, M. E. S., Davis, T. M., Deiosso, N., Desai, S., Diehl, H. T., Dodelson, S., Doux, C., Everett, S., Frieman, J., García-Bellido, J., Gaztanaga, E., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., Huterer, D., Kuehn, K., Lahav, O., Lee, S., Lidman, C., Lin, H., Marshall, J. L., Menanteau, F., Miquel, R., Myles, J., Ogando, R. L. C., Palmese, A., Percival, W. J., Malagón, A. A. Plazas, Roodman, A., Rosenfeld, R., Samuroff, S., Cid, D. Sanchez, Santiago, B., Schubnell, M., Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., To, C., Tucker, D. L., Walker, A. R., Weller, J., Wiseman, P., and Yamamoto, M.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
In this paper we present and validate the galaxy sample used for the analysis of the baryon acoustic oscillation (BAO) signal in the Dark Energy Survey (DES) Y6 data. The definition is based on a color and redshift-dependent magnitude cut optimized to select galaxies at redshifts higher than 0.6, while ensuring a high-quality photo-$z$ determination. The optimization is performed using a Fisher forecast algorithm, finding the optimal $i$-magnitude cut to be given by $i$<19.64+2.894$z_{\rm ph}$. For the optimal sample, we forecast an increase in precision in the BAO measurement of $\sim$25% with respect to the Y3 analysis. Our BAO sample has a total of 15,937,556 galaxies in the redshift range 0.6<$z_{\rm ph}$<1.2, and its angular mask covers 4,273.42 deg${}^2$ to a depth of $i$=22.5. We validate its redshift distributions with three different methods: directional neighborhood fitting algorithm (DNF), which is our primary photo-$z$ estimation; direct calibration with spectroscopic redshifts from VIPERS; and clustering redshift using SDSS galaxies. The fiducial redshift distribution is a combination of these three techniques performed by modifying the mean and width of the DNF distributions to match those of VIPERS and clustering redshift. In this paper we also describe the methodology used to mitigate the effect of observational systematics, which is analogous to the one used in the Y3 analysis. This paper is one of the two dedicated to the analysis of the BAO signal in DES Y6. In its companion paper, we present the angular diameter distance constraints obtained through the fitting to the BAO scale., Comment: 23 pages, 10 figures. Submitted to PRD
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- 2024
212. Dark Energy Survey: A 2.1% measurement of the angular Baryonic Acoustic Oscillation scale at redshift $z_{\rm eff}$=0.85 from the final dataset
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DES Collaboration, Abbott, T. M. C., Adamow, M., Aguena, M., Allam, S., Alves, O., Amon, A., Andrade-Oliveira, F., Asorey, J., Avila, S., Bacon, D., Bechtol, K., Bernstein, G. M., Bertin, E., Blazek, J., Bocquet, S., Brooks, D., Burke, D. L., Camacho, H., Rosell, A. Carnero, Carollo, D., Carretero, J., Castander, F. J., Cawthon, R., Chan, K. C., Chang, C., Conselice, C., Costanzi, M., Crocce, M., da Costa, L. N., Pereira, M. E. S., Davis, T. M., De Vicente, J., Deiosso, N., Desai, S., Diehl, H. T., Dodelson, S., Doux, C., Drlica-Wagner, A., Elvin-Poole, J., Everett, S., Ferrero, I., Ferté, A., Flaugher, B., Fosalba, P., Frieman, J., García-Bellido, J., Gaztanaga, E., Giannini, G., Gruendl, R. A., Gutierrez, G., Hartley, W. G., Hinton, S. R., Hollowood, D. L., Honscheid, K., Huterer, D., James, D. J., Kent, S., Kuehn, K., Lahav, O., Lee, S., Lidman, C., Lin, H., Marshall, J. L., Martini, P., Mena-Fernández, J., Menanteau, F., Miquel, R., Mohr, J. J., Myles, J., Nichol, R. C., Ogando, R. L. C., Palmese, A., Percival, W. J., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Prat, J., Rodríguez-Monroy, M., Romer, A. K., Roodman, A., Rosenfeld, R., Ross, A. J., Rykoff, E. S., Sako, M., Samuroff, S., Sánchez, C., Sanchez, E., Cid, D. Sanchez, Santiago, B., Schubnell, M., Sevilla-Noarbe, I., Sheldon, E., Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., To, C., Cipriano, L. Toribio San, Troxel, M. A., Tucker, B. E., Tucker, D. L., Walker, A. R., Weaverdyck, N., Weller, J., Wiseman, P., and Yanny, B.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
We present the angular diameter distance measurement obtained with the Baryonic Acoustic Oscillation feature from galaxy clustering in the completed Dark Energy Survey, consisting of six years (Y6) of observations. We use the Y6 BAO galaxy sample, optimized for BAO science in the redshift range 0.6<$z$<1.2, with an effective redshift at $z_{\rm eff}$=0.85 and split into six tomographic bins. The sample has nearly 16 million galaxies over 4,273 square degrees. Our consensus measurement constrains the ratio of the angular distance to sound horizon scale to $D_M(z_{\rm eff})/r_d$ = 19.51$\pm$0.41 (at 68.3% confidence interval), resulting from comparing the BAO position in our data to that predicted by Planck $\Lambda$CDM via the BAO shift parameter $\alpha=(D_M/r_d)/(D_M/r_d)_{\rm Planck}$. To achieve this, the BAO shift is measured with three different methods, Angular Correlation Function (ACF), Angular Power Spectrum (APS), and Projected Correlation Function (PCF) obtaining $\alpha=$ 0.952$\pm$0.023, 0.962$\pm$0.022, and 0.955$\pm$0.020, respectively, which we combine to $\alpha=$ 0.957$\pm$0.020, including systematic errors. When compared with the $\Lambda$CDM model that best fits Planck data, this measurement is found to be 4.3% and 2.1$\sigma$ below the angular BAO scale predicted. To date, it represents the most precise angular BAO measurement at $z$>0.75 from any survey and the most precise measurement at any redshift from photometric surveys. The analysis was performed blinded to the BAO position and it is shown to be robust against analysis choices, data removal, redshift calibrations and observational systematics., Comment: Submitted to PRD, 39 pages, 12 figures
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- 2024
213. The SRG/eROSITA All-Sky Survey: Dark Energy Survey Year 3 Weak Gravitational Lensing by eRASS1 selected Galaxy Clusters
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Grandis, S., Ghirardini, V., Bocquet, S., Garrel, C., Mohr, J. J., Liu, A., Kluge, M., Kimmig, L., Reiprich, T. H., Alarcon, A., Amon, A., Artis, E., Bahar, Y. E., Balzer, F., Bechtol, K., Becker, M. R., Bernstein, G., Bulbul, E., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Cawthon, R., Chang, C., Chen, R., Chiu, I., Choi, A., Clerc, N., Comparat, J., Cordero, J., Davis, C., Derose, J., Diehl, H. T., Dodelson, S., Doux, C., Drlica-Wagner, A., Eckert, K., Elvin-Poole, J., Everett, S., Ferte, A., Gatt, M., Giannini, G., Giles, P., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Herner, K., Huf, E. M., Kleinebreil, F., Kuropatkin, N., Leget, P. F., Maccrann, N., Mccullough, J., Merloni, A., Myles, J., Nandra, K., Navarro-Alsina, A., Okabe, N., Pacaud, F., Pandey, S., Prat, J., Predehl, P., Ramos, M., Raveri, M., Rollins, R. P., Roodman, A., Ross, A. J., Rykoff, E. S., Sanchez, C., Sanders, J., Schrabback, T., Secco, L. F., Seppi, R., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M., Tutusaus, I., Varga, T. N., Wu, H., Yanny, B., Yin, B., Zhang, X., Zhang, Y., Alves, O., Bhargava, S., Brooks, D., Burke, D. L., Carretero, J., Costanzi, M., da Costa, L. N., Pereira, M. E. S., De Vicente, J., Desai, S., Doel, P., Ferrero, I., Flaugher, B., Friedel, D., Frieman, J., García-Bellido, J., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Jeffrey, N., Lahav, O., Lee, S., Marshall, J. L., Menanteau, F., Ogando, R. L. C., Pieres, A., Malagón, A. A. Plazas, Romer, A. K., Sanchez, E., Schubnell, M., Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Weaverdyck, N., and Weller, J.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
Number counts of galaxy clusters across redshift are a powerful cosmological probe, if a precise and accurate reconstruction of the underlying mass distribution is performed -- a challenge called mass calibration. With the advent of wide and deep photometric surveys, weak gravitational lensing by clusters has become the method of choice to perform this measurement. We measure and validate the weak gravitational lensing (WL) signature in the shape of galaxies observed in the first 3 years of the DES Y3 caused by galaxy clusters selected in the first all-sky survey performed by SRG/eROSITA. These data are then used to determine the scaling between X-ray photon count rate of the clusters and their halo mass and redshift. We empirically determine the degree of cluster member contamination in our background source sample. The individual cluster shear profiles are then analysed with a Bayesian population model that self-consistently accounts for the lens sample selection and contamination, and includes marginalization over a host of instrumental and astrophysical systematics. To quantify the accuracy of the mass extraction of that model, we perform mass measurements on mock cluster catalogs with realistic synthetic shear profiles. This allows us to establish that hydro-dynamical modelling uncertainties at low lens redshifts ($z<0.6$) are the dominant systematic limitation. At high lens redshift the uncertainties of the sources' photometric redshift calibration dominate. With regard to the X-ray count rate to halo mass relation, we constrain all its parameters. This work sets the stage for a joint analysis with the number counts of eRASS1 clusters to constrain a host of cosmological parameters. We demonstrate that WL mass calibration of galaxy clusters can be performed successfully with source galaxies whose calibration was performed primarily for cosmic shear experiments., Comment: 27 pages, 18 figures, 2 appendices, submitted to A\&A
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- 2024
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214. Oracle-Efficient Differentially Private Learning with Public Data
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Block, Adam, Bun, Mark, Desai, Rathin, Shetty, Abhishek, and Wu, Steven
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Statistics - Machine Learning ,Computer Science - Cryptography and Security ,Computer Science - Machine Learning - Abstract
Due to statistical lower bounds on the learnability of many function classes under privacy constraints, there has been recent interest in leveraging public data to improve the performance of private learning algorithms. In this model, algorithms must always guarantee differential privacy with respect to the private samples while also ensuring learning guarantees when the private data distribution is sufficiently close to that of the public data. Previous work has demonstrated that when sufficient public, unlabelled data is available, private learning can be made statistically tractable, but the resulting algorithms have all been computationally inefficient. In this work, we present the first computationally efficient, algorithms to provably leverage public data to learn privately whenever a function class is learnable non-privately, where our notion of computational efficiency is with respect to the number of calls to an optimization oracle for the function class. In addition to this general result, we provide specialized algorithms with improved sample complexities in the special cases when the function class is convex or when the task is binary classification.
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- 2024
215. The TESS-Keck Survey. XVIII. A sub-Neptune and spurious long-period signal in the TOI-1751 system
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Desai, Anmol, Turtelboom, Emma V., Harada, Caleb K., Dressing, Courtney D., Rice, David R., Murphy, Joseph M. Akana, Brinkman, Casey L., Chontos, Ashley, Crossfield, Ian J. M., Dai, Fei, Hill, Michelle L., Fetherolf, Tara, Giacalone, Steven, Howard, Andrew W., Huber, Daniel, Isaacson, Howard, Kane, Stephen R., Lubin, Jack, MacDougall, Mason G., Mayo, Andrew W., Močnik, Teo, Polanski, Alex S., Rice, Malena, Robertson, Paul, Rubenzahl, Ryan A., Van Zandt, Judah, Weiss, Lauren M., Bieryla, Allyson, Buchhave, Lars A., Jenkins, Jon M., Kostov, Veselin B., Levine, Alan M., Lillo-Box, Jorge, Paegert, M., Rabus, Markus, Seager, S., Stassun, Keivan G., Ting, Eric B., Watanabe, David, and Winn, Joshua N.
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Astrophysics - Earth and Planetary Astrophysics - Abstract
We present and confirm TOI-1751 b, a transiting sub-Neptune orbiting a slightly evolved, solar-type, metal-poor star ($T_{eff} = 5996 \pm 110$ K, $log(g) = 4.2 \pm 0.1$, V = 9.3 mag, [Fe/H] = $-0.40 \pm 0.06$ dex) every 37.47 d. We use TESS photometry to measure a planet radius of $2.77_{-0.07}^{+0.15}~\rm{R_\oplus}$. We also use both Keck/HIRES and APF/Levy radial velocities (RV) to derive a planet mass of $14.5_{-3.14}^{+3.15} ~\rm{M_\oplus}$, and thus a planet density of $3.6 \pm 0.9 \, {\rm g}\,{\rm cm}^{-3}$. There is also a long-period ($\sim400~\rm{d}$) signal that is observed in only the Keck/HIRES data. We conclude that this long-period signal is not planetary in nature, and is likely due to the window function of the Keck/HIRES observations. This highlights the role of complementary observations from multiple observatories to identify and exclude aliases in RV data. Finally, we investigate potential compositions of this planet, including rocky and water-rich solutions, as well as theoretical irradiated ocean models. TOI-1751 b is a warm sub-Neptune, with an equilibrium temperature of $\sim 820$ K. As TOI-1751 is a metal-poor star, TOI-1751 b may have formed in a water-enriched formation environment. We thus favor a volatile-rich interior composition for this planet., Comment: 30 pages, 9 figures. Accepted for publication in AJ
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- 2024
216. CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting
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Yang, Jiezhi, Desai, Khushi, Packer, Charles, Bhatia, Harshil, Rhinehart, Nicholas, McAllister, Rowan, and Gonzalez, Joseph
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Computer Science - Computer Vision and Pattern Recognition - Abstract
We propose CARFF, a method for predicting future 3D scenes given past observations. Our method maps 2D ego-centric images to a distribution over plausible 3D latent scene configurations and predicts the evolution of hypothesized scenes through time. Our latents condition a global Neural Radiance Field (NeRF) to represent a 3D scene model, enabling explainable predictions and straightforward downstream planning. This approach models the world as a POMDP and considers complex scenarios of uncertainty in environmental states and dynamics. Specifically, we employ a two-stage training of Pose-Conditional-VAE and NeRF to learn 3D representations, and auto-regressively predict latent scene representations utilizing a mixture density network. We demonstrate the utility of our method in scenarios using the CARLA driving simulator, where CARFF enables efficient trajectory and contingency planning in complex multi-agent autonomous driving scenarios involving occlusions., Comment: ECCV 2024. Project page with video and code: www.carff.website
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- 2024
217. CUI@CHI 2024: Building Trust in CUIs-From Design to Deployment
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Desai, Smit, Wei, Christina, Sin, Jaisie, Dubiel, Mateusz, Zargham, Nima, Ahire, Shashank, Porcheron, Martin, Kuzminykh, Anastasia, Lee, Minha, Candello, Heloisa, Fischer, Joel, Munteanu, Cosmin, and Cowan, Benjamin R
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Computer Science - Human-Computer Interaction - Abstract
Conversational user interfaces (CUIs) have become an everyday technology for people the world over, as well as a booming area of research. Advances in voice synthesis and the emergence of chatbots powered by large language models (LLMs), notably ChatGPT, have pushed CUIs to the forefront of human-computer interaction (HCI) research and practice. Now that these technologies enable an elemental level of usability and user experience (UX), we must turn our attention to higher-order human factors: trust and reliance. In this workshop, we aim to bring together a multidisciplinary group of researchers and practitioners invested in the next phase of CUI design. Through keynotes, presentations, and breakout sessions, we will share our knowledge, identify cutting-edge resources, and fortify an international network of CUI scholars. In particular, we will engage with the complexity of trust and reliance as attitudes and behaviours that emerge when people interact with conversational agents.
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- 2024
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218. First (calibration) experiment using proton beam from FRENA at SINP
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Basu, C., Banerjee, K., Ghosh, T. K., Mukherjee, G., Bhattacharya, C., Desai, Shraddha S, Shil, R., Saha, A. K., Meena, J. K., Bar, T., Basak, D., Sahoo, L. K., Saha, S., Marick, C., Das, D., Kujur, M., Roy, S., Basu, S. S., Gond, U., Saha, A., Das, A., Samanta, M., Saha, P., and Karan, S. K.
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Physics - Instrumentation and Detectors ,Nuclear Experiment ,Physics - Accelerator Physics - Abstract
This work presents the first calibration experiment of a 3 MV Tandetron accelerator, FRENA, performed in May 2022. The $^7$Li(p,n) reaction threshold was measured to calibrate the terminal voltage measuring device. A LiF target of thickness 175 $\mu$g/cm$^2$ was used in the experiment. The measured threshold was 1872$\pm$2.7 keV, indicating 6$-$10 keV energy shift.
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- 2024
219. A pilot search for MeV gamma-ray emission from five galaxy clusters using archival COMPTEL data
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Manna, Siddhant and Desai, Shantanu
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Astrophysics - High Energy Astrophysical Phenomena ,Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
We search for MeV gamma-ray emission between 0.75-30 MeV from five galaxy clusters, viz. Coma, VIRGO, SPT-CL J2012-5649, Bullet, and El Gordo, using archival data from the COMPTEL telescope. For this purpose we use three search templates: point source, radial disk and radial Gaussian. We do not detect any signals from Coma, SPT-CL J2012-5649, Bullet and El Gordo clusters with the 95\% c.l. photon energy flux limit $\sim 10^{-10} ~\rm{erg /cm^2/s} $. For VIRGO, we detect a non-zero signal between 0.92 to 1.63 MeV having marginal significance of about $2.5\sigma$, with the observed energy flux $ \sim 10^{-9}~\rm{ergs/cm^2/s}$. However, we do not confirm the previously reported evidence in literature for a gamma-ray line from Coma and VIRGO clusters between 5-7 MeV., Comment: 9 pages, 7 figures. Accepted for publication in JCAP
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- 2024
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220. Citizen Science for IceCube: Name that Neutrino
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Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Blot, S., Bontempo, F., Book, J. Y., Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Busse, R. S., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, C., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Corley, R., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., DuVernois, M. A., Ehrhardt, T., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Lincetto, M., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neumann, M., Niederhausen, H., Nisa, M. U., Noell, A., Novikov, A., Nowicki, S. C., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaufel, M., Schieler, H., Schindler, S., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Tung, C. F., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Warrick, E. H. S., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
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Astrophysics - High Energy Astrophysical Phenomena - Abstract
Name that Neutrino is a citizen science project where volunteers aid in classification of events for the IceCube Neutrino Observatory, an immense particle detector at the geographic South Pole. From March 2023 to September 2023, volunteers did classifications of videos produced from simulated data of both neutrino signal and background interactions. Name that Neutrino obtained more than 128,000 classifications by over 1,800 registered volunteers that were compared to results obtained by a deep neural network machine-learning algorithm. Possible improvements for both Name that Neutrino and the deep neural network are discussed.
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- 2024
221. Comparison of $\Lambda$CDM and $R_h = ct$ with updated galaxy cluster $f_{gas}$ measurements using Bayesian inference
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Panchal, Kunj and Desai, Shantanu
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Astrophysics - Cosmology and Nongalactic Astrophysics ,General Relativity and Quantum Cosmology - Abstract
We use updated gas mass fraction measurements of 44 massive dynamically relaxed galaxy clusters collated in arXiv:2111.09343 to distinguish between the standard $\Lambda$CDM model and $R_h=ct$ universe. For this purpose, we use Bayesian model selection to compare the efficacy of both these cosmological models given the data. The gas mass fraction is modeled using both cosmology-dependent terms and also astrophysical parameters, which account for the variation with cluster mass and redshift. We used two different prior choices for some of the astrophysical parameters. We find a Bayes factors of 50 and 5 for $\Lambda$CDM as compared to $R_h=ct$ for these two prior choices. This implies that $\Lambda$CDM is favored compared to $R_h=ct$ with significance ranging from substantial to very strong., Comment: 8 pages. Accepted for publication in JHEAP
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- 2024
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222. Data-driven compression of electron-phonon interactions
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Luo, Yao, Desai, Dhruv, Chang, Benjamin K., Park, Jinsoo, and Bernardi, Marco
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Condensed Matter - Materials Science - Abstract
First-principles calculations of electron interactions in materials have seen rapid progress in recent years, with electron-phonon (e-ph) interactions being a prime example. However, these techniques use large matrices encoding the interactions on dense momentum grids, which reduces computational efficiency and obscures interpretability. For e-ph interactions, existing interpolation techniques leverage locality in real space, but the high dimensionality of the data remains a bottleneck to balance cost and accuracy. Here we show an efficient way to compress e-ph interactions based on singular value decomposition (SVD), a widely used matrix / image compression technique. Leveraging (un)constrained SVD methods, we accurately predict material properties related to e-ph interactions - including charge mobility, spin relaxation times, band renormalization, and superconducting critical temperature - while using only a small fraction (1-2%) of the interaction data. These findings unveil the hidden low-dimensional nature of e-ph interactions. Furthermore, they accelerate state-of-the-art first-principles e-ph calculations by about two orders of magnitudes without sacrificing accuracy. Our Pareto-optimal parametrization of e-ph interactions can be readily generalized to electron-electron and electron-defect interactions, as well as to other couplings, advancing quantitative studies of condensed matter., Comment: 12 pages, 3 figures
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- 2024
223. Principal eigenvectors and principal ratios in hypergraph Tur\'an problems
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Cooper, Joshua, Desai, Dheer Noal, and Sahay, Anurag
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Mathematics - Combinatorics ,05C65 (Primary), 05C50 (Secondary) - Abstract
For a general class of hypergraph Tur\'an problems with uniformity $r$, we investigate the principal eigenvector for the $p$-spectral radius (in the sense of Keevash--Lenz--Mubayi and Nikiforov) for the extremal graphs, showing in a strong sense that these eigenvectors have close to equal weight on each vertex (equivalently, showing that the principal ratio is close to $1$). We investigate the sharpness of our result; it is likely sharp for the Tur\'an tetrahedron problem. In the course of this latter discussion, we establish a lower bound on the $p$-spectral radius of an arbitrary $r$-graph in terms of the degrees of the graph. This builds on earlier work of Cardoso--Trevisan, Li--Zhou--Bu, Cioab\u{a}--Gregory, and Zhang. The case $1 < p < r$ of our results leads to some subtleties connected to Nikiforov's notion of $k$-tightness, arising from the Perron-Frobenius theory for the $p$-spectral radius. We raise a conjecture about these issues, and provide some preliminary evidence for our conjecture., Comment: 21 pages, 1 figure. Dedicated to the memory of Vladimir Nikiforov
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- 2024
224. The Dark Energy Survey Supernova Program: Cosmological Analysis and Systematic Uncertainties
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Vincenzi, M., Brout, D., Armstrong, P., Popovic, B., Taylor, G., Acevedo, M., Camilleri, R., Chen, R., Davis, T. M., Hinton, S. R., Kelsey, L., Kessler, R., Lee, J., Lidman, C., Möller, A., Qu, H., Sako, M., Sanchez, B., Scolnic, D., Smith, M., Sullivan, M., Wiseman, P., Asorey, J., Bassett, B. A., Carollo, D., Carr, A., Foley, R. J., Frohmaier, C., Galbany, L., Glazebrook, K., Graur, O., Kovacs, E., Kuehn, K., Malik, U., Nichol, R. C., Rose, B., Tucker, B. E., Toy, M., Tucker, D. L., Yuan, F., Abbott, T. M. C., Aguena, M., Alves, O., Andrade-Oliveira, F., Annis, J., Bacon, D., Bechtol, K., Bernstein, G. M., Brooks, D., Burke, D. L., Rosell, A. Carnero, Carretero, J., Castander, F. J., Conselice, C., da Costa, L. N., Pereira, M. E. S., Desai, S., Diehl, H. T., Doel, P., Ferrero, I., Flaugher, B., Friedel, D., Frieman, J., García-Bellido, J., Gatti, M., Giannini, G., Gruen, D., Gruendl, R. A., Hollowood, D. L., Honscheid, K., Huterer, D., James, D. J., Kuropatkin, N., Lahav, O., Lee, S., Lin, H., Marshall, J. L., Mena-Fernández, J., Menanteau, F., Miquel, R., Palmese, A., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Romer, A. K., Roodman, A., Sanchez, E., Cid, D. Sanchez, Schubnell, M., Sevilla-Noarbe, I., Suchyta, E., Swanson, M. E. C., Tarle, G., To, C., Walker, A. R., and Weaverdyck, N.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
We present the full Hubble diagram of photometrically-classified Type Ia supernovae (SNe Ia) from the Dark Energy Survey supernova program (DES-SN). DES-SN discovered more than 20,000 SN candidates and obtained spectroscopic redshifts of 7,000 host galaxies. Based on the light-curve quality, we select 1635 photometrically-identified SNe Ia with spectroscopic redshift 0.10$< z <$1.13, which is the largest sample of supernovae from any single survey and increases the number of known $z>0.5$ supernovae by a factor of five. In a companion paper, we present cosmological results of the DES-SN sample combined with 194 spectroscopically-classified SNe Ia at low redshift as an anchor for cosmological fits. Here we present extensive modeling of this combined sample and validate the entire analysis pipeline used to derive distances. We show that the statistical and systematic uncertainties on cosmological parameters are $\sigma_{\Omega_M,{\rm stat+sys}}^{\Lambda{\rm CDM}}=$0.017 in a flat $\Lambda$CDM model, and $(\sigma_{\Omega_M},\sigma_w)_{\rm stat+sys}^{w{\rm CDM}}=$(0.082, 0.152) in a flat $w$CDM model. Combining the DES SN data with the highly complementary CMB measurements by Planck Collaboration (2020) reduces uncertainties on cosmological parameters by a factor of 4. In all cases, statistical uncertainties dominate over systematics. We show that uncertainties due to photometric classification make up less than 10% of the total systematic uncertainty budget. This result sets the stage for the next generation of SN cosmology surveys such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time., Comment: 39 pages, 19 figures; Submitted to ApJ; companion paper Dark Energy Collaboration et al. on consecutive arxiv number 2401.02929
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- 2024
225. The Dark Energy Survey: Cosmology Results With ~1500 New High-redshift Type Ia Supernovae Using The Full 5-year Dataset
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DES Collaboration, Abbott, T. M. C., Acevedo, M., Aguena, M., Alarcon, A., Allam, S., Alves, O., Amon, A., Andrade-Oliveira, F., Annis, J., Armstrong, P., Asorey, J., Avila, S., Bacon, D., Bassett, B. A., Bechtol, K., Bernardinelli, P. H., Bernstein, G. M., Bertin, E., Blazek, J., Bocquet, S., Brooks, D., Brout, D., Buckley-Geer, E., Burke, D. L., Camacho, H., Camilleri, R., Campos, A., Rosell, A. Carnero, Carollo, D., Carr, A., Carretero, J., Castander, F. J., Cawthon, R., Chang, C., Chen, R., Choi, A., Conselice, C., Costanzi, M., da Costa, L. N., Crocce, M., Davis, T. M., DePoy, D. L., Desai, S., Diehl, H. T., Dixon, M., Dodelson, S., Doel, P., Doux, C., Drlica-Wagner, A., Elvin-Poole, J., Everett, S., Ferrero, I., Ferté, A., Flaugher, B., Foley, R. J., Fosalba, P., Friedel, D., Frieman, J., Frohmaier, C., Galbany, L., García-Bellido, J., Gatti, M., Gaztanaga, E., Giannini, G., Glazebrook, K., Graur, O., Gruen, D., Gruendl, R. A., Gutierrez, G., Hartley, W. G., Herner, K., Hinton, S. R., Hollowood, D. L., Honscheid, K., Huterer, D., Jain, B., James, D. J., Jeffrey, N., Kasai, E., Kelsey, L., Kent, S., Kessler, R., Kim, A. G., Kirshner, R. P., Kovacs, E., Kuehn, K., Lahav, O., Lee, J., Lee, S., Lewis, G. F., Li, T. S., Lidman, C., Lin, H., Malik, U., Marshall, J. L., Martini, P., Mena-Fernández, J., Menanteau, F., Miquel, R., Mohr, J. J., Mould, J., Muir, J., Möller, A., Neilsen, E., Nichol, R. C., Nugent, P., Ogando, R. L. C., Palmese, A., Pan, Y. -C., Paterno, M., Percival, W. J., Pereira, M. E. S., Pieres, A., Malagón, A. A. Plazas, Popovic, B., Porredon, A., Prat, J., Qu, H., Raveri, M., Rodríguez-Monroy, M., Romer, A. K., Roodman, A., Rose, B., Sako, M., Sanchez, E., Cid, D. Sanchez, Schubnell, M., Scolnic, D., Sevilla-Noarbe, I., Shah, P., Smith, J. Allyn., Smith, M., Soares-Santos, M., Suchyta, E., Sullivan, M., Suntzeff, N., Swanson, M. E. C., Sánchez, B. O., Tarle, G., Taylor, G., Thomas, D., To, C., Toy, M., Troxel, M. A., Tucker, B. E., Tucker, D. L., Uddin, S. A., Vincenzi, M., Walker, A. R., Weaverdyck, N., Wechsler, R. H., Weller, J., Wester, W., Wiseman, P., Yamamoto, M., Yuan, F., Zhang, B., and Zhang, Y.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
We present cosmological constraints from the sample of Type Ia supernovae (SN Ia) discovered during the full five years of the Dark Energy Survey (DES) Supernova Program. In contrast to most previous cosmological samples, in which SN are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being a SN Ia, we find 1635 DES SNe in the redshift range $0.10
0.5$ SNe compared to the previous leading compilation of Pantheon+, and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints we combine the DES supernova data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning $0.025 - Published
- 2024
226. SPT Clusters with DES and HST Weak Lensing. II. Cosmological Constraints from the Abundance of Massive Halos
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Bocquet, S., Grandis, S., Bleem, L. E., Klein, M., Mohr, J. J., Schrabback, T., Abbott, T. M. C., Ade, P. A. R., Aguena, M., Alarcon, A., Allam, S., Allen, S. W., Alves, O., Amon, A., Anderson, A. J., Annis, J., Ansarinejad, B., Austermann, J. E., Avila, S., Bacon, D., Bayliss, M., Beall, J. A., Bechtol, K., Becker, M. R., Bender, A. N., Benson, B. A., Bernstein, G. M., Bhargava, S., Bianchini, F., Brodwin, M., Brooks, D., Bryant, L., Campos, A., Canning, R. E. A., Carlstrom, J. E., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Cawthon, R., Chang, C. L., Chang, C., Chaubal, P., Chen, R., Chiang, H. C., Choi, A., Chou, T-L., Citron, R., Moran, C. Corbett, Cordero, J., Costanzi, M., Crawford, T. M., Crites, A. T., da Costa, L. N., Pereira, M. E. S., Davis, C., Davis, T. M., DeRose, J., Desai, S., de Haan, T., Diehl, H. T., Dobbs, M. A., Dodelson, S., Doux, C., Drlica-Wagner, A., Eckert, K., Elvin-Poole, J., Everett, S., Everett, W., Ferrero, I., Ferté, A., Flores, A. M., Frieman, J., Gallicchio, J., García-Bellido, J., Gatti, M., George, E. M., Giannini, G., Gladders, M. D., Gruen, D., Gruendl, R. A., Gupta, N., Gutierrez, G., Halverson, N. W., Harrison, I., Hartley, W. G., Herner, K., Hinton, S. R., Holder, G. P., Hollowood, D. L., Holzapfel, W. L., Honscheid, K., Hrubes, J. D., Huang, N., Hubmayr, J., Huff, E. M., Huterer, D., Irwin, K. D., James, D. J., Jarvis, M., Khullar, G., Kim, K., Knox, L., Kraft, R., Krause, E., Kuehn, K., Kuropatkin, N., Kéruzoré, F., Lahav, O., Lee, A. T., Leget, P. -F., Li, D., Lin, H., Lowitz, A., MacCrann, N., Mahler, G., Mantz, A., Marshall, J. L., McCullough, J., McDonald, M., McMahon, J. J., Mena-Fernández, J., Menanteau, F., Meyer, S. S., Miquel, R., Montgomery, J., Myles, J., Natoli, T., Navarro-Alsina, A., Nibarger, J. P., Noble, G. I., Novosad, V., Ogando, R. L. C., Omori, Y., Padin, S., Pandey, S., Paschos, P., Patil, S., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Prat, J., Pryke, C., Raveri, M., Reichardt, C. L., Roberson, J., Rollins, R. P., Romero, C., Roodman, A., Ruhl, J. E., Rykoff, E. S., Saliwanchik, B. R., Salvati, L., Sánchez, C., Sanchez, E., Cid, D. Sanchez, Saro, A., Schaffer, K. K., Secco, L. F., Sevilla-Noarbe, I., Sharon, K., Sheldon, E., Shin, T., Sievers, C., Smecher, G., Smith, M., Somboonpanyakul, T., Sommer, M., Stalder, B., Stark, A. A., Stephen, J., Strazzullo, V., Suchyta, E., Tarle, G., To, C., Troxel, M. A., Tucker, C., Tutusaus, I., Varga, T. N., Veach, T., Vieira, J. D., Vikhlinin, A., von der Linden, A., Wang, G., Weaverdyck, N., Weller, J., Whitehorn, N., Wu, W. L. K., Yanny, B., Yefremenko, V., Yin, B., Young, M., Zebrowski, J. A., Zhang, Y., Zohren, H., and Zuntz, J.
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Astrophysics - Cosmology and Nongalactic Astrophysics - Abstract
We present cosmological constraints from the abundance of galaxy clusters selected via the thermal Sunyaev-Zel'dovich (SZ) effect in South Pole Telescope (SPT) data with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). The cluster sample is constructed from the combined SPT-SZ, SPTpol ECS, and SPTpol 500d surveys, and comprises 1,005 confirmed clusters in the redshift range $0.25-1.78$ over a total sky area of 5,200 deg$^2$. We use DES Year 3 weak-lensing data for 688 clusters with redshifts $z<0.95$ and HST weak-lensing data for 39 clusters with $0.6
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- 2024
227. Euclid preparation: XLVIII. The pre-launch Science Ground Segment simulation framework
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Euclid Collaboration, Serrano, S., Hudelot, P., Seidel, G., Pollack, J. E., Jullo, E., Torradeflot, F., Benielli, D., Fahed, R., Auphan, T., Carretero, J., Aussel, H., Casenove, P., Castander, F. J., Davies, J. E., Fourmanoit, N., Huot, S., Kara, A., Keihänen, E., Kermiche, S., Okumura, K., Zoubian, J., Ealet, A., Boucaud, A., Bretonnière, H., Casas, R., Clément, B., Duncan, C. A. J., George, K., Kiiveri, K., Kurki-Suonio, H., Kümmel, M., Laugier, D., Mainetti, G., Mohr, J. J., Montoro, A., Neissner, C., Rosset, C., Schirmer, M., Tallada-Crespí, P., Tonello, N., Venhola, A., Verderi, A., Zacchei, A., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Azzollini, R., Baccigalupi, C., Baldi, M., Bardelli, S., Basset, A., Battaglia, P., Bernardeau, F., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Candini, G. P., Capobianco, V., Carbone, C., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Cledassou, R., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Crocce, M., Cropper, M., Da Silva, A., Degaudenzi, H., De Lucia, G., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Granett, B. R., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoar, J., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Joachimi, B., Kiessling, A., Kitching, T., Kohley, R., Kunz, M., Boulc'h, Q. Le, Liebing, P., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marcin, S., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Morris, P., Moscardini, L., Munari, E., Nakajima, R., Niemi, S. -M., Nutma, T., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Rusholme, B., Saglia, R., Sakr, Z., Sánchez, A. G., Sapone, D., Sartoris, B., Sauvage, M., Schneider, P., Schrabback, T., Scodeggio, M., Secroun, A., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Starck, J. -L., Steinwagner, J., Taylor, A. N, Teplitz, H., Tereno, I., Toledo-Moreo, R., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Biviano, A., Bozzo, E., Di Ferdinando, D., Farinelli, R., Graciá-Carpio, J., Mauri, N., Scottez, V., Tenti, M., Akrami, Y., Allevato, V., Ballardini, M., Blanchard, A., Borgani, S., Borlaff, A. S., Bruton, S., Burigana, C., Cappi, A., Carvalho, C. S., Castro, T., Cañas-Herrera, G., Chambers, K. C., Cooray, A. R., Coupon, J., Davini, S., de la Torre, S., Desai, S., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., Garcia-Bellido, J., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Gregorio, A., Hildebrandt, H., Huertas-Company, M., Ilbert, O., Muñoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Nucita, A. A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Reimberg, P., Schneider, A., Sereno, M., Shulevski, A., Simon, P., Mancini, A. Spurio, Stadel, J., Tewes, M., Teyssier, R., Toft, S., Tucci, M., Valiviita, J., Viel, M., and Zinchenko, I. A.
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Astrophysics - Cosmology and Nongalactic Astrophysics ,Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
The European Space Agency's Euclid mission is one of the upcoming generation of large-scale cosmology surveys, which will map the large-scale structure in the Universe with unprecedented precision. The development and validation of the SGS pipeline requires state-of-the-art simulations with a high level of complexity and accuracy that include subtle instrumental features not accounted for previously as well as faster algorithms for the large-scale production of the expected Euclid data products. In this paper, we present the Euclid SGS simulation framework as applied in a large-scale end-to-end simulation exercise named Science Challenge 8. Our simulation pipeline enables the swift production of detailed image simulations for the construction and validation of the Euclid mission during its qualification phase and will serve as a reference throughout operations. Our end-to-end simulation framework starts with the production of a large cosmological N-body & mock galaxy catalogue simulation. We perform a selection of galaxies down to I_E=26 and 28 mag, respectively, for a Euclid Wide Survey spanning 165 deg^2 and a 1 deg^2 Euclid Deep Survey. We build realistic stellar density catalogues containing Milky Way-like stars down to H<26. Using the latest instrumental models for both the Euclid instruments and spacecraft as well as Euclid-like observing sequences, we emulate with high fidelity Euclid satellite imaging throughout the mission's lifetime. We present the SC8 data set consisting of overlapping visible and near-infrared Euclid Wide Survey and Euclid Deep Survey imaging and low-resolution spectroscopy along with ground-based. This extensive data set enables end-to-end testing of the entire ground segment data reduction and science analysis pipeline as well as the Euclid mission infrastructure, paving the way to future scientific and technical developments and enhancements., Comment: 39 pages, 25 figures, A&A submitted
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- 2024
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228. A test of MOND and Emergent Gravity with SMACS J0723.3-7327 using eROSITA observations
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Govind, Ambica and Desai, Shantanu
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Astrophysics - Cosmology and Nongalactic Astrophysics ,General Relativity and Quantum Cosmology - Abstract
We implement a test of MOND and Verlinde's Emergent Gravity using the galaxy cluster SMACS J0723-7327, which has been recently imaged using the eROSITA X-ray telescope as well as with JWST. We test MOND using two independent methods. The first method involves comparing the dynamical MOND mass and baryonic mass, while the second method entails a comparison of the MOND-estimated temperature with the observed temperature. We then compare the unseen mass predicted by Emergent Gravity with the estimated dark matter mass. We find that MOND shows a mass discrepancy in the central regions at high significance levels. The observed temperature profile is in marginal disagreement with that in the MOND paradigm. However, the Emergent Gravity Theory agrees in accurately accounting for the dynamical mass in the inner regions within $1\sigma$. Our results are qualitatively consistent with the earlier tests on other clusters., Comment: 17 pages, 3 figures. Accepted for publication in JCAP
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- 2024
- Full Text
- View/download PDF
229. The effects of Facebook and Instagram on the 2020 election: A deactivation experiment.
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Allcott, Hunt, Gentzkow, Matthew, Mason, Winter, Wilkins, Arjun, Barberá, Pablo, Brown, Taylor, Cisneros, Juan, Crespo-Tenorio, Adriana, Dimmery, Drew, Freelon, Deen, González-Bailón, Sandra, Guess, Andrew, Kim, Young, Lazer, David, Malhotra, Neil, Moehler, Devra, Nair-Desai, Sameer, Nait El Barj, Houda, Nyhan, Brendan, Paixao de Queiroz, Ana, Pan, Jennifer, Settle, Jaime, Thorson, Emily, Tromble, Rebekah, Velasco Rivera, Carlos, Wittenbrink, Benjamin, Zahedian, Saam, Franco, Annie, Kiewiet de Jonge, Chad, Stroud, Natalie, Tucker, Joshua, and Wojcieszak, Magdalena
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Facebook ,Instagram ,election ,polarization ,social media ,Politics ,Humans ,Social Media ,United States ,Attitude ,Male ,Female - Abstract
We study the effect of Facebook and Instagram access on political beliefs, attitudes, and behavior by randomizing a subset of 19,857 Facebook users and 15,585 Instagram users to deactivate their accounts for 6 wk before the 2020 U.S. election. We report four key findings. First, both Facebook and Instagram deactivation reduced an index of political participation (driven mainly by reduced participation online). Second, Facebook deactivation had no significant effect on an index of knowledge, but secondary analyses suggest that it reduced knowledge of general news while possibly also decreasing belief in misinformation circulating online. Third, Facebook deactivation may have reduced self-reported net votes for Trump, though this effect does not meet our preregistered significance threshold. Finally, the effects of both Facebook and Instagram deactivation on affective and issue polarization, perceived legitimacy of the election, candidate favorability, and voter turnout were all precisely estimated and close to zero.
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- 2024
230. Determinants of mosaic chromosomal alteration fitness.
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Pershad, Yash, Mack, Taralynn, Poisner, Hannah, Jakubek, Yasminka, Stilp, Adrienne, Mitchell, Braxton, Lewis, Joshua, Boerwinkle, Eric, Loos, Ruth, Chami, Nathalie, Wang, Zhe, Barnes, Kathleen, Pankratz, Nathan, Fornage, Myriam, Redline, Susan, Psaty, Bruce, Bis, Joshua, Shojaie, Ali, Silverman, Edwin, Cho, Michael, Yun, Jeong, DeMeo, Dawn, Levy, Daniel, Johnson, Andrew, Mathias, Rasika, Taub, Margaret, Arnett, Donna, North, Kari, Raffield, Laura, Carson, April, Doyle, Margaret, Rich, Stephen, Guo, Xiuqing, Cox, Nancy, Roden, Dan, Franceschini, Nora, Desai, Pinkal, Reiner, Alex, Auer, Paul, Scheet, Paul, Jaiswal, Siddhartha, Weinstock, Joshua, Bick, Alexander, and Rotter, Jerome
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Humans ,Mosaicism ,Chromosome Aberrations ,Clonal Hematopoiesis ,Male ,Female ,Genome-Wide Association Study ,Janus Kinase 2 ,Telomerase ,Loss of Heterozygosity ,Cross-Sectional Studies ,Mutation ,Middle Aged ,Hematopoietic Stem Cells ,Polymorphism ,Single Nucleotide ,Aged - Abstract
Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate as PACER scores for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our mCA fitness estimates, derived by aggregating per-individual PACER scores, were correlated (R2 = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using population-level distributions of clonal fraction. Among individuals with JAK2 V617F clonal hematopoiesis of indeterminate potential or mCAs affecting the JAK2 gene on chromosome 9, PACER score was strongly correlated with erythrocyte count. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified a TCL1A locus variant associated with mCA clonal expansion rate, with suggestive variants in NRIP1 and TERT.
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- 2024
231. Investigating Fire–Atmosphere Interaction in a Forest Canopy Using Wavelets
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Desai, Ajinkya, Guilloteau, Clément, Heilman, Warren E, Charney, Joseph J, Skowronski, Nicholas S, Clark, Kenneth L, Gallagher, Michael R, Foufoula-Georgiou, Efi, and Banerjee, Tirtha
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Earth Sciences ,Atmospheric Sciences ,Heading surface fire ,Time-frequency plane ,Ramp-cliff structures ,Cross-wavelet coherence ,Heat/momentum fluxes ,Meteorology & Atmospheric Sciences ,Atmospheric sciences - Abstract
Wildland fire–atmosphere interaction generates complex turbulence patterns, organized across multiple scales, which inform fire-spread behaviour, firebrand transport, and smoke dispersion. Here, we utilize wavelet-based techniques to explore the characteristic temporal scales associated with coherent patterns in the measured temperature and the turbulent fluxes during a prescribed wind-driven (heading) surface fire beneath a forest canopy. We use temperature and velocity measurements from tower-mounted sonic anemometers at multiple heights. Patterns in the wavelet-based energy density of the measured temperature plotted on a time–frequency plane indicate the presence of fire-modulated ramp–cliff structures in the low-to-mid-frequency band (0.01–0.33 Hz), with mean ramp durations approximately 20% shorter and ramp slopes that are an order of magnitude higher compared to no-fire conditions. We then investigate heat- and momentum-flux events near the canopy top through a cross-wavelet coherence analysis. Briefly before the fire-front arrives at the tower base, momentum-flux events are relatively suppressed and turbulent fluxes are chiefly thermally-driven near the canopy top, owing to the tilting of the flame in the direction of the wind. Fire-induced heat-flux events comprising warm updrafts and cool downdrafts are coherent down to periods of a second, whereas ambient heat-flux events operate mainly at higher periods (above 17 s). Later, when the strongest temperature fluctuations are recorded near the surface, fire-induced heat-flux events occur intermittently at shorter scales and cool sweeps start being seen for periods ranging from 8 to 35 s near the canopy top, suggesting a diminishing influence of the flame and increasing background atmospheric variability thereat. The improved understanding of the characteristic time scales associated with fire-induced turbulence features, as the fire-front evolves, will help develop more reliable fire behaviour and scalar transport models.
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- 2024
232. Adjusting Incidence Estimates with Laboratory Test Performances: A Pragmatic Maximum Likelihood Estimation-Based Approach.
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Weng, Yingjie, Tian, Lu, Boothroyd, Derek, Lee, Justin, Zhang, Kenny, Lu, Di, Lindan, Christina, Bollyky, Jenna, Huang, Beatrice, Rutherford, George, Maldonado, Yvonne, and Desai, Manisha
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Humans ,Likelihood Functions ,Incidence ,Longitudinal Studies ,Pandemics ,Computer Simulation ,COVID-19 - Abstract
Understanding the incidence of disease is often crucial for public policy decision-making, as observed during the COVID-19 pandemic. Estimating incidence is challenging, however, when the definition of incidence relies on tests that imperfectly measure disease, as in the case when assays with variable performance are used to detect the SARS-CoV-2 virus. To our knowledge, there are no pragmatic methods to address the bias introduced by the performance of labs in testing for the virus. In the setting of a longitudinal study, we developed a maximum likelihood estimation-based approach to estimate laboratory performance-adjusted incidence using the expectation-maximization algorithm. We constructed confidence intervals (CIs) using both bootstrapped-based and large-sample interval estimator approaches. We evaluated our methods through extensive simulation and applied them to a real-world study (TrackCOVID), where the primary goal was to determine the incidence of and risk factors for SARS-CoV-2 infection in the San Francisco Bay Area from July 2020 to March 2021. Our simulations demonstrated that our method converged rapidly with accurate estimates under a variety of scenarios. Bootstrapped-based CIs were comparable to the large-sample estimator CIs with a reasonable number of incident cases, shown via a simulation scenario based on the real TrackCOVID study. In more extreme simulated scenarios, the coverage of large-sample interval estimation outperformed the bootstrapped-based approach. Results from the application to the TrackCOVID study suggested that assuming perfect laboratory test performance can lead to an inaccurate inference of the incidence. Our flexible, pragmatic method can be extended to a variety of disease and study settings.
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- 2024
233. Search for 10–1000 GeV Neutrinos from Gamma-Ray Bursts with IceCube
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Abbasi, R, Ackermann, M, Adams, J, Agarwalla, SK, Aguilar, JA, Ahlers, M, Alameddine, JM, Amin, NM, Andeen, K, Anton, G, Argüelles, C, Ashida, Y, Athanasiadou, S, Ausborm, L, Axani, SN, Bai, X, V., A Balagopal, Baricevic, M, Barwick, SW, Basu, V, Bay, R, Beatty, JJ, Tjus, J Becker, Beise, J, Bellenghi, C, Benning, C, BenZvi, S, Berley, D, Bernardini, E, Besson, DZ, Blaufuss, E, Blot, S, Bontempo, F, Book, JY, Meneguolo, C Boscolo, Böser, S, Botner, O, Böttcher, J, Braun, J, Brinson, B, Brostean-Kaiser, J, Brusa, L, Burley, RT, Busse, RS, Butterfield, D, Campana, MA, Carloni, K, Carnie-Bronca, EG, Chattopadhyay, S, Chau, N, Chen, C, Chen, Z, Chirkin, D, Choi, S, Clark, BA, Coleman, A, Collin, GH, Connolly, A, Conrad, JM, Coppin, P, Correa, P, Cowen, DF, Dave, P, De Clercq, C, DeLaunay, JJ, Delgado, D, Deng, S, Deoskar, K, Desai, A, Desiati, P, de Vries, KD, de Wasseige, G, DeYoung, T, Diaz, A, Díaz-Vélez, JC, Dittmer, M, Domi, A, Dujmovic, H, DuVernois, MA, Ehrhardt, T, Eimer, A, Eller, P, Ellinger, E, Mentawi, S El, Elsässer, D, Engel, R, Erpenbeck, H, Evans, J, Evenson, PA, Fan, KL, Fang, K, Farrag, K, Fazely, AR, Fedynitch, A, Feigl, N, Fiedlschuster, S, Finley, C, Fischer, L, Fox, D, and Franckowiak, A
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Nuclear and Plasma Physics ,Particle and High Energy Physics ,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
We present the results of a search for 10-1000 GeV neutrinos from 2268 gamma-ray bursts (GRBs) over 8 yr of IceCube-DeepCore data. This work probes burst physics below the photosphere where electromagnetic radiation cannot escape. Neutrinos of tens of giga electronvolts are predicted in sub-photospheric collision of free-streaming neutrons with bulk-jet protons. In a first analysis, we searched for the most significant neutrino-GRB coincidence using six overlapping time windows centered on the prompt phase of each GRB. In a second analysis, we conducted a search for a group of GRBs, each individually too weak to be detectable, but potentially significant when combined. No evidence of neutrino emission is found for either analysis. The most significant neutrino coincidence is for Fermi-GBM GRB bn 140807500, with a p-value of 0.097 corrected for all trials. The binomial test used to search for a group of GRBs had a p-value of 0.65 after all trial corrections. The binomial test found a group consisting only of GRB bn 140807500 and no additional GRBs. The neutrino limits of this work complement those obtained by IceCube at tera electronvolt to peta electronvolt energies. We compare our findings for the large set of GRBs as well as GRB 221009A to the sub-photospheric neutron-proton collision model and find that GRB 221009A provides the most constraining limit on baryon loading. For a jet Lorentz factor of 300 (800), the baryon loading on GRB 221009A is lower than 3.85 (2.13) at a 90% confidence level.
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- 2024
234. Propofol Induction is Associated with Changes in Diastolic Function
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Hamilton, Zachary, Desai, Shalin, McCloskey, Lynh, and Fleming, Neal
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Diastolic dysfunction associated with peri- and post-operative complications. Propofol and cardiovascular depression. Some studies report that propofol worsens diastolic function, others report improvement.
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- 2024
235. Pediatric neuromodulation for drug-resistant epilepsy: Survey of current practices, techniques, and outcomes across US epilepsy centers.
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Joshi, Charuta, Karakas, Cemal, Eschbach, Krista, Samanta, Debopam, Desai, Virendra, Singh, Rani, McGoldrick, Patricia, Wolf, Steven, Abel, Taylor, Novotny, Edward, Oluigbo, Chima, Reddy, Shilpa, Alexander, Allyson, Price, Angela, Reeders, Puck, Mcnamara, Nancy, Romanowski, Erin, Mutchnick, Ian, Ostendorf, Adam, Shaikhouni, Ammar, Knox, Andrew, Aungaroon, Gewalin, Olaya, Joffre, Muh, Carrie, and Auguste, Kurtis
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DBS ,RNS ,neuromodulation ,outcomes ,practices ,Humans ,Child ,Child ,Preschool ,Deep Brain Stimulation ,Epilepsy ,Drug Resistant Epilepsy ,Seizures ,Intralaminar Thalamic Nuclei - Abstract
Neuromodulation via Responsive Neurostimulation (RNS) or Deep Brain Stimulation (DBS) is an emerging treatment strategy for pediatric drug-resistant epilepsy (DRE). Knowledge gaps exist in patient selection, surgical technique, and perioperative care. Here, we use an expert survey to clarify practices. Thirty-two members of the Pediatric Epilepsy Research Consortium were surveyed using REDCap. Respondents were from 17 pediatric epilepsy centers (missing data in one): Four centers implant RNS only while 13 implant both RNS and DBS. Thirteen RNS programs commenced in or before 2020, and 10 of 12 DBS programs began thereafter. The busiest six centers implant 6-10 new RNS devices per year; all DBS programs implant 50%) was reported by 81% (13/16) of centers. RNS and DBS are rapidly evolving treatment modalities for safe and effective treatment of pediatric DRE. There is increasing interest in multicenter collaboration to gain knowledge and facilitate dialogue. PLAIN LANGUAGE SUMMARY: We surveyed 32 pediatric epilepsy centers in USA to highlight current practices of intracranial neuromodulation. Of the 17 that replied, we found that most centers are implanting thalamic targets in pediatric drug-resistant epilepsy using the RNS device. DBS device is starting to be used in pediatric epilepsy, especially after 2020. Different strategies for target identification are enumerated. This study serves as a starting point for future collaborative research.
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- 2024
236. Association of antibiotic exposure with residual cancer burden in HER2-negative early stage breast cancer.
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Kulkarni, Amit, Jain, Aditya, Jewett, Patricia, Desai, Nidhi, Yee, Douglas, Blaes, Anne, Van t veer, Laura, and Hirst, Gillian
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Antibiotic exposure during immunotherapy (IO) has been shown to negatively affect clinical outcomes in various cancer types. The aim of this study was to evaluate whether antibiotic exposure in patients with high-risk early-stage HER2-negative breast cancer (BC) undergoing treatment with neoadjuvant pembrolizumab impacted residual cancer burden (RCB) and pathologic complete response (pCR) in the pembrolizumab-4 arm of the ISPY-2 clinical trial. Patients received pembrolizumab for four cycles concurrently with weekly paclitaxel for 12 weeks, followed by four cycles of doxorubicin plus cyclophosphamide every 2 or 3 weeks. Patients who received at least one dose of systemic antibiotics concurrently at the time of immunotherapy (IO) were included in the antibiotic exposure group (ATB+). All other participants were included in the control group (ATB-). RCB index and PCR rates were compared between the ATB+ and ATB- groups using t-tests and Chi-squared tests, and linear and logistic regression models, respectively. Sixty-six patients were included in the analysis. 18/66 (27%) patients were in the ATB+ group. Antibiotic use during IO was associated with a higher mean RCB index (1.80 ± 1.43 versus 1.08 ± 1.41) and a lower pCR rate (27.8% versus 52.1%). The association between antibiotic use and the RCB index remained significant in multivariable linear regression analysis (RCB index-coefficient 0.86, 95% CI 0.20-1.53, P = 0.01). Our findings suggest that concurrent antibiotic exposure during neoadjuvant pembrolizumab in HER2-negative early-stage BC is associated with higher RCB. Further validation in larger cohorts is needed to confirm these findings.
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- 2024
237. Broselow Tape vs Provider Weight Estimation in Pediatric ED Patients
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Zummer, Jaryd, Desai, Sameer, Shercliffe, Rachel, and Reed, Madison
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- 2024
238. Emergency Department Utilization Measured Through Bounce Back Rate is Significantly Higher in Homeless Patients
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Sairajeev, Sasha and Desai, Sameer
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- 2024
239. Search for Continuous and Transient Neutrino Emission Associated with IceCube’s Highest-energy Tracks: An 11 yr Analysis
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Abbasi, R, Ackermann, M, Adams, J, Agarwalla, SK, Aguilar, JA, Ahlers, M, Alameddine, JM, Amin, NM, Andeen, K, Anton, G, Argüelles, C, Ashida, Y, Athanasiadou, S, Axani, SN, Bai, X, V., A Balagopal, Baricevic, M, Barwick, SW, Basu, V, Bay, R, Beatty, JJ, Tjus, J Becker, Beise, J, Bellenghi, C, Benning, C, BenZvi, S, Berley, D, Bernardini, E, Besson, DZ, Blaufuss, E, Blot, S, Bontempo, F, Book, JY, Meneguolo, C Boscolo, Böser, S, Botner, O, Böttcher, J, Bourbeau, E, Braun, J, Brinson, B, Brostean-Kaiser, J, Burley, RT, Busse, RS, Butterfield, D, Campana, MA, Carloni, K, Carnie-Bronca, EG, Chattopadhyay, S, Chau, N, Chen, C, Chen, Z, Chirkin, D, Choi, S, Clark, BA, Coenders, S, Coleman, A, Collin, GH, Connolly, A, Conrad, JM, Coppin, P, Correa, P, Cowen, DF, Dave, P, De Clercq, C, DeLaunay, JJ, Delgado, D, Deng, S, Deoskar, K, Desai, A, Desiati, P, de Vries, KD, de Wasseige, G, DeYoung, T, Diaz, A, Díaz-Vélez, JC, Dittmer, M, Domi, A, Dujmovic, H, DuVernois, MA, Ehrhardt, T, Eimer, A, Eller, P, Ellinger, E, Mentawi, S El, Elsässer, D, Engel, R, Erpenbeck, H, Evans, J, Evenson, PA, Fan, KL, Fang, K, Farrag, K, Fazely, AR, Fedynitch, A, Feigl, N, Fiedlschuster, S, Finley, C, Fischer, L, Fox, D, and Franckowiak, A
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Nuclear and Plasma Physics ,Particle and High Energy Physics ,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
IceCube alert events are neutrinos with a moderate-to-high probability of having astrophysical origin. In this study, we analyze 11 yr of IceCube data and investigate 122 alert events and a selection of high-energy tracks detected between 2009 and the end of 2021. This high-energy event selection (alert events + high-energy tracks) has an average probability of ≥0.5 of being of astrophysical origin. We search for additional continuous and transient neutrino emission within the high-energy events’ error regions. We find no evidence for significant continuous neutrino emission from any of the alert event directions. The only locally significant neutrino emission is the transient emission associated with the blazar TXS 0506+056, with a local significance of 3σ, which confirms previous IceCube studies. When correcting for 122 test positions, the global p-value is 0.156 and compatible with the background hypothesis. We constrain the total continuous flux emitted from all 122 test positions at 100 TeV to be below 1.2 × 10−15 (TeV cm2 s)−1 at 90% confidence assuming an E −2 spectrum. This corresponds to 4.5% of IceCube’s astrophysical diffuse flux. Overall, we find no indication that alert events in general are linked to lower-energetic continuous or transient neutrino emission.
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- 2024
240. Investigating trends in interest for benign prostatic hyperplasia surgery options using Google Trends.
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Daniels, James, Patel, Devin, Galvan, Gloria, Friedrich, Nadine, Akhavein, Arash, Daskivich, Timothy, Josephson, David, Desai, Premal, De Nunzio, Cosimo, Freedland, Stephen, and Das, Sanjay
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Male ,Humans ,Prostatic Hyperplasia ,Search Engine ,Prostatic Neoplasms ,Transurethral Resection of Prostate ,Lower Urinary Tract Symptoms - Abstract
Understanding patient interest among surgical options is challenging. We used Google Trends to analyze interest in benign prostatic hyperplasia (BPH) surgeries recommended for prostate volumes
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- 2024
241. Microencapsulated Benzoyl Peroxide for Rosacea in Context: A Review of the Current Treatment Landscape.
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Desai, Seemal, Baldwin, Hilary, Del Rosso, James, Bhatia, Neal, Harper, Julie, York, Jean, Gold, Linda, and Gallo, Richard
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Adult ,Humans ,Benzoyl Peroxide ,Quality of Life ,Dermatologic Agents ,Rosacea ,Metronidazole - Abstract
Rosacea, a chronic skin condition affecting millions of people in the USA, leads to significant social and professional stigmatization. Effective management strategies are crucial to alleviate symptoms and improve patients quality of life. Encapsulated benzoyl peroxide 5% (E-BPO 5%) is a newly FDA-approved topical treatment for rosacea that shows promise in enhancing therapeutic response and minimizing skin irritation. This review aims to assess the role of recently FDA approved E-BPO 5% in the current treatment landscape for rosacea management, as it is not yet included in clinical guidelines that predominantly rely on older approved therapies. The review focuses on randomized controlled trials conducted in English-speaking adults. It evaluates the efficacy, safety, and tolerability of various US Food and Drug Administration (FDA)-approved agents used for rosacea treatment, including E-BPO cream, metronidazole gel, azelaic acid gel and foam, ivermectin cream, minocycline foam, oral doxycycline, brimonidine gel, and oxymetazoline HCl cream. Existing therapies have been effective in reducing papulopustular lesions and erythema associated with rosacea for many years. E-BPO 5% offers a promising addition to the treatment options due to its microencapsulation technology, which prolongs drug delivery time and aims to improve therapeutic response while minimizing skin irritation. Further research is necessary to determine the exact role of E-BPO 5% in the therapeutic landscape for rosacea. However, based on available evidence, E-BPO 5% shows potential as a valuable treatment option for managing inflammatory lesions of rosacea, and it may offer benefits to patients including: rapid onset of action, demonstrated efficacy by Week 2, excellent tolerability, and sustained long-term results for up to 52 weeks of treatment.
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- 2024
242. Wait Time Advantage for Transplant Candidates With HIV Who Accept Kidneys From Donors With HIV Under the HOPE Act.
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Motter, Jennifer, Hussain, Sarah, Brown, Diane, Florman, Sander, Rana, Meenakshi, Friedman-Moraco, Rachel, Gilbert, Alexander, Stock, Peter, Mehta, Shikha, Mehta, Sapna, Stosor, Valentina, Elias, Nahel, Pereira, Marcus, Haidar, Ghady, Malinis, Maricar, Morris, Michele, Hand, Jonathan, Aslam, Saima, Schaenman, Joanna, Baddley, John, Small, Catherine, Wojciechowski, David, Santos, Carlos, Blumberg, Emily, Odim, Jonah, Apewokin, Senu, Giorgakis, Emmanouil, Bowring, Mary, Werbel, William, Desai, Niraj, Tobian, Aaron, Segev, Dorry, Massie, Allan, and Durand, Christine
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Humans ,Male ,Waiting Lists ,Kidney ,Tissue Donors ,Kidney Transplantation ,Living Donors ,Transplant Recipients ,HIV Infections - Abstract
BACKGROUND: Kidney transplant (KT) candidates with HIV face higher mortality on the waitlist compared with candidates without HIV. Because the HIV Organ Policy Equity (HOPE) Act has expanded the donor pool to allow donors with HIV (D + ), it is crucial to understand whether this has impacted transplant rates for this population. METHODS: Using a linkage between the HOPE in Action trial (NCT03500315) and Scientific Registry of Transplant Recipients, we identified 324 candidates listed for D + kidneys (HOPE) compared with 46 025 candidates not listed for D + kidneys (non-HOPE) at the same centers between April 26, 2018, and May 24, 2022. We characterized KT rate, KT type (D + , false-positive [FP; donor with false-positive HIV testing], D - [donor without HIV], living donor [LD]) and quantified the association between HOPE enrollment and KT rate using multivariable Cox regression with center-level clustering; HOPE was a time-varying exposure. RESULTS: HOPE candidates were more likely male individuals (79% versus 62%), Black (73% versus 35%), and publicly insured (71% versus 52%; P
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- 2024
243. Carve3D: Improving Multi-view Reconstruction Consistency for Diffusion Models with RL Finetuning
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Xie, Desai, Li, Jiahao, Tan, Hao, Sun, Xin, Shu, Zhixin, Zhou, Yi, Bi, Sai, Pirk, Sören, and Kaufman, Arie E.
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning - Abstract
Multi-view diffusion models, obtained by applying Supervised Finetuning (SFT) to text-to-image diffusion models, have driven recent breakthroughs in text-to-3D research. However, due to the limited size and quality of existing 3D datasets, they still suffer from multi-view inconsistencies and Neural Radiance Field (NeRF) reconstruction artifacts. We argue that multi-view diffusion models can benefit from further Reinforcement Learning Finetuning (RLFT), which allows models to learn from the data generated by themselves and improve beyond their dataset limitations during SFT. To this end, we introduce Carve3D, an improved RLFT algorithm coupled with a novel Multi-view Reconstruction Consistency (MRC) metric, to enhance the consistency of multi-view diffusion models. To measure the MRC metric on a set of multi-view images, we compare them with their corresponding NeRF renderings at the same camera viewpoints. The resulting model, which we denote as Carve3DM, demonstrates superior multi-view consistency and NeRF reconstruction quality than existing models. Our results suggest that pairing SFT with Carve3D's RLFT is essential for developing multi-view-consistent diffusion models, mirroring the standard Large Language Model (LLM) alignment pipeline. Our code, training and testing data, and video results are available at: https://desaixie.github.io/carve-3d., Comment: 22 pages, 16 figures. Our code, training and testing data, and video results are available at: https://desaixie.github.io/carve-3d. This paper has been accepted to CVPR 2024. v2: incorporated changes from the CVPR 2024 camera-ready version
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- 2023
244. SENSEI: First Direct-Detection Results on sub-GeV Dark Matter from SENSEI at SNOLAB
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SENSEI Collaboration, Adari, Prakruth, Bloch, Itay M., Botti, Ana M., Cababie, Mariano, Cancelo, Gustavo, Cervantes-Vergara, Brenda A., Crisler, Michael, Daal, Miguel, Desai, Ansh, Drlica-Wagner, Alex, Essig, Rouven, Estrada, Juan, Etzion, Erez, Moroni, Guillermo Fernandez, Holland, Stephen E., Kehat, Yonatan, Korn, Yaron, Lawson, Ian, Luoma, Steffon, Orly, Aviv, Perez, Santiago E., Rodrigues, Dario, Saffold, Nathan A., Scorza, Silvia, Singal, Aman, Sofo-Haro, Miguel, Stefanazzi, Leandro, Stifter, Kelly, Tiffenberg, Javier, Uemura, Sho, Villalpando, Edgar Marrufo, Volansky, Tomer, Wu, Yikai, Yu, Tien-Tien, Emken, Timon, and Xu, Hailin
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Astrophysics - Cosmology and Nongalactic Astrophysics ,High Energy Physics - Experiment ,High Energy Physics - Phenomenology ,Physics - Instrumentation and Detectors - Abstract
We present the first results from a dark matter search using six Skipper-CCDs in the SENSEI detector operating at SNOLAB. With an exposure of 534.9 gram-days from well-performing sensors, we select events containing 2 to 10 electron-hole pairs. After aggressively masking images to remove backgrounds, we observe 55 two-electron events, 4 three-electron events, and no events containing 4 to 10 electrons. The two-electron events are consistent with pileup from one-electron events. Among the 4 three-electron events, 2 appear in pixels that are likely impacted by detector defects, although not strongly enough to trigger our "hot-pixel" mask. We use these data to set world-leading constraints on sub-GeV dark matter interacting with electrons and nuclei., Comment: 5 pages, 2 figures, + Supplemental Materials (5 pages, 5 figures) + References
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- 2023
245. Dark Energy Survey Deep Field photometric redshift performance and training incompleteness assessment
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Cipriano, L. Toribio San, De Vicente, J., Sevilla-Noarbe, I., Hartley, W. G., Myles, J., Amon, A., Bernstein, G. M., Choi, A., Eckert, K., Gruendl, R. A., Harrison, I., Sheldon, E., Yanny, B., Aguena, M., Allam, S. S., Alves, O., Bacon, D., Brooks, D., Campos, A., Rosell, A. Carnero, Carretero, J., Castander, F. J., Conselice, C., da Costa, L. N., Pereira, M. E. S., Davis, T. M., Desai, S., Diehl, H. T., Doel, P., Ferrero, I., Frieman, J., García-Bellido, J., Gaztañaga, E., Giannini, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lee, S., Lidman, C., Marshall, J. L., Mena-Fernández, J., Menanteau, F., Miquel, R., Palmese, A., Pieres, A., Malagón, A. A. Plazas, Roodman, A., Sanchez, E., Smith, M., Soares-Santos, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Vincenzi, M., Weaverdyck, N., and Wiseman, P.
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Astrophysics - Cosmology and Nongalactic Astrophysics ,Astrophysics - Astrophysics of Galaxies - Abstract
Context. The determination of accurate photometric redshifts (photo-zs) in large imaging galaxy surveys is key for cosmological studies. One of the most common approaches are machine learning techniques. These methods require a spectroscopic or reference sample to train the algorithms. Attention has to be paid to the quality and properties of these samples since they are key factors in the estimation of reliable photo-zs. Aims. The goal of this work is to calculate the photo-zs for the Y3 DES Deep Fields catalogue using the DNF machine learning algorithm. Moreover, we want to develop techniques to assess the incompleteness of the training sample and metrics to study how incompleteness affects the quality of photometric redshifts. Finally, we are interested in comparing the performance obtained with respect to the EAzY template fitting approach on Y3 DES Deep Fields catalogue. Methods. We have emulated -- at brighter magnitude -- the training incompleteness with a spectroscopic sample whose redshifts are known to have a measurable view of the problem. We have used a principal component analysis to graphically assess incompleteness and to relate it with the performance parameters provided by DNF. Finally, we have applied the results about the incompleteness to the photo-z computation on Y3 DES Deep Fields with DNF and estimated its performance. Results. The photo-zs for the galaxies on DES Deep Fields have been computed with the DNF algorithm and added to the Y3 DES Deep Fields catalogue. They are available at https://des.ncsa.illinois.edu/releases/y3a2/Y3deepfields. Some techniques have been developed to evaluate the performance in the absence of "true" redshift and to assess completeness. We have studied... (Partial abstract), Comment: 14 pages, 17 figures
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- 2023
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246. Search for 10--1000 GeV neutrinos from Gamma Ray Bursts with IceCube
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IceCube Collaboration, Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Blot, S., Bontempo, F., Book, J. Y., Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Busse, R. S., Butterfield, D., Campana, M. A., Carloni, K., Carnie-Bronca, E. G., Chattopadhyay, S., Chau, N., Chen, C., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Domi, A., Dujmovic, H., DuVernois, M. A., Ehrhardt, T., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Gerhardt, L., Ghadimi, A., Glaser, C., Glauch, T., Glüsenkamp, T., Gonzalez, J. G., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., In, S., Ishihara, A., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Lincetto, M., Liu, Y., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neumann, M., Niederhausen, H., Nisa, M. U., Noell, A., Novikov, A., Nowicki, S. C., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Herrera, S. E. Sanchez, Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seunarine, S., Shah, R., Shefali, S., Shimizu, N., Silva, C., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Tung, C. F., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, Y., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
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Astrophysics - High Energy Astrophysical Phenomena - Abstract
We present the results of a search for 10--1,000 GeV neutrinos from 2,268 gamma-ray bursts over 8 years of IceCube-DeepCore data. This work probes burst physics below the photosphere where electromagnetic radiation cannot escape. Neutrinos of tens of GeVs are predicted in sub-photospheric collision of free streaming neutrons with bulk-jet protons. In a first analysis, we searched for the most significant neutrino-GRB coincidence using six overlapping time windows centered on the prompt phase of each GRB. In a second analysis, we conducted a search for a group of GRBs, each individually too weak to be detectable, but potentially significant when combined. No evidence of neutrino emission is found for either analysis. The most significant neutrino coincidence is for Fermi-GBM GRB bn 140807500, with a p-value of 0.097 corrected for all trials. The binomial test used to search for a group of GRBs had a p-value of 0.65 after all trial corrections. The binomial test found a group consisting only of GRB bn 140807500 and no additional GRBs. The neutrino limits of this work complement those obtained by IceCube at TeV to PeV energies. We compare our findings for the large set of GRBs as well as GRB 221009A to the sub-photospheric neutron-proton collision model and find that GRB 221009A provides the most constraining limit on baryon loading. For a jet Lorentz factor of 300 (800), the baryon loading on GRB 221009A is lower than 3.85 (2.13) at a 90% confidence level.
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- 2023
- Full Text
- View/download PDF
247. Optimizing Likelihood-free Inference using Self-supervised Neural Symmetry Embeddings
- Author
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Chatterjee, Deep, Harris, Philip C., Goel, Maanas, Desai, Malina, Coughlin, Michael W., and Katsavounidis, Erik
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Computer Science - Machine Learning ,Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
Likelihood-free inference is quickly emerging as a powerful tool to perform fast/effective parameter estimation. We demonstrate a technique of optimizing likelihood-free inference to make it even faster by marginalizing symmetries in a physical problem. In this approach, physical symmetries, for example, time-translation are learned using joint-embedding via self-supervised learning with symmetry data augmentations. Subsequently, parameter inference is performed using a normalizing flow where the embedding network is used to summarize the data before conditioning the parameters. We present this approach on two simple physical problems and we show faster convergence in a smaller number of parameters compared to a normalizing flow that does not use a pre-trained symmetry-informed representation., Comment: Accepted for Machine Learning and the Physical Sciences Workshop (submission 69) at NeurIPS 2023; for codes, see https://github.com/ML4GW/summer-projects-2023/blob/neurips-2023/symmetry-informed-flows/README.md
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- 2023
248. Rethinking materials simulations: Blending direct numerical simulations with neural operators
- Author
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Oommen, Vivek, Shukla, Khemraj, Desai, Saaketh, Dingreville, Remi, and Karniadakis, George Em
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Computer Science - Machine Learning ,Physics - Computational Physics - Abstract
Direct numerical simulations (DNS) are accurate but computationally expensive for predicting materials evolution across timescales, due to the complexity of the underlying evolution equations, the nature of multiscale spatio-temporal interactions, and the need to reach long-time integration. We develop a new method that blends numerical solvers with neural operators to accelerate such simulations. This methodology is based on the integration of a community numerical solver with a U-Net neural operator, enhanced by a temporal-conditioning mechanism that enables accurate extrapolation and efficient time-to-solution predictions of the dynamics. We demonstrate the effectiveness of this framework on simulations of microstructure evolution during physical vapor deposition modeled via the phase-field method. Such simulations exhibit high spatial gradients due to the co-evolution of different material phases with simultaneous slow and fast materials dynamics. We establish accurate extrapolation of the coupled solver with up to 16.5$\times$ speed-up compared to DNS. This methodology is generalizable to a broad range of evolutionary models, from solid mechanics, to fluid dynamics, geophysics, climate, and more.
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- 2023
249. All-Sky Search for Transient Astrophysical Neutrino Emission with 10 Years of IceCube Cascade Events
- Author
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Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Ausborm, L., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Blot, S., Bontempo, F., Book, J. Y., Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Busse, R. S., Butterfield, D., Campana, M. A., Carloni, K., Carnie-Bronca, E. G., Chattopadhyay, S., Chau, N., Chen, C., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Domi, A., Dujmovic, H., DuVernois, M. A., Ehrhardt, T., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Gerhardt, L., Ghadimi, A., Glaser, C., Glauch, T., Glüsenkamp, T., Gonzalez, J. G., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., In, S., Ishihara, A., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Lincetto, M., Liu, Y., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neumann, M., Niederhausen, H., Nisa, M. U., Noell, A., Novikov, A., Nowicki, S. C., Pollmann, A. Obertacke, O'Dell, V., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Herrera, S. E. Sanchez, Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Sclafani, S., Seckel, D., Seikh, M., Seunarine, S., Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Tung, C. F., Turcotte, R., Twagirayezu, J. P., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, Y., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
- Subjects
Astrophysics - High Energy Astrophysical Phenomena ,High Energy Physics - Experiment - Abstract
We present the results of a time-dependent search for neutrino flares in data collected by IceCube between May 2011 and 2021. This data set contains cascade-like events originating from charged-current electron neutrino and tau neutrino interactions and all-flavor neutral-current interactions. IceCube's previous all-sky searches for neutrino flares used data sets consisting of track-like events originating from charged-current muon neutrino interactions. The cascade data sets are statistically independent of the track data sets and provide a new opportunity to observe the transient all-sky landscape. This search uses the spatial, temporal, and energy information of the cascade-like events to conduct searches for the most statistically significant neutrino flares in the northern and southern skies. No statistically significant time-dependent neutrino emission was observed. For the most statistically significant location in the northern sky, $p_\mathrm{global} =$ 0.71, and in the southern sky, $p_\mathrm{global} =$ 0.51. These results are compatible with the background hypothesis. Assuming an E$^{-2.53}$ spectrum from the diffuse astrophysical neutrino flux as measured with cascades, these results are used to calculate upper limits at the 90\% confidence level on neutrino flares of varying duration and constrain the contribution of these flares to the diffuse astrophysical neutrino flux. These constraints are independent of a specified class of astrophysical objects and show that multiple unresolved transient sources may contribute to the diffuse astrophysical neutrino flux., Comment: Submitted to The Astrophysical Journal
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- 2023
- Full Text
- View/download PDF
250. Using Large Language Models for Hyperparameter Optimization
- Author
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Zhang, Michael R., Desai, Nishkrit, Bae, Juhan, Lorraine, Jonathan, and Ba, Jimmy
- Subjects
Computer Science - Machine Learning ,Computer Science - Artificial Intelligence - Abstract
This paper studies using foundational large language models (LLMs) to make decisions during hyperparameter optimization (HPO). Empirical evaluations demonstrate that in settings with constrained search budgets, LLMs can perform comparably or better than traditional HPO methods like random search and Bayesian optimization on standard benchmarks. Furthermore, we propose to treat the code specifying our model as a hyperparameter, which the LLM outputs, going beyond the capabilities of existing HPO approaches. Our findings suggest that LLMs are a promising tool for improving efficiency in the traditional decision-making problem of hyperparameter optimization., Comment: 29 pages
- Published
- 2023
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