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339,404 results on '"Pal, A."'

1. Statistics and Complexity of Wavefunction Spreading in Quantum Dynamical Systems

Author: Fu, Yichao, Kim, Keun-Young, Pal, Kunal, and Pal, Kuntal
Subjects: Quantum Physics, High Energy Physics - Theory
Abstract: We consider the statistics of the results of a measurement of the spreading operator in the Krylov basis generated by the Hamiltonian of a quantum system starting from a specified initial pure state. We first obtain the probability distribution of the results of measurements of this spreading operator at a certain instant of time, and compute the characteristic function of this distribution. We show that the moments of this characteristic function are related to the so-called generalised spread complexities, and obtain expressions for them in several cases when the Hamiltonian is an element of a Lie algebra. Furthermore, by considering a continuum limit of the Krylov basis, we show that the generalised spread complexities of higher orders have a peak in the time evolution for a random matrix Hamiltonian belonging to the Gaussian unitary ensemble. We also obtain an upper bound in the change in generalised spread complexity at an arbitrary time in terms of the operator norm of the Hamiltonian and discuss the significance of these results.
Published: 2024

2. Dynamical interiors of Black-Bounce spacetimes

Author: Pal, Kunal, Pal, Kuntal, and Sarkar, Tapobrata
Subjects: General Relativity and Quantum Cosmology, High Energy Physics - Theory
Abstract: Using the Israel-Darmois junction conditions, we obtain a class of regular dynamical interiors to the recently proposed black-bounce spacetimes which regularises the Schwarzschild singularity by introducing a regularisation parameter. We show that a regularised Friedmann-Lemaitre-Robertson-Walker like interior geometry can not be matched smoothly with the exterior black-bounce spacetime through a timelike hypersurface, as there always exists a thin shell of non-zero energy-momentum tensor at the matching hypersurface. We obtain the expressions for the energy density and pressure of the thin shell energy-momentum tensor in terms of the regularisation parameter and derive an evolution equation for the scale factor of the interior geometry by imposing physical conditions on these components of the surface energy-momentum tensor. We also discuss the formation of the event horizon inside the interior in the case when the initial conditions are such that the situation describes a collapsing matter cloud. We elaborate upon the physical implications of these results.
Published: 2024

3. Search for gravitational waves emitted from SN 2023ixf

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abouelfettouh, I., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Agarwal, D., Agathos, M., Abchouyeh, M. Aghaei, Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Argianas, L., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Attadio, F., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Baier, J. G., Baiotti, L., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartoletti, A. M., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bates, D. E., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Baynard II, P. A., Bazzan, M., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blagg, L. A., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boudon, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Brandt, J., Braun, I., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, B. C., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cáceres-Barbosa, V., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, J. C. L., Chan, M., Chandra, K., Chang, R. -J., Chao, S., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, Y., Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Cheung, S. Y., Chiadini, F., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chugh, P., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciolfi, R., Clara, F., Clark, J. A., Clarke, J., Clarke, T. A., Clearwater, P., Clesse, S., Coccia, E., Codazzo, E., Cohadon, P. -F., Colace, S., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Connolly, G., Conti, L., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Crook, S., Crouch, R., Csizmazia, J., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Pra, S. Dal, Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Davis, P. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., De Simone, R., Dhani, A., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Dominguez, D., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Eleveld, R. M., Emma, M., Endo, K., Engl, A. J., Enloe, E., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Felicetti, R., Fenyvesi, E., Ferguson, D. L., Ferraiuolo, S., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fujimori, T., Fulda, P., Fyffe, M., Gadre, B., Gair, J. R., Galaudage, S., Galdi, V., Gallagher, H., Gallardo, S., Gallego, B., Gamba, R., Gamboa, A., Ganapathy, D., Ganguly, A., Garaventa, B., García-Bellido, J., Núñez, C. García, García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garron, A., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., Gennari, V., George, J., George, R., Gerberding, O., Gergely, L., Ghosh, Archisman, Ghosh, Sayantan, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gibson, D. T., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Glotin, F., Godfrey, J., Godwin, P., Goebbels, N. L., Goetz, E., Golomb, J., Lopez, S. Gomez, Goncharov, B., Gong, Y., González, G., Goodarzi, P., Goode, S., Goodwin-Jones, A. W., Gosselin, M., Göttel, A. S., Gouaty, R., Gould, D. W., Govorkova, K., Goyal, S., Grace, B., Grado, A., Graham, V., Granados, A. E., Granata, M., Granata, V., Gras, S., Grassia, P., Gray, A., Gray, C., Gray, R., Greco, G., Green, A. C., Green, S. M., Green, S. R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimaud, C., Grote, H., Guerra, D., Guetta, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H., Guo, W., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, Ish, Gupta, N. C., Gupta, P., Gupta, S. K., Gupta, T., Gupte, N., Gurs, J., Gutierrez, N., Guzman, F., H, H. -Y., Haba, D., Haberland, M., Haino, S., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hanselman, A. G., Hansen, H., Hanson, J., Harada, R., Hardison, A. R., Haris, K., Harmark, T., Harms, J., Harry, G. M., Harry, I. W., Hart, J., Haskell, B., Haster, C. -J., Hathaway, J. S., Haughian, K., Hayakawa, H., Hayama, K., Hayes, R., Heffernan, A., Heidmann, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Henderson-Sapir, O., Hendry, M., Heng, I. S., Hennes, E., Henshaw, C., Hertog, T., Heurs, M., Hewitt, A. L., Heyns, J., Higginbotham, S., Hild, S., Hill, S., Himemoto, Y., Hirata, N., Hirose, C., Hoang, S., Hochheim, S., Hofman, D., Holland, N. A., Holley-Bockelmann, K., Holmes, Z. J., Holz, D. E., Honet, L., Hong, C., Hornung, J., Hoshino, S., Hough, J., Hourihane, S., Howell, E. J., Hoy, C. G., Hrishikesh, C. A., Hsieh, H. -F., Hsiung, C., Hsu, H. C., Hsu, W. -F., Hu, P., Hu, Q., Huang, H. Y., Huang, Y. -J., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V., Husa, S., Huxford, R., Huynh-Dinh, T., Iampieri, L., Iandolo, G. A., Ianni, M., Iess, A., Imafuku, H., Inayoshi, K., Inoue, Y., Iorio, G., Iqbal, M. H., Irwin, J., Ishikawa, R., Isi, M., Ismail, M. A., Itoh, Y., Iwanaga, H., Iwaya, M., Iyer, B. R., JaberianHamedan, V., Jacquet, C., Jacquet, P. -E., Jadhav, S. J., Jadhav, S. P., Jain, T., James, A. L., James, P. A., Jamshidi, R., Janquart, J., Janssens, K., Janthalur, N. N., Jaraba, S., Jaranowski, P., Jaume, R., Javed, W., Jennings, A., Jia, W., Jiang, J., Kubisz, J., Johanson, C., Johns, G. R., Johnson, N. A., Johnston, M. C., Johnston, R., Johny, N., Jones, D. H., Jones, D. I., Jones, R., Jose, S., Joshi, P., Ju, L., Jung, K., Junker, J., Juste, V., Kajita, T., Kaku, I., Kalaghatgi, C., Kalogera, V., Kamiizumi, M., Kanda, N., Kandhasamy, S., Kang, G., Kanner, J. B., Kapadia, S. J., Kapasi, D. P., Karat, S., Karathanasis, C., Kashyap, R., Kasprzack, M., Kastaun, W., Kato, T., Katsavounidis, E., Katzman, W., Kaushik, R., Kawabe, K., Kawamoto, R., Kazemi, A., Keitel, D., Kelley-Derzon, J., Kennington, J., Kesharwani, R., Key, J. S., Khadela, R., Khadka, S., Khalili, F. Y., Khan, F., Khan, I., Khanam, T., Khursheed, M., Khusid, N. M., Kiendrebeogo, W., Kijbunchoo, N., Kim, C., Kim, J. C., Kim, K., Kim, M. H., Kim, S., Kim, Y. -M., Kimball, C., Kinley-Hanlon, M., Kinnear, M., Kissel, J. S., Klimenko, S., Knee, A. M., Knust, N., Kobayashi, K., Obergaulinger, M., Koch, P., Koehlenbeck, S. M., Koekoek, G., Kohri, K., Kokeyama, K., Koley, S., Kolitsidou, P., Kolstein, M., Komori, K., Kong, A. K. H., Kontos, A., Korobko, M., Kossak, R. V., Kou, X., Koushik, A., Kouvatsos, N., Kovalam, M., Kozak, D. B., Kranzhoff, S. L., Kringel, V., Krishnendu, N. V., Królak, A., Kruska, K., Kuehn, G., Kuijer, P., Kulkarni, S., Ramamohan, A. Kulur, Kumar, A., Kumar, Praveen, Kumar, Prayush, Kumar, Rahul, Kumar, Rakesh, Kume, J., Kuns, K., Kuntimaddi, N., Kuroyanagi, S., Kurth, N. J., Kuwahara, S., Kwak, K., Kwan, K., Kwok, J., Lacaille, G., Lagabbe, P., Laghi, D., Lai, S., Laity, A. H., Lakkis, M. H., Lalande, E., Lalleman, M., Lalremruati, P. C., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., La Rana, A., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Lawrence, J., Lawrence, M. N., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Lecoeuche, Y. K., Lee, H. M., Lee, H. W., Lee, K., Lee, R. -K., Lee, R., Lee, S., Lee, Y., Legred, I. N., Lehmann, J., Lehner, L., Jean, M. Le, Lemaître, A., Lenti, M., Leonardi, M., Lequime, M., Leroy, N., Lesovsky, M., Letendre, N., Lethuillier, M., Levin, S. E., Levin, Y., Leyde, K., Li, A. K. Y., Li, K. L., Li, T. G. F., Li, X., Li, Z., Lihos, A., Lin, C-Y., Lin, C. -Y., Lin, E. T., Lin, F., Lin, H., Lin, L. C. -C., Lin, Y. -C., Linde, F., Linker, S. D., Littenberg, T. B., Liu, A., Liu, G. C., Liu, Jian, Villarreal, F. Llamas, Llobera-Querol, J., Lo, R. K. L., Locquet, J. -P., London, L. T., Longo, A., Lopez, D., Portilla, M. Lopez, Lorenzini, M., Lorenzo-Medina, A., Loriette, V., Lormand, M., Losurdo, G., Lott IV, T. P., Lough, J. D., Loughlin, H. A., Lousto, C. O., Lowry, M. J., Lu, N., Lück, H., Lumaca, D., Lundgren, A. P., Lussier, A. W., Ma, L. -T., Ma, S., Ma'arif, M., Macas, R., Macedo, A., MacInnis, M., Maciy, R. R., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Macri, D., Maeda, K., Maenaut, S., Hernandez, I. Magaña, Magare, S. S., Magazzù, C., Magee, R. M., Maggio, E., Maggiore, R., Magnozzi, M., Mahesh, M., Mahesh, S., Maini, M., Majhi, S., Majorana, E., Makarem, C. N., Makelele, E., Malaquias-Reis, J. A., Mali, U., Maliakal, S., Malik, A., Man, N., Mandic, V., Mangano, V., Mannix, B., Mansell, G. L., Mansingh, G., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Pina, D. Marín, Marion, F., Márka, S., Márka, Z., Markosyan, A. S., Markowitz, A., Maros, E., Marsat, S., Martelli, F., Martin, I. W., Martin, R. M., Martinez, B. B., Martinez, M., Martinez, V., Martini, A., Martinovic, K., Martins, J. C., Martynov, D. V., Marx, E. J., Massaro, L., Masserot, A., Masso-Reid, M., Mastrodicasa, M., Mastrogiovanni, S., Matcovich, T., Matiushechkina, M., Matsuyama, M., Mavalvala, N., Maxwell, N., McCarrol, G., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McEachin, S., McElhenny, C., McGhee, G. I., McGinn, J., McGowan, K. B. M., McIver, J., McLeod, A., McRae, T., Meacher, D., Meijer, Q., Melatos, A., Mellaerts, S., Menendez-Vazquez, A., Menoni, C. S., Mera, F., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Mérou, J. R., Merritt, J. D., Merzougui, M., Messenger, C., Messick, C., Meyer-Conde, M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Miller, A. L., Miller, S., Millhouse, M., Milotti, E., Milotti, V., Minenkov, Y., Mio, N., Mir, Ll. M., Mirasola, L., Miravet-Tenés, M., Miritescu, C. -A., Mishra, A. K., Mishra, A., Mishra, C., Mishra, T., Mitchell, A. L., Mitchell, J. G., Mitra, S., Mitrofanov, V. P., Mittleman, R., Miyakawa, O., Miyamoto, S., Miyoki, S., Mo, G., Mobilia, L., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondal, C., Mondin, M., Montani, M., Moore, C. J., Moraru, D., More, A., More, S., Moreno, G., Morgan, C., Morisaki, S., Moriwaki, Y., Morras, G., Moscatello, A., Mourier, P., Mours, B., Mow-Lowry, C. M., Muciaccia, F., Mukherjee, Arunava, Mukherjee, D., Mukherjee, Samanwaya, Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Mundi, J., Mungioli, C. L., Oberg, W. R. Munn, Murakami, Y., Murakoshi, M., Murray, P. G., Muusse, S., Nabari, D., Nadji, S. L., Nagar, A., Nagarajan, N., Nagler, K. N., Nakagaki, K., Nakamura, K., Nakano, H., Nakano, M., Nandi, D., Napolano, V., Narayan, P., Nardecchia, I., Narikawa, T., Narola, H., Naticchioni, L., Nayak, R. K., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Neunzert, A., Ng, S., Quynh, L. Nguyen, Nichols, S. A., Nielsen, A. B., Nieradka, G., Niko, A., Nishino, Y., Nishizawa, A., Nissanke, S., Nitoglia, E., Niu, W., Nocera, F., Norman, M., North, C., Novak, J., Siles, J. F. Nuño, Nuttall, L. K., Obayashi, K., Oberling, J., O'Dell, J., Oertel, M., Offermans, A., Oganesyan, G., Oh, J. J., Oh, K., O'Hanlon, T., Ohashi, M., Ohkawa, M., Ohme, F., Oliveira, A. S., Oliveri, R., O'Neal, B., Oohara, K., O'Reilly, B., Ormsby, N. D., Orselli, M., O'Shaughnessy, R., O'Shea, S., Oshima, Y., Oshino, S., Ossokine, S., Osthelder, C., Ota, I., Ottaway, D. J., Ouzriat, A., Overmier, H., Owen, B. J., Pace, A. E., Pagano, R., Page, M. A., Pai, A., Pal, A., Pal, S., Palaia, M. A., Pálfi, M., Palma, P. 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Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We present the results of a search for gravitational-wave transients associated with core-collapse supernova SN 2023ixf, which was observed in the galaxy Messier 101 via optical emission on 2023 May 19th, during the LIGO-Virgo-KAGRA 15th Engineering Run. We define a five-day on-source window during which an accompanying gravitational-wave signal may have occurred. No gravitational waves have been identified in data when at least two gravitational-wave observatories were operating, which covered $\sim 14\%$ of this five-day window. We report the search detection efficiency for various possible gravitational-wave emission models. Considering the distance to M101 (6.7 Mpc), we derive constraints on the gravitational-wave emission mechanism of core-collapse supernovae across a broad frequency spectrum, ranging from 50 Hz to 2 kHz where we assume the GW emission occurred when coincident data are available in the on-source window. Considering an ellipsoid model for a rotating proto-neutron star, our search is sensitive to gravitational-wave energy $1 \times 10^{-5} M_{\odot} c^2$ and luminosity $4 \times 10^{-5} M_{\odot} c^2/\text{s}$ for a source emitting at 50 Hz. These constraints are around an order of magnitude more stringent than those obtained so far with gravitational-wave data. The constraint on the ellipticity of the proto-neutron star that is formed is as low as $1.04$, at frequencies above $1200$ Hz, surpassing results from SN 2019ejj., Comment: Main paper: 6 pages, 4 figures and 1 table. Total with appendices: 20 pages, 4 figures, and 1 table
Published: 2024

4. A search using GEO600 for gravitational waves coincident with fast radio bursts from SGR 1935+2154

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abouelfettouh, I., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Agarwal, D., Agathos, M., Abchouyeh, M. Aghaei, Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Argianas, L., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Attadio, F., Aubin, F., AultONeal, K., Avallone, G., Azrad, D., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Baier, J. G., Baiotti, L., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartoletti, A. M., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bates, D. E., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Baynard II, P. A., Bazzan, M., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blagg, L. A., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boudon, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Brandt, J., Braun, I., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, B. C., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cáceres-Barbosa, V., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, J. C. L., Chan, M., Chandra, K., Chang, R. -J., Chao, S., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, Y., Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Cheung, S. Y., Chiadini, F., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chugh, P., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciolfi, R., Clara, F., Clark, J. A., Clarke, J., Clarke, T. A., Clearwater, P., Clesse, S., Coccia, E., Codazzo, E., Cohadon, P. -F., Colace, S., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Connolly, G., Conti, L., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Crook, S., Crouch, R., Csizmazia, J., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. 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Tapia San, Tarafder, R., Taranto, C., Taruya, A., Tasson, J. D., Teloi, M., Tenorio, R., Themann, H., Theodoropoulos, A., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tissino, J., Tiwari, A., Tiwari, P., Tiwari, S., Tiwari, V., Todd, M. R., Toivonen, A. M., Toland, K., Tolley, A. E., Tomaru, T., Tomita, K., Tomura, T., Tong-Yu, C., Toriyama, A., Toropov, N., Torres-Forné, A., Torrie, C. I., Toscani, M., Melo, I. Tosta e, Tournefier, E., Trapananti, A., Travasso, F., Traylor, G., Trevor, M., Tringali, M. C., Tripathee, A., Troian, G., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. J., Tsang, T. T. L., Tso, R., Tsuchida, S., Tsukada, L., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Ubach, H., Uchiyama, T., Udall, R. P., Uehara, T., Uematsu, M., Ueno, K., Ueno, S., Undheim, V., Ushiba, T., Vacatello, M., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valencia, J., Valentini, M., Vallejo-Peña, S. A., Vallero, S., Valsan, V., van Bakel, N., van Beuzekom, M., van Dael, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Sluys, M., Van de Walle, A., van Dongen, J., Vandra, K., van Haevermaet, H., van Heijningen, J. V., Van Hove, P., VanKeuren, M., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varghese, J. J., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venikoudis, S., Venneberg, J., Verdier, P., Verkindt, D., Verma, B., Verma, P., Verma, Y., Vermeulen, S. M., Vetrano, F., Veutro, A., Vibhute, A. M., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Vilkha, A., Villa-Ortega, V., Vincent, E. T., Vinet, J. -Y., Viret, S., Virtuoso, A., Vitale, S., Vives, A., Vocca, H., Voigt, D., von Reis, E. R. G., von Wrangel, J. S. A., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Wajid, A., Walker, M., Wallace, G. S., Wallace, L., Wang, H., Wang, J. Z., Wang, W. H., Wang, Z., Waratkar, G., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watarai, D., Wayt, K. E., Weaver, B. R., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., Whiting, B. F., Whittle, C., Wildberger, J. B., Wilk, O. S., Wilken, D., Wilkin, A. T., Willadsen, D. J., Willetts, K., Williams, D., Williams, M. J., Williams, N. S., Willis, J. L., Willke, B., Wils, M., Winterflood, J., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wolfe, N. E., Wong, H. T., Wong, H. W. Y., Wong, I. C. F., Wright, J. L., Wright, M., Wu, C., Wu, D. S., Wu, H., Wuchner, E., Wysocki, D. M., Xu, V. A., Xu, Y., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yan, T., Yang, F. W., Yang, F., Yang, K. Z., Yang, Y., Yarbrough, Z., Yasui, H., Yeh, S. -W., Yelikar, A. B., Yin, X., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuan, S., Yuzurihara, H., Zadrożny, A., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zeoli, M., Zerrad, M., Zevin, M., Zhang, A. C., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhou, R., Zhu, X. -J., Zhu, Z. -H., Zucker, M. E., and Zweizig, J.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: The magnetar SGR 1935+2154 is the only known Galactic source of fast radio bursts (FRBs). FRBs from SGR 1935+2154 were first detected by CHIME/FRB and STARE2 in 2020 April, after the conclusion of the LIGO, Virgo, and KAGRA Collaborations' O3 observing run. Here we analyze four periods of gravitational wave (GW) data from the GEO600 detector coincident with four periods of FRB activity detected by CHIME/FRB, as well as X-ray glitches and X-ray bursts detected by NICER and NuSTAR close to the time of one of the FRBs. We do not detect any significant GW emission from any of the events. Instead, using a short-duration GW search (for bursts $\leq$ 1 s) we derive 50\% (90\%) upper limits of $10^{48}$ ($10^{49}$) erg for GWs at 300 Hz and $10^{49}$ ($10^{50}$) erg at 2 kHz, and constrain the GW-to-radio energy ratio to $\leq 10^{14} - 10^{16}$. We also derive upper limits from a long-duration search for bursts with durations between 1 and 10 s. These represent the strictest upper limits on concurrent GW emission from FRBs., Comment: 15 pages of text including references, 4 figures, 5 tables
Published: 2024

5. Exploring neutrino interactions in light of present and upcoming galaxy survey

Author: Pal, Sourav, Samanta, Rickmoy, and Pal, Supratik
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, High Energy Physics - Phenomenology
Abstract: In the standard cosmological framework, neutrinos begin to free-stream after the weak interaction phase ends in the early universe, at a temperature of approximately $T \sim 1 \, {\rm MeV}$. However, the onset of neutrino free-streaming can be delayed if additional interactions occur in the early universe, leaving imprints on both the cosmic microwave background (CMB) angular power spectra and the large-scale structure (LSS) matter power spectra. We present a thorough analysis of early universe neutrino interactions with a fairly generalized parameterization of the interaction rates as a power law in neutrino temperature. In this (6+2) parameter scenario, we constrain the cosmological parameters along with the free-streaming redshift and the sum of the neutrino mass in presence of such interactions, with the help of full shape (FS) galaxy power spectra from BOSS Data Release 12. Our analysis reveals that a combined dataset of FS along with CMB and BAO offers improved constraints on the free-streaming redshift from present data, comparable to the forecast results from future CMB-S4 data. Additionally, we investigate the prospects of future galaxy surveys by forecasting on Euclid mission in combination with Planck and CMB-S4, and find significant improvement on both the free-streaming redshift and the sum of the neutrino mass than the existing constraints as well as than CMB-S4 alone., Comment: 21 pages, 5 sets of figures and 7 tables. Comments are welcome
Published: 2024

6. Phytochemicals in mango (Mangifera indica) parts and their bioactivities: A Review

Author: Yadav, Deependra, Pal, A. K., Singh, S. P., and Sati, Kailash
Published: 2022
Full Text: View/download PDF

7. Dynamically Encircled Higher-order Exceptional Points in an Optical Fiber

Author: Roy, Arpan, Laha, Arnab, Biswas, Abhijit, Miranowicz, Adam, Pal, Bishnu P., and Ghosh, Somnath
Subjects: Physics - Optics
Abstract: The unique properties of exceptional point (EP) singularities, arising from non-Hermitian physics, have unlocked new possibilities for manipulating light-matter interactions. A tailored gain-loss variation, while encircling higher-order EPs dynamically, can significantly enhance the control of the topological flow of light in multi-level photonic systems. In particular, the integration of dynamically encircled higher-order EPs within fiber geometries holds remarkable promise for advancing specialty optical fiber applications, though a research gap remains in exploring and realizing such configurations. Here, we report a triple-core specialty optical fiber engineered with customized loss and gain to explore the topological characteristics of a third-order exceptional point (EP3), formed by two interconnected second-order exceptional points (EP2s). We elucidate chiral and nonchiral light transmission through the fiber, grounded in second- and third-order branch point behaviors and associated adiabatic and nonadiabatic modal characteristics, while considering various dynamical parametric loops to encircle the embedded EPs. We investigate the persistence of EP-induced light dynamics specifically in the parametric regions immediately adjacent to, though not encircling, the embedded EPs, potentially leading to improved device performance. Our findings offer significant implications for the design and implementation of novel light management technologies in all-fiber photonics and communications., Comment: 10 pages, 5 figures
Published: 2024

8. Designing Atomtronic Circuits via Superfluid Dynamics

Author: Jährling, Sarah, Singh, Vijay Pal, and Mathey, Ludwig
Subjects: Condensed Matter - Quantum Gases, Quantum Physics
Abstract: We propose to design atomtronic circuits with Bose-Einstein condensates (BECs) in circuit-like traps that are controlled via mobile barriers. Using classical-field simulations, we demonstrate a universal set of logical gates and show how to assemble them into circuits. We first demonstrate an AND gate based on a T-shaped BEC, utilizing a combination of mobile and static barriers. The mobile barriers provide the logical input of the gate, while the static barrier functions as a Josephson junction that generates the AND output of the gate via a density imbalance across the barrier. Next we show how to combine three AND gates into a circuit, with a design composed of two T-shapes and an H-shape. Furthermore, we demonstrate how to use Josephson oscillations to create a NOT gate and combine it with an AND gate, thereby showcasing a universal set of gates and their assembly into circuits., Comment: 9 pages, 8 figures
Published: 2024

9. Comparative Analysis of Audio Feature Extraction for Real-Time Talking Portrait Synthesis

Author: Salehi, Pegah, Sheshkal, Sajad Amouei, Thambawita, Vajira, Gautam, Sushant, Sabet, Saeed S., Johansen, Dag, Riegler, Michael A., and Halvorsen, Pål
Subjects: Computer Science - Sound, Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction, Electrical Engineering and Systems Science - Audio and Speech Processing, 68T45, 68T07, 68T01
Abstract: This paper examines the integration of real-time talking-head generation for interviewer training, focusing on overcoming challenges in Audio Feature Extraction (AFE), which often introduces latency and limits responsiveness in real-time applications. To address these issues, we propose and implement a fully integrated system that replaces conventional AFE models with Open AI's Whisper, leveraging its encoder to optimize processing and improve overall system efficiency. Our evaluation of two open-source real-time models across three different datasets shows that Whisper not only accelerates processing but also improves specific aspects of rendering quality, resulting in more realistic and responsive talking-head interactions. These advancements make the system a more effective tool for immersive, interactive training applications, expanding the potential of AI-driven avatars in interviewer training., Comment: 16 pages, 6 figures, 3 tables. submitted to MDPI journal in as Big Data and Cognitive Computing
Published: 2024

10. The impact of stochastic resetting on resource allocation: The case of Reallocating geometric Brownian motion

Author: Jolakoski, Petar, Trajanovski, Pece, Pal, Arnab, Stojkoski, Viktor, Kocarev, Ljupco, and Sandev, Trifce
Subjects: Condensed Matter - Statistical Mechanics
Abstract: We study the effects of stochastic resetting on the Reallocating geometric Brownian motion (RGBM), an established model for resource redistribution relevant to systems such as population dynamics, evolutionary processes, economic activity, and even cosmology. The RGBM model is inherently non-stationary and non-ergodic, leading to complex resource redistribution dynamics. By introducing stochastic resetting, which periodically returns the system to a predetermined state, we examine how this mechanism modifies RGBM behavior. Our analysis uncovers distinct long-term regimes determined by the interplay between the resetting rate, the strength of resource redistribution, and standard geometric Brownian motion parameters: the drift and the noise amplitude. Notably, we identify a critical resetting rate beyond which the self-averaging time becomes effectively infinite. In this regime, the first two moments are stationary, indicating a stabilized distribution of an initially unstable, mean-repulsive process. We demonstrate that optimal resetting can effectively balance growth and redistribution, reducing inequality in the resource distribution. These findings help us understand better the management of resource dynamics in uncertain environments.
Published: 2024

11. KAN/MultKAN with Physics-Informed Spline fitting (KAN-PISF) for ordinary/partial differential equation discovery of nonlinear dynamic systems

Author: Pal, Ashish and Nagarajaiah, Satish
Subjects: Physics - Computational Physics, Computer Science - Machine Learning
Abstract: Machine learning for scientific discovery is increasingly becoming popular because of its ability to extract and recognize the nonlinear characteristics from the data. The black-box nature of deep learning methods poses difficulties in interpreting the identified model. There is a dire need to interpret the machine learning models to develop a physical understanding of dynamic systems. An interpretable form of neural network called Kolmogorov-Arnold networks (KAN) or Multiplicative KAN (MultKAN) offers critical features that help recognize the nonlinearities in the governing ordinary/partial differential equations (ODE/PDE) of various dynamic systems and find their equation structures. In this study, an equation discovery framework is proposed that includes i) sequentially regularized derivatives for denoising (SRDD) algorithm to denoise the measure data to obtain accurate derivatives, ii) KAN to identify the equation structure and suggest relevant nonlinear functions that are used to create a small overcomplete library of functions, and iii) physics-informed spline fitting (PISF) algorithm to filter the excess functions from the library and converge to the correct equation. The framework was tested on the forced Duffing oscillator, Van der Pol oscillator (stiff ODE), Burger's equation, and Bouc-Wen model (coupled ODE). The proposed method converged to the true equation for the first three systems. It provided an approximate model for the Bouc-Wen model that could acceptably capture the hysteresis response. Using KAN maintains low complexity, which helps the user interpret the results throughout the process and avoid the black-box-type nature of machine learning methods.
Published: 2024

12. Chebyshev's method for exponential maps

Author: Ghora, Subhasis, Nayak, Tarakanta, Pal, Soumen, and Phogat, Pooja
Subjects: Mathematics - Dynamical Systems, 37F10, 65H05
Abstract: It is proved that the Chebyshev's method applied to an entire function $f$ is a rational map if and only if $f(z) = p(z) e^{q(z)}$, for some polynomials $p$ and $q$. These are referred to as rational Chebyshev maps, and their fixed points are discussed in this article. It is seen that $\infty$ is a parabolic fixed point with multiplicity one bigger than the degree of $q$. Considering $q(z)=p(z)^n+c$, where $p$ is a linear polynomial, $n \in \mathbb{N}$ and $c$ is a non-zero constant, we show that the Chebyshev's method applied to $pe^q$ is affine conjugate to that applied to $z e^{z^n}$. We denote this by $C_n$. All the finite extraneous fixed points of $C_n$ are shown to be repelling. The Julia set $\mathcal{J}(C_n)$ of $C_n$ is found to be preserved under rotations of order $n$ about the origin. For each $n$, the immediate basin of $0$ is proved to be simply connected. For all $n \leq 16$, we prove that $\mathcal{J}(C_n)$ is connected. The Newton's method applied to $ze^{z^n}$ is found to be conjugate to a polynomial, and its dynamics is also completely determined., Comment: 29 pages, 10 figures
Published: 2024

13. Measurement of enhanced electric dipole transition strengths at high spin in $^{100}$Ru: Possible observation of octupole deformation

Author: Karmakar, A., Nazir, Nazira, Datta, P., Sheikh, J. A., Jehangir, S., Bhat, G. H., Nayak, S. S., Bhattacharya, Soumik, Paul, Suchorita, Pal, Snigdha, Bhattacharyya, S., Mukherjee, G., Basu, S., Chakraborty, S., Panwar, S., Giri, Pankaj K., Raut, R., Ghugre, S. S., Palit, R., Ali, Sajad, Shaikh, W., and Chattopadhyay, S.
Subjects: Nuclear Experiment, Nuclear Theory
Abstract: The majority of atomic nuclei have deformed shapes and nearly all these shapes are symmetric with respect to reflection. There are only a few reflection asymmetric pear-shaped nuclei that have been found in actinide and lanthanide regions, which have static octupole deformation. These nuclei possess an intrinsic electric dipole moment due to the shift between the center of charge and the center of mass. This manifests in the enhancement of the electric dipole transition rates. In this article, we report on the measurement of the lifetimes of the high spin levels of the two alternate parity bands in $^{100}$Ru through the Doppler Shift Attenuation Method. The estimated electric dipole transition rates have been compared with the calculated transition rates using the triaxial projected shell model without octupole deformation, and are found to be an order of magnitude enhanced. Thus, the observation of seven inter-leaved electric dipole transitions with enhanced rates establish $^{100}$Ru as possibly the first octupole deformed nucleus reported in the A $\approx$ 100 mass region.
Published: 2024

14. Self-consistent thermodynamical treatment for quark matter in quasi-particle model at finite temperature

Author: Pal, Suman and Chaudhuri, Gargi
Subjects: High Energy Physics - Phenomenology, Astrophysics - High Energy Astrophysical Phenomena, Nuclear Theory
Abstract: In this work, we have studied the medium effects in strange quark matter in the framework of a grand-canonical ensemble using the phenomenological quasi-particle model. This model is studied with proper self-consistent thermodynamical treatment by incorporating chemical potential-dependent quark mass. We have also included the vector interaction in a self-consistent way. The main aim of this work is to explore the proper thermodynamic treatment in addressing the medium effects at both zero and finite temperatures. In the case of the finite temperature, we explore the study of self-consistent thermodynamics in the isothermal as well as the isentropic processes. The effect of finite temperature and lepton fraction have been studied on the equation of state, speed of sound, and particle fraction. The $M-R$ and $M-\Lambda$ diagrams are found to be consistent with the observational constraints.
Published: 2024

15. IntentGPT: Few-shot Intent Discovery with Large Language Models

Author: Rodriguez, Juan A., Botzer, Nicholas, Vazquez, David, Pal, Christopher, Pedersoli, Marco, and Laradji, Issam
Subjects: Computer Science - Computation and Language
Abstract: In today's digitally driven world, dialogue systems play a pivotal role in enhancing user interactions, from customer service to virtual assistants. In these dialogues, it is important to identify user's goals automatically to resolve their needs promptly. This has necessitated the integration of models that perform Intent Detection. However, users' intents are diverse and dynamic, making it challenging to maintain a fixed set of predefined intents. As a result, a more practical approach is to develop a model capable of identifying new intents as they emerge. We address the challenge of Intent Discovery, an area that has drawn significant attention in recent research efforts. Existing methods need to train on a substantial amount of data for correctly identifying new intents, demanding significant human effort. To overcome this, we introduce IntentGPT, a novel training-free method that effectively prompts Large Language Models (LLMs) such as GPT-4 to discover new intents with minimal labeled data. IntentGPT comprises an \textit{In-Context Prompt Generator}, which generates informative prompts for In-Context Learning, an \textit{Intent Predictor} for classifying and discovering user intents from utterances, and a \textit{Semantic Few-Shot Sampler} that selects relevant few-shot examples and a set of known intents to be injected into the prompt. Our experiments show that IntentGPT outperforms previous methods that require extensive domain-specific data and fine-tuning, in popular benchmarks, including CLINC and BANKING, among others., Comment: ICLR 2024 Workshop on LLM Agents
Published: 2024

16. The role of inducible defence in ecological models: Effects of nonlocal intraspecific competitions

Author: Saha, Sangeeta, Pal, Swadesh, and Melnik, Roderick
Subjects: Quantitative Biology - Populations and Evolution, Mathematics - Dynamical Systems
Abstract: Phenotypic plasticity is a key factor in driving the evolution of species in the predator-prey interaction. The natural environment is replete with phenotypic plasticity, which is the source of inducible defences against predators, including concealment, cave-dwelling, mimicry, evasion, and revenge. In this work, a predator-prey model is proposed where the prey species shows inducible defence against their predators. The dynamics produce a wide range of non-trivial and impactful results, including the stabilizing effect of the defence mechanism. The model is also analyzed in the presence of spatio-temporal diffusion in a bounded domain. It is found in the numerical simulation that the Turing domain shrinks with the increase of defence level. The work is extended further by introducing a nonlocal term in the intra-specific competition of the prey species. The Turing instability condition has been studied for the local model around the coexisting steady state, followed by the Turing and non-Turing patterns in the presence of the nonlocal interaction term. The work reveals how an increase in inducible defence reduces the Turing domain in the local interaction model but expands it when the range of nonlocal interactions is extended, suggesting a higher likelihood of species colonization., Comment: arXiv admin note: text overlap with arXiv:2310.01392
Published: 2024

17. Exploring the Influence of Residential Electric Vehicle Charging on Distribution System Hosting Capacity -- A Case-Study in Arizona

Author: Golgol, Mohammad, Pal, Anamitra, Vittal, Vijay, Fini, Christine, Palomino, Ernest, and Girardi, Kyle
Subjects: Electrical Engineering and Systems Science - Systems and Control
Abstract: The installation of high-capacity fast chargers for electric vehicles (EVs) is posing a significant risk to the distribution grid as the increased demand from widespread residential EV charging could exceed the technical limits of the distribution system. Addressing this issue is critical, given that current infrastructure upgrades to enhance EV hosting capacity are both costly and time-consuming. Moreover, the inherent uncertainties associated with EV charging parameters make it challenging for power utilities to accurately assess the impact of EVs added to specific locations. To address these knowledge gaps, this study (a) introduces an algorithm to coordinate residential EV charging, and (b) proposes a comprehensive framework that evaluates all transformers within a feeder. The proposed method is applied to a real-world feeder, which includes 120 transformers of varying capacities. The results demonstrate that this approach effectively manages a substantial number of EVs without overloading any of the transformers, while also pinpointing locations that must be prioritized for future upgrades. This framework can serve as a valuable reference for utilities when conducting distribution system evaluations for supporting the growing EV penetration.
Published: 2024

18. Entanglement asymmetry and symmetry defects in boundary conformal field theory

Author: Kusuki, Yuya, Murciano, Sara, Ooguri, Hirosi, and Pal, Sridip
Subjects: High Energy Physics - Theory, Condensed Matter - Statistical Mechanics, Quantum Physics
Abstract: A state in a quantum system with a given global symmetry, $G$, can be sensitive to the presence of boundaries, which may either preserve or break this symmetry. In this work, we investigate how conformal invariant boundary conditions influence the $G-$symmetry breaking through the lens of the entanglement asymmetry, a quantifier of the "distance" between a symmetry-broken state and its symmetrized counterpart. By leveraging 2D boundary conformal field theory (BCFT), we investigate the symmetry breaking for both finite and compact Lie groups. Beyond the leading order term, we also compute the subleading corrections in the subsystem size, highlighting their dependence on the symmetry group $G$ and the BCFT operator content. We further explore the entanglement asymmetry following a global quantum quench, where a symmetry-broken state evolves under a symmetry-restoring Hamiltonian. In this dynamical setting, we compute the entanglement asymmetry by extending the method of images to a BCFT with non-local objects such as invertible symmetry defects., Comment: 29 pages, 7 figures
Published: 2024

19. CWebGen -- A tool to study colour structure of scattering amplitudes in IR limit

Author: Agarwal, Neelima, Pal, Sourav, Srivastav, Aditya, and Tripathi, Anurag
Subjects: High Energy Physics - Phenomenology, High Energy Physics - Theory
Abstract: Infrared singularities in perturbative Quantum Chromodynamics (QCD) are captured by the Soft function, which can be calculated efficiently using Feynman diagrams known as webs. The starting point for calculating Soft function using webs is to compute the web mixing matrices using a well known replica trick algorithm. We present a package implemented in Mathematica to calculate these mixing matrices. Along with the package, we provide several state-of-the art computations., Comment: 19 pages, 5 figures, 2 tables
Published: 2024

20. Semi-Truths: A Large-Scale Dataset of AI-Augmented Images for Evaluating Robustness of AI-Generated Image detectors

Author: Pal, Anisha, Kruk, Julia, Phute, Mansi, Bhattaram, Manognya, Yang, Diyi, Chau, Duen Horng, and Hoffman, Judy
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Text-to-image diffusion models have impactful applications in art, design, and entertainment, yet these technologies also pose significant risks by enabling the creation and dissemination of misinformation. Although recent advancements have produced AI-generated image detectors that claim robustness against various augmentations, their true effectiveness remains uncertain. Do these detectors reliably identify images with different levels of augmentation? Are they biased toward specific scenes or data distributions? To investigate, we introduce SEMI-TRUTHS, featuring 27,600 real images, 223,400 masks, and 1,472,700 AI-augmented images that feature targeted and localized perturbations produced using diverse augmentation techniques, diffusion models, and data distributions. Each augmented image is accompanied by metadata for standardized and targeted evaluation of detector robustness. Our findings suggest that state-of-the-art detectors exhibit varying sensitivities to the types and degrees of perturbations, data distributions, and augmentation methods used, offering new insights into their performance and limitations. The code for the augmentation and evaluation pipeline is available at https://github.com/J-Kruk/SemiTruths., Comment: Accepted at NeurIPS 2024 Track Datasets & Benchmarks Track
Published: 2024

21. External Control over Magnon-Magnon Coupling in a Two-Dimensional Array of Square Shaped Nanomagnets

Author: Barman, Swapnil, Pal, Pratap Kumar, and Mitra, Rajib Kumar
Subjects: Condensed Matter - Mesoscale and Nanoscale Physics, Quantum Physics
Abstract: The field of hybrid magnonics has gained significant momentum in recent years, driven by its potential to enable coherent information transfer and quantum transduction. This study delves into the tunable magnon-magnon coupling within a two-dimensional array of Ni80Fe20 (Permalloy) square nanomagnets by modulating its internal magnetic field configuration. Using a broadband ferromagnetic resonance (FMR) spectroscopy, we systematically investigate the influence of the orientation of external magnetic field and microwave power on the coupling properties. Our findings reveal a pronounced anticrossing behavior, indicative of robust magnon-magnon coupling, whose strength can be tuned through both static and dynamic external parameters. The ability to modulate coupling strengths in this system highlights its potential for developing flexible and adaptive magnonic devices, crucial for future applications in quantum information processing and spintronic technologies. This work not only broadens the understanding of magnon-magnon interactions in complex geometries but also opens new avenues for the design of next-generation quantum magnonic systems.
Published: 2024

22. vTune: Verifiable Fine-Tuning for LLMs Through Backdooring

Author: Zhang, Eva, Pal, Arka, Potti, Akilesh, and Goldblum, Micah
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computers and Society
Abstract: As fine-tuning large language models (LLMs) becomes increasingly prevalent, users often rely on third-party services with limited visibility into their fine-tuning processes. This lack of transparency raises the question: how do consumers verify that fine-tuning services are performed correctly? For instance, a service provider could claim to fine-tune a model for each user, yet simply send all users back the same base model. To address this issue, we propose vTune, a simple method that uses a small number of backdoor data points added to the training data to provide a statistical test for verifying that a provider fine-tuned a custom model on a particular user's dataset. Unlike existing works, vTune is able to scale to verification of fine-tuning on state-of-the-art LLMs, and can be used both with open-source and closed-source models. We test our approach across several model families and sizes as well as across multiple instruction-tuning datasets, and find that the statistical test is satisfied with p-values on the order of $\sim 10^{-40}$, with no negative impact on downstream task performance. Further, we explore several attacks that attempt to subvert vTune and demonstrate the method's robustness to these attacks.
Published: 2024

23. The Empirical Impact of Data Sanitization on Language Models

Author: Pal, Anwesan, Bhargava, Radhika, Hinsz, Kyle, Esterhuizen, Jacques, and Bhattacharya, Sudipta
Subjects: Computer Science - Computation and Language
Abstract: Data sanitization in the context of language modeling involves identifying sensitive content, such as personally identifiable information (PII), and redacting them from a dataset corpus. It is a common practice used in natural language processing (NLP) to maintain privacy. Nevertheless, the impact of data sanitization on the language understanding capability of a language model remains less studied. This paper empirically analyzes the effects of data sanitization across several benchmark language-modeling tasks including comprehension question answering (Q&A), entailment, sentiment analysis, and text classification. Our experiments cover a wide spectrum comprising finetuning small-scale language models, to prompting large language models (LLMs), on both original and sanitized datasets, and comparing their performance across the tasks. Interestingly, our results suggest that for some tasks such as sentiment analysis or entailment, the impact of redaction is quite low, typically around 1-5%, while for tasks such as comprehension Q&A there is a big drop of >25% in performance observed in redacted queries as compared to the original. For tasks that have a higher impact, we perform a deeper dive to inspect the presence of task-critical entities. Finally, we investigate correlation between performance and number of redacted entities, and also suggest a strategy to repair an already redacted dataset by means of content-based subsampling. Additional details are available at https://sites.google.com/view/datasan., Comment: Paper accepted at Safe Generative AI Workshop at NeurIPS 2024
Published: 2024

24. First Identification and Chemical Modeling of New Thiol ($-$SH) Bearing Molecule in the Interstellar Medium: Dithioformic Acid

Author: Manna, Arijit and Pal, Sabyasachi
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: The study of complex organic molecules containing thiol ($-$SH) groups is essential in interstellar media because $-$SH plays an important role in the polymerization of amino acids (R-CH(NH$_{2}$)-COOH). Some quantum chemical studies have shown that there is a high chance of detecting the emission lines of dithioformic acid (HC(S)SH) in the highly dense and warm-inner regions of hot molecular cores and hot corinos. Therefore, we attempted to search for the emission lines of HC(S)SH toward the highly dense hot corino object NGC 1333 IRAS 4A using the Atacama Large Millimeter/Submillimeter Array (ALMA) band 7. We present the first detection of the rotational emission lines of the trans-conformer of dithioformic acid (t-HC(S)SH) toward the NGC 1333 IRAS 4A2. The column density and excitation temperature of the t-HC(S)SH toward NGC 1333 IRAS 4A2 are (2.63$\pm$0.32)$\times$10$^{15}$ cm$^{-2}$ and 255$\pm$32 K, respectively. The fractional abundance of t-HC(S)SH with respect to H$_{2}$ is (2.53$\pm$0.68)$\times$10$^{-9}$. The column density ratio of t-HC(S)SH and t-HCOOH toward NGC 1333 IRAS 4A2 is 0.36$\pm$0.02. To understand the possible formation pathways of HC(S)SH, we computed a two-phase warm-up chemical model abundance of HC(S)SH using the gas-grain chemical code UCLCHEM. After chemical modeling, we claim that HC(S)SH is formed in NGC 1333 IRAS 4A2 via barrierless radical--radical reactions between CSSH and H on the grain surfaces., Comment: Published in ACS Earth and Space Chemistry
Published: 2024
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25. A Lightweight QoS-Aware Resource Allocation Method for NR-V2X Networks

Author: Saxena, Chitranshi, Thakur, Krishna Pal, Mukherjee, Deb, Behera, Sadananda, and Palit, Basabdatta
Subjects: Computer Science - Networking and Internet Architecture, Electrical Engineering and Systems Science - Signal Processing
Abstract: Vehicle-to-Everything (V2X) communication, which includes Vehicle-to-Infrastructure (V2I), Vehicle-to-Vehicle (V2V), and Vehicle-to-Pedestrian (V2P) networks, is gaining significant attention due to the rise of connected and autonomous vehicles. V2X systems require diverse Quality of Service (QoS) provisions, with V2V communication demanding stricter latency and reliability compared to V2I. The 5G New Radio-V2X (NR-V2X) standard addresses these needs using multi-numerology Orthogonal Frequency Division Multiple Access (OFDMA), which allows for flexible allocation of radio resources. However, V2I and V2V users sharing the same radio resources leads to interference, necessitating efficient power and resource allocation. In this work, we propose a novel resource allocation and sharing algorithm for 5G-based V2X systems. Our approach first groups Resource Blocks (RBs) into Resource Chunks (RCs) and allocates them to V2I users using the Gale-Shapley stable matching algorithm. Power is then allocated to RCs to facilitate efficient resource sharing between V2I and V2V users through a bisection search method. Finally, the Gale-Shapley algorithm is used to pair V2I and V2V users, maintaining low computational complexity while ensuring high performance. Simulation results demonstrate that our proposed Gale-Shapley Resource Allocation with Gale-Shapley Sharing (GSRAGS) achieves competitive performance with lower complexity compared to existing works while effectively meeting the QoS demands of V2X communication systems., Comment: 8 pages, 10 figures
Published: 2024

26. A GMRT 610 MHz radio survey of the North Ecliptic Pole (NEP, ADF-N) / Euclid Deep Field North

Author: White, Glenn J., Barrufet, L., Serjeant, S., Pearson, C. P., Sedgwick, C., Pal, S., Shimwell, T. W., Sirothia, S. K., Chiu, P., Oi, N., Takagi, T., Shim, H., Matsuhara, H., Patra, D., Malkan, M., Kim, H. K., Nakagawa, T., Malek, K., Burgarella, D., and Ishigaki, T.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: This paper presents a 610 MHz radio survey covering 1.94 square degrees around the North Ecliptic Pole (NEP), which includes parts of the AKARI (ADF-N) and Euclid, Deep Fields North. The median 5-sigma sensitivity is 28 microJy beam per beam, reaching as low as 19 microJy per beam, with a synthesised beam of 3.6 x 4.1 arcsec. The catalogue contains 1675 radio components, with 339 grouped into multi-component sources and 284 isolated components likely part of double radio sources. Imaging, cataloguing, and source identification are presented, along with preliminary scientific results. From a non-statistical sub-set of 169 objects with multi-wavelength AKARI and other detections, luminous infrared galaxies (LIRGs) represent 66 percent of the sample, ultra-luminous infrared galaxies (ULIRGs) 4 percent, and sources with L_IR < 1011 L_sun 30 percent. In total, 56 percent of sources show some AGN presence, though only seven are AGN-dominated. ULIRGs require three times higher AGN contribution to produce high-quality SED fits compared to lower luminosity galaxies, and AGN presence increases with AGN fraction. The PAH mass fraction is insignificant, although ULIRGs have about half the PAH strength of lower IR-luminosity galaxies. Higher luminosity galaxies show gas and stellar masses an order of magnitude larger, suggesting higher star formation rates. For LIRGs, AGN presence increases with redshift, indicating that part of the total luminosity could be contributed by AGN activity rather than star formation. Simple cross-matching revealed 13 ROSAT QSOs, 45 X-ray sources, and 61 sub-mm galaxies coincident with GMRT radio sources.
Published: 2024
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27. The co-evolution of direct, indirect and generalized reciprocity

Author: Pal, Saptarshi, Hilbe, Christian, and Glynatsi, Nikoleta E
Subjects: Quantitative Biology - Populations and Evolution
Abstract: People often engage in costly cooperation, especially in repeated interactions. When deciding whether to cooperate, individuals typically take into account how others have acted in the past. For instance, when one person is deciding whether to cooperate with another, they may consider how they were treated by the other party (direct reciprocity), how the other party treated others (indirect reciprocity), or how they themselves were treated by others in general (generalized reciprocity). Given these different approaches, it is unclear which strategy, or more specifically which mode of reciprocity, individuals will prefer. This study introduces a model where individuals decide how much weight to give each type of information when choosing to cooperate. Through equilibrium analysis, we find that all three modes of reciprocity can be sustained when individuals have sufficiently frequent interactions. However, the existence of such equilibria does not guarantee that individuals will learn to use them. Simulations show that when individuals mainly imitate others, generalized reciprocity often hinders cooperation, leading to defection even under conditions favorable to cooperation. In contrast, when individuals explore new strategies during learning, stable cooperation emerges through direct reciprocity. This study highlights the importance of studying all forms of reciprocity in unison.
Published: 2024

28. ALMA and GMRT Studies of Dust Continuum Emission and Spectral Lines Toward Oort Cloud Comet C/2022 E3 (ZTF)

Author: Manna, Arijit, Pal, Sabyasachi, Sinha, Sekhar, and Mondal, Sushanta Kumar
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: The atomic and molecular compounds of cometary ices serve as valuable knowledge into the chemical and physical properties of the outer solar nebula, where comets are formed. From the cometary atmospheres, the atoms and gas-phase molecules arise mainly in three ways: (i) the outgassing from the nucleus, (ii) the photochemical process, and (iii) the sublimation of icy grains from the nucleus. In this paper, we present the radio and millimeter wavelength observation results of Oort cloud non-periodic comet C/2022 E3 (ZTF) using the Giant Metrewave Radio Telescope (GMRT) band L and the Atacama Large Millimeter/Submillimeter Array (ALMA) band 6. We do not detect continuum emissions and an emission line of atomic hydrogen (HI) at rest frequency 1420 MHz from this comet using the GMRT. Based on ALMA observations, we detect the dust continuum emission and rotational emission lines of methanol (CH$_{3}$OH) from comet C/2022 E3 (ZTF). From the dust continuum emission, the activity of dust production (Af$\rho$) of comet ZTF is 2280$\pm$50 cm. Based on LTE spectral modelling, the column density and excitation temperature of CH$_{3}$OH towards C/2022 E3 (ZTF) are (4.50$\pm$0.25)$\times$10$^{14}$ cm$^{-2}$ and 70$\pm$3 K. The integrated emission maps show that CH$_{3}$OH was emitted from the coma region of the comet. The production rate of CH$_{3}$OH towards C/2022 E3 (ZTF) is (7.32$\pm$0.64)$\times$10$^{26}$ molecules s$^{-1}$. The fractional abundance of CH$_{3}$OH with respect to H$_{2}$O in the coma of the comet is 1.52%. We also compare our derived abundance of CH$_{3}$OH with the existence modelled value, and we see the observed and modelled values are nearly similar. We claim that CH$_{3}$OH is formed via the subsequential hydrogenation of formaldehyde (H$_{2}$CO) on the grain surface of comet C/2022 E3 (ZTF)., Comment: Accepted for publication in Research in Astronomy and Astrophysics (RAA)
Published: 2024

29. Empowering Library Users: Creative Strategies for Engagement and Innovation

Author: Paul, Snehasish, Chauhan, Shivali, and Pal, Atul Kumar
Subjects: Computer Science - Digital Libraries
Abstract: This study investigated the integration of cutting-edge technologies and methodologies for creating dynamic, user-centered library environments. In creative strategies for engagement and innovation, library users must be empowered to undertake the new role of modernizing library services and enhancing user experiences. It also enhances the information management and user engagement. This can be attained from personalized approaches, such as recommendation systems to interactive platforms that will have effective experiences tailored to users of different natures. It investigates the consumer engagement practices of enthusiasm, sharing, and learning about their roles in cognitive, affective, and behavioural engagements. Combined, these new approaches will help promote learning, interaction, and growth, add value, and have a more positive impact on users. The challenge for libraries in this rapidly changing, technologically advancing, and digitally networked world, with a base of expectant users, is to remain relevant and engaging. This study discusses innovative strategies for empowering library users and enhancing their engagement through creative and technological approaches. This investigation was conducted to integrate cutting-edge technologies and methodologies into creating dynamic library settings that are user-centered and foster learning, interaction, and personal growth.
Published: 2024

30. MuCol Milestone Report No. 5: Preliminary Parameters

Author: Accettura, Carlotta, Adrian, Simon, Agarwal, Rohit, Ahdida, Claudia, Aimé, Chiara, Aksoy, Avni, Alberghi, Gian Luigi, Alden, Siobhan, Alfonso, Luca, Amapane, Nicola, Amorim, David, Andreetto, Paolo, Anulli, Fabio, Appleby, Rob, Apresyan, Artur, Asadi, Pouya, Mahmoud, Mohammed Attia, Auchmann, Bernhard, Back, John, Badea, Anthony, Bae, Kyu Jung, Bahng, E. J., Balconi, Lorenzo, Balli, Fabrice, Bandiera, Laura, Barbagallo, Carmelo, Barlow, Roger, Bartoli, Camilla, Bartosik, Nazar, Barzi, Emanuela, Batsch, Fabian, Bauce, Matteo, Begel, Michael, Berg, J. Scott, Bersani, Andrea, Bertarelli, Alessandro, Bertinelli, Francesco, Bertolin, Alessandro, Bhat, Pushpalatha, Bianchi, Clarissa, Bianco, Michele, Bishop, William, Black, Kevin, Boattini, Fulvio, Bogacz, Alex, Bonesini, Maurizio, Bordini, Bernardo, de Sousa, Patricia Borges, Bottaro, Salvatore, Bottura, Luca, Boyd, Steven, Breschi, Marco, Broggi, Francesco, Brunoldi, Matteo, Buffat, Xavier, Buonincontri, Laura, Burrows, Philip Nicholas, Burt, Graeme Campbell, Buttazzo, Dario, Caiffi, Barbara, Calatroni, Sergio, Calviani, Marco, Calzaferri, Simone, Calzolari, Daniele, Cantone, Claudio, Capdevilla, Rodolfo, Carli, Christian, Carrelli, Carlo, Casaburo, Fausto, Casarsa, Massimo, Castelli, Luca, Catanesi, Maria Gabriella, Cavallucci, Lorenzo, Cavoto, Gianluca, Celiberto, Francesco Giovanni, Celona, Luigi, Cemmi, Alessia, Ceravolo, Sergio, Cerri, Alessandro, Cerutti, Francesco, Cesarini, Gianmario, Cesarotti, Cari, Chancé, Antoine, Charitonidis, Nikolaos, Chiesa, Mauro, Chiggiato, Paolo, Ciccarella, Vittoria Ludovica, Puviani, Pietro Cioli, Colaleo, Anna, Colao, Francesco, Collamati, Francesco, Costa, Marco, Craig, Nathaniel, Curtin, David, Damerau, Heiko, Da Molin, Giacomo, D'Angelo, Laura, Dasu, Sridhara, de Blas, Jorge, De Curtis, Stefania, De Gersem, Herbert, Delahaye, Jean-Pierre, Del Moro, Tommaso, Denisov, Dmitri, Denizli, Haluk, Dermisek, Radovan, Valdor, Paula Desiré, Desponds, Charlotte, Di Luzio, Luca, Di Meco, Elisa, Diociaiuti, Eleonora, Di Petrillo, Karri Folan, Di Sarcina, Ilaria, Dorigo, Tommaso, Dreimanis, Karlis, Pree, Tristan du, Yildiz, Hatice Duran, Edgecock, Thomas, Fabbri, Siara, Fabbrichesi, Marco, Farinon, Stefania, Ferrand, Guillaume, Somoza, Jose Antonio Ferreira, Fieg, Max, Filthaut, Frank, Fox, Patrick, Franceschini, Roberto, Ximenes, Rui Franqueira, Gallinaro, Michele, Garcia-Sciveres, Maurice, Garcia-Tabares, Luis, Gargiulo, Ruben, Garion, Cedric, Garzelli, Maria Vittoria, Gast, Marco, Generoso, Lisa, Gerber, Cecilia E., Giambastiani, Luca, Gianelle, Alessio, Gianfelice-Wendt, Eliana, Gibson, Stephen, Gilardoni, Simone, Giove, Dario Augusto, Giovinco, Valentina, Giraldin, Carlo, Glioti, Alfredo, Gorzawski, Arkadiusz, Greco, Mario, Grojean, Christophe, Grudiev, Alexej, Gschwendtner, Edda, Gueli, Emanuele, Guilhaudin, Nicolas, Han, Chengcheng, Han, Tao, Hauptman, John Michael, Herndon, Matthew, Hillier, Adrian D, Hillman, Micah, Holmes, Tova Ray, Homiller, Samuel, Jana, Sudip, Jindariani, Sergo, Johannesson, Sofia, Johnson, Benjamin, Jones, Owain Rhodri, Jurj, Paul-Bogdan, Kahn, Yonatan, Kamath, Rohan, Kario, Anna, Karpov, Ivan, Kelliher, David, Kilian, Wolfgang, Kitano, Ryuichiro, Kling, Felix, Kolehmainen, Antti, Kong, K. C., Kosse, Jaap, Krintiras, Georgios, Krizka, Karol, Kumar, Nilanjana, Kvikne, Erik, Kyle, Robert, Laface, Emanuele, Lane, Kenneth, Latina, Andrea, Lechner, Anton, Lee, Junghyun, Lee, Lawrence, Lee, Seh Wook, Lefevre, Thibaut, Leonardi, Emanuele, Lerner, Giuseppe, Li, Peiran, Li, Qiang, Li, Tong, Li, Wei, Lindroos, Mats, Lipton, Ronald, Liu, Da, Liu, Miaoyuan, Liu, Zhen, Voti, Roberto Li, Lombardi, Alessandra, Lomte, Shivani, Long, Kenneth, Longo, Luigi, Lorenzo, José, Losito, Roberto, Low, Ian, Lu, Xianguo, Lucchesi, Donatella, Luo, Tianhuan, Lupato, Anna, Ma, Yang, Machida, Shinji, Madlener, Thomas, Magaletti, Lorenzo, Maggi, Marcello, Durand, Helene Mainaud, Maltoni, Fabio, Manczak, Jerzy Mikolaj, Mandurrino, Marco, Marchand, Claude, Mariani, Francesco, Marin, Stefano, Mariotto, Samuele, Martin-Haugh, Stewart, Masullo, Maria Rosaria, Mauro, Giorgio Sebastiano, Mazzolari, Andrea, Mękała, Krzysztof, Mele, Barbara, Meloni, Federico, Meng, Xiangwei, Mentink, Matthias, Métral, Elias, Miceli, Rebecca, Milas, Natalia, Mohammadi, Abdollah, Moll, Dominik, Montella, Alessandro, Morandin, Mauro, Morrone, Marco, Mulder, Tim, Musenich, Riccardo, Nardecchia, Marco, Nardi, Federico, Nenna, Felice, Neuffer, David, Newbold, David, Novelli, Daniel, Olvegård, Maja, Onel, Yasar, Orestano, Domizia, Osborne, John, Otten, Simon, Torres, Yohan Mauricio Oviedo, Paesani, Daniele, Griso, Simone Pagan, Pagani, Davide, Pal, Kincso, Palmer, Mark, Pampaloni, Alessandra, Panci, Paolo, Pani, Priscilla, Papaphilippou, Yannis, Paparella, Rocco, Paradisi, Paride, Passeri, Antonio, Pasternak, Jaroslaw, Pastrone, Nadia, Pellecchia, Antonello, Piccinini, Fulvio, Piekarz, Henryk, Pieloni, Tatiana, Plouin, Juliette, Portone, Alfredo, Potamianos, Karolos, Potdevin, Joséphine, Prestemon, Soren, Puig, Teresa, Qiang, Ji, Quettier, Lionel, Rabemananjara, Tanjona Radonirina, Radicioni, Emilio, Radogna, Raffaella, Rago, Ilaria Carmela, Ratkus, Andris, Resseguie, Elodie, Reuter, Juergen, Ribani, Pier Luigi, Riccardi, Cristina, Ricciardi, Stefania, Robens, Tania, Robert, Youri, Rogers, Chris, Rojo, Juan, Romagnoni, Marco, Ronald, Kevin, Rosser, Benjamin, Rossi, Carlo, Rossi, Lucio, Rozanov, Leo, Ruhdorfer, Maximilian, Ruiz, Richard, Saini, Saurabh, Sala, Filippo, Salierno, Claudia, Salmi, Tiina, Salvini, Paola, Salvioni, Ennio, Sammut, Nicholas, Santini, Carlo, Saputi, Alessandro, Sarra, Ivano, Scarantino, Giuseppe, Schneider-Muntau, Hans, Schulte, Daniel, Scifo, Jessica, Sen, Tanaji, Senatore, Carmine, Senol, Abdulkadir, Sertore, Daniele, Sestini, Lorenzo, Rêgo, Ricardo César Silva, Simone, Federica Maria, Skoufaris, Kyriacos, Sorbello, Gino, Sorbi, Massimo, Sorti, Stefano, Soubirou, Lisa, Spataro, David, Queiroz, Farinaldo S., Stamerra, Anna, Stapnes, Steinar, Stark, Giordon, Statera, Marco, Stechauner, Bernd Michael, Su, Shufang, Su, Wei, Sun, Xiaohu, Sytov, Alexei, Tang, Jian, Tang, Jingyu, Taylor, Rebecca, Kate, Herman Ten, Testoni, Pietro, Thiele, Leonard Sebastian, Garcia, Rogelio Tomas, Topp-Mugglestone, Max, Torims, Toms, Torre, Riccardo, Tortora, Luca, Tortora, Ludovico, Trifinopoulos, Sokratis, Udongwo, Sosoho-Abasi, Vai, Ilaria, Valente, Riccardo Umberto, van Rienen, Ursula, Van Weelderen, Rob, Vanwelde, Marion, Velev, Gueorgui, Venditti, Rosamaria, Vendrasco, Adam, Verna, Adriano, Vernassa, Gianluca, Verweij, Arjan, Verwilligen, Piet, Villamizar, Yoxara, Vittorio, Ludovico, Vitulo, Paolo, Vojskovic, Isabella, Wang, Dayong, Wang, Lian-Tao, Wang, Xing, Wendt, Manfred, Widorski, Markus, Wozniak, Mariusz, Wu, Yongcheng, Wulzer, Andrea, Xie, Keping, Yang, Yifeng, Yap, Yee Chinn, Yonehara, Katsuya, Yoo, Hwi Dong, You, Zhengyun, Zanetti, Marco, Zaza, Angela, Zhang, Liang, Zhu, Ruihu, Zlobin, Alexander, Zuliani, Davide, and Zurita, José Francisco
Subjects: Physics - Accelerator Physics
Abstract: This document is comprised of a collection of updated preliminary parameters for the key parts of the muon collider. The updated preliminary parameters follow on from the October 2023 Tentative Parameters Report. Particular attention has been given to regions of the facility that are believed to hold greater technical uncertainty in their design and that have a strong impact on the cost and power consumption of the facility. The data is collected from a collaborative spreadsheet and transferred to overleaf.
Published: 2024
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31. Scar-induced imbalance in staggered Rydberg ladders

Author: Pal, Mainak, Sarkar, Madhumita, Sengupta, K., and Sen, Arnab
Subjects: Quantum Physics, Condensed Matter - Strongly Correlated Electrons
Abstract: We demonstrate that the kinematically-constrained model of Rydberg atoms on a two-leg ladder with staggered detuning, $\Delta \in [0,1]$, has quantum many-body scars (QMBS) in its spectrum and represents a non-perturbative generalization of the paradigmatic PXP model defined on a chain. We show that these QMBS result in coherent many-body revivals and site-dependent magnetization dynamics for both N\'eel and Rydberg vacuum initial states around $\Delta=1$. The latter feature leads to eigenstate thermalization hypothesis (ETH)-violating finite imbalance at long times in a disorder free system. This is further demonstrated by constructing appropriate local imbalance operators that display finite long-time averages for N\'eel and vacuum initial states. We also study the fidelity and Shannon entropy for such dynamics which, along with the presence of long-time finite imbalance, brings out the qualitatively different nature of QMBS in PXP ladders with $\Delta \sim 1$ from those in the PXP chain., Comment: v1; 4+$\epsilon$ pages; 3 figs; Supplementary Materials attached
Published: 2024

32. Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning

Author: Arefin, Md Rifat, Subbaraj, Gopeshh, Gontier, Nicolas, LeCun, Yann, Rish, Irina, Shwartz-Ziv, Ravid, and Pal, Christopher
Subjects: Computer Science - Machine Learning, Computer Science - Computation and Language
Abstract: Decoder-only Transformers often struggle with complex reasoning tasks, particularly arithmetic reasoning requiring multiple sequential operations. In this work, we identify representation collapse in the model's intermediate layers as a key factor limiting their reasoning capabilities. To address this, we propose Sequential Variance-Covariance Regularization (Seq-VCR), which enhances the entropy of intermediate representations and prevents collapse. Combined with dummy pause tokens as substitutes for chain-of-thought (CoT) tokens, our method significantly improves performance in arithmetic reasoning problems. In the challenging $5 \times 5$ integer multiplication task, our approach achieves $99.5\%$ exact match accuracy, outperforming models of the same size (which yield $0\%$ accuracy) and GPT-4 with five-shot CoT prompting ($44\%$). We also demonstrate superior results on arithmetic expression and longest increasing subsequence (LIS) datasets. Our findings highlight the importance of preventing intermediate layer representation collapse to enhance the reasoning capabilities of Transformers and show that Seq-VCR offers an effective solution without requiring explicit CoT supervision.
Published: 2024

33. Theoretical characterisation of the Gauss-Newton conditioning in Neural Networks

Author: Zhao, Jim, Singh, Sidak Pal, and Lucchi, Aurelien
Subjects: Computer Science - Machine Learning, Statistics - Machine Learning
Abstract: The Gauss-Newton (GN) matrix plays an important role in machine learning, most evident in its use as a preconditioning matrix for a wide family of popular adaptive methods to speed up optimization. Besides, it can also provide key insights into the optimization landscape of neural networks. In the context of deep neural networks, understanding the GN matrix involves studying the interaction between different weight matrices as well as the dependencies introduced by the data, thus rendering its analysis challenging. In this work, we take a first step towards theoretically characterizing the conditioning of the GN matrix in neural networks. We establish tight bounds on the condition number of the GN in deep linear networks of arbitrary depth and width, which we also extend to two-layer ReLU networks. We expand the analysis to further architectural components, such as residual connections and convolutional layers. Finally, we empirically validate the bounds and uncover valuable insights into the influence of the analyzed architectural components.
Published: 2024

34. Very High-energy Gamma-Ray Episodic Activity of Radio Galaxy NGC 1275 in 2022-2023 Measured with MACE

Author: Godambe, S., Mankuzhiyil, N., Borwankar, C., Ghosal, B., Tolamatti, A., Pal, M., Chandra, P., Khurana, M., Pandey, P., Dar, Z. A., Godiyal, S., Hariharan, J., Anand, Keshav, Norlha, S., Sarkar, D., Thubstan, R., Venugopal, K., Pathania, A., Kotwal, S., Kumar, Raj, Bhatt, N., Chanchalani, K., Das, M., Singh, K. K., Gour, K. K., Kothari, M., Kumar, Nandan, Kumar, Naveen, Marandi, P., Kushwaha, C. P., Koul, M. K., Dorjey, P., Dorji, N., Chitnis, V. R., Rannot, R. C., Bhattacharyya, S., Chouhan, N., Dhar, V. K., Sharma, M., and Yadav, K. K.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: The radio galaxy NGC 1275, located at the central region of Perseus cluster, is a well-known very high-energy (VHE) gamma-ray emitter. The Major Atmospheric Cherenkov Experiment Telescope has detected two distinct episodes of VHE (E > 80 GeV) gamma-ray emission from NGC 1275 during 2022 December and 2023 January. The second outburst, observed on 2023 January 10, was the more intense of the two, with flux reaching 58$\%$ of the Crab Nebula flux above 80 GeV. The differential energy spectrum measured between 80 GeV and 1.5 TeV can be described by a power law with a spectral index of $\Gamma = - 2.90 \pm 0.16_{stat}$ for both flaring events. The broadband spectral energy distribution derived from these flares, along with quasisimultaneous low-energy counterparts, suggests that the observed gamma-ray emission can be explained using a homogeneous single-zone synchrotron self-Compton model. The physical parameters derived from this model for both flaring states are similar. The intermediate state observed between two flaring episodes is explained by a lower Doppler factor or magnetic field, which subsequently returned to its previous value during the high-activity state observed on 2023 January 10., Comment: 7 Pages, 5 Figures, and 1 Table
Published: 2024
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35. Spectral set, complete spectral set and dilation for Banach space operators

Author: Jana, Swapan and Pal, Sourav
Subjects: Mathematics - Functional Analysis, Mathematics - Complex Variables, Mathematics - Operator Algebras
Abstract: Famous results due to von Neumann, Sz.-Nagy and Arveson assert that the following four statements are equivalent; a Hilbert space operator $T$ is a contraction; the closed unit disk $\overline{\mathbb D}$ is a spectral set for $T$; $T$ can be dilated to a Hilbert space isometry; $\overline{\mathbb D}$ is a complete spectral set for $T$. In this article, we show by counter examples that no two of them are equivalent for Banach space operators. If $\mathcal F_r$ is the family of all Banach space operators having norm less than or equal to $r$ and if $D_R$ denotes the open disk in the complex plane with centre at the origin and radius $R$, then we prove by an application of Bohr's theorem that $\overline{D}_R$ is the minimal spectral set for $\mathcal F_r$ if and only if $r=\frac{R}{3}$. Also, we prove the equivalence of the following two facts: the Bohr radius of $D_R$ is $\frac{R}{3}$ and $\sup \{ r>0\,:\, \overline{D}_R \text{ is a spectral set for } \mathcal F_r \}=\frac{R}{3}$. We found several new characterizations for a Hilbert space in terms of spectral set and complete spectral set for different operators., Comment: 15 pages
Published: 2024

36. Characterization of more than three years of in-orbit radiation damage of SiPMs on GRBAlpha and VZLUSAT-2 CubeSats

Author: Ripa, Jakub, Dafcikova, Marianna, Kosik, Pavel, Münz, Filip, Ohno, Masanori, Galgoczi, Gabor, Werner, Norbert, Pal, Andras, Meszaros, Laszlo, Csak, Balazs, Fukazawa, Yasushi, Takahashi, Hiromitsu, Mizuno, Tsunefumi, Nakazawa, Kazuhiro, Odaka, Hirokazu, Ichinohe, Yuto, Kapus, Jakub, Hudec, Jan, Frajt, Marcel, Rezenov, Maksim, Daniel, Vladimir, Svoboda, Petr, Dudas, Juraj, Sabol, Martin, Laszlo, Robert, Koleda, Martin, Duriskova, Michaela, Szakszonova, Lea, Kolar, Martin, Husarikova, Nikola, Breuer, Jean-Paul, Hroch, Filip, Vitek, Tomas, Vertat, Ivo, Urbanec, Tomas, Povalac, Ales, Kasal, Miroslav, Hanak, Peter, smelko, Miroslav, Topinka, Martin, Chang, Hsiang-Kuang, Liu, Tsung-Che, Lin, Chih-Hsun, Hu, Chin-Ping, and Tsao, Che-Chih
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Physics - Instrumentation and Detectors
Abstract: It is well known that silicon photomultipliers (SiPMs) are prone to radiation damage. With the increasing popularity of SiPMs among new spaceborne missions, especially on CubeSats, it is of paramount importance to characterize their performance in space environment. In this work, we report the in-orbit ageing of SiPM arrays, so-called multi-pixel photon counters (MPPCs), using measurements acquired by the GRBAlpha and VZLUSAT-2 CubeSats at low Earth orbit (LEO) spanning over three years, which in duration is unique. GRBAlpha is a 1U CubeSat launched on March 22, 2021, to a 550 km altitude sun-synchronous polar orbit (SSO) carrying on board a gamma-ray detector based on CsI(Tl) scintillator readout by eight MPPCs and regularly detecting gamma-ray transients such as gamma-ray bursts and solar flares in the energy range of ~30-900 keV. VZLUSAT-2 is a 3U CubeSat launched on January 13, 2022 also to a 550 km altitude SSO carrying on board, among other payloads, two gamma-ray detectors similar to the one on GRBAlpha. We have flight-proven the Hamamatsu MPPCs S13360-3050 PE and demonstrated that MPPCs, shielded by 2.5 mm of PbSb alloy, can be used in an LEO environment on a scientific mission lasting beyond three years. This manifests the potential of MPPCs being employed in future satellites., Comment: Submitted to Nuclear Instruments and Methods in Physics Research Section A, 13 pages, 14 figures
Published: 2024

37. Neural Model Checking

Author: Giacobbe, Mirco, Kroening, Daniel, Pal, Abhinandan, and Tautschnig, Michael
Subjects: Computer Science - Logic in Computer Science, Computer Science - Machine Learning
Abstract: We introduce a machine learning approach to model checking temporal logic, with application to formal hardware verification. Model checking answers the question of whether every execution of a given system satisfies a desired temporal logic specification. Unlike testing, model checking provides formal guarantees. Its application is expected standard in silicon design and the EDA industry has invested decades into the development of performant symbolic model checking algorithms. Our new approach combines machine learning and symbolic reasoning by using neural networks as formal proof certificates for linear temporal logic. We train our neural certificates from randomly generated executions of the system and we then symbolically check their validity using satisfiability solving which, upon the affirmative answer, establishes that the system provably satisfies the specification. We leverage the expressive power of neural networks to represent proof certificates as well as the fact that checking a certificate is much simpler than finding one. As a result, our machine learning procedure for model checking is entirely unsupervised, formally sound, and practically effective. We experimentally demonstrate that our method outperforms the state-of-the-art academic and commercial model checkers on a set of standard hardware designs written in SystemVerilog., Comment: To appear in NeurIPS 2024
Published: 2024

38. A proof of a conjecture on trivariate permutations

Author: Bartoli, Daniele, Pal, Mohit, Stanica, Pantelimon, and Toccotelli, Tommaso
Subjects: Mathematics - Number Theory, Computer Science - Information Theory, Mathematics - Algebraic Geometry, Mathematics - Combinatorics, 12E20, 11T06
Abstract: In this note we show (for a large enough dimension of the underlying field) a conjecture of [C. Beierle, C. Carlet, G. Leander, L. Perrin, {\em A further study of quadratic APN permutations in dimension nine}, Finite Fields Appl. 81 (2022), 102049] on a trivariate permutation. This function is a global representation of two new sporadic quadratic APN permutations in dimension $9$ found by [C. Beierle, G. Leander, {\em New instances of quadratic APN functions}, IEEE Trans. Inf. Theory 68(1) (2022), 670--678].
Published: 2024

39. A proof of a conjecture on permutation trinomials

Author: Bartoli, Daniele, Pal, Mohit, and Stanica, Pantelimon
Subjects: Mathematics - Number Theory, Mathematics - Algebraic Geometry, 11G20, 11T06, 12E20, 14Q10
Abstract: In this paper we use algebraic curves and other algebraic number theory methods to show the validity of a permutation polynomial conjecture regarding $f(X)=X^{q(p-1)+1} +\alpha X^{pq}+X^{q+p-1}$, on finite fields $\mathbb{F}_{q^2}, q=p^k$, from [A. Rai, R. Gupta, {\it Further results on a class of permutation trinomials}, Cryptogr. Commun. 15 (2023), 811--820].
Published: 2024

40. SoccerGuard: Investigating Injury Risk Factors for Professional Soccer Players with Machine Learning

Author: Bartels, Finn, Xing, Lu, Midoglu, Cise, Boeker, Matthias, Kirsten, Toralf, and Halvorsen, Pål
Subjects: Computer Science - Human-Computer Interaction, Computer Science - Machine Learning
Abstract: We present SoccerGuard, a novel framework for predicting injuries in women's soccer using Machine Learning (ML). This framework can ingest data from multiple sources, including subjective wellness and training load reports from players, objective GPS sensor measurements, third-party player statistics, and injury reports verified by medical personnel. We experiment with a number of different settings related to synthetic data generation, input and output window sizes, and ML models for prediction. Our results show that, given the right configurations and feature combinations, injury event prediction can be undertaken with considerable accuracy. The optimal results are achieved when input windows are reduced and larger combined output windows are defined, in combination with an ideally balanced data set. The framework also includes a dashboard with a user-friendly Graphical User Interface (GUI) to support interactive analysis and visualization.
Published: 2024

41. Long time behavior of a stochastically modulated infinite server queue

Author: Majumder, Abhishek Pal
Subjects: Mathematics - Probability, Statistics - Computation
Abstract: We consider an infinite server queue where the arrival and the service rates are both modulated by a stochastic environment governed by an $S$-valued stochastic process $X$ that is ergodic with a limiting measure $\pi\in \mathcal{P}(S)$. Under certain conditions when $X$ is semi-Markovian and satisfies the renewal regenerative property, long-term behavior of the total counts of people in the queue (denoted by $Y:=(Y_{t}:t\ge 0)$) becomes explicit and the limiting measure of $Y$ can be described through a well-studied affine stochastic recurrence equation (SRE) $X\stackrel{d}{=}CX+D,\,\, X\perp\!\!\!\perp (C, D)$. We propose a sampling scheme from that limiting measure with explicit convergence diagnostics. Additionally, one example is presented where the stochastic environment makes the system transient, in absence of a `no-feedback' assumption., Comment: Any comments are welcome at palmabhishek@gmail.com
Published: 2024

42. Prominent mid-infrared excess of the dwarf planet (136472) Makemake discovered by JWST/MIRI indicates ongoing activity

Author: Kiss, Csaba, Müller, Thomas G., Farkas-Takács, Anikó, Moór, Attila, Protopapa, Silvia, Parker, Alex H., Santos-Sanz, Pablo, Ortiz, Jose Luis, Holler, Bryan J., Wong, Ian, Stansberry, John, Fernández-Valenzuela, Estela, Glein, Christopher R., Lellouch, Emmanuel, Vilenius, Esa, Kalup, Csilla E., Regály, Zsolt, Szakáts, Róbert, Marton, Gábor, Pál, András, and Szabó, Gyula M.
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: We report on the discovery of a very prominent mid-infrared (18-25 {\mu}m) excess associated with the trans-Neptunian dwarf planet (136472) Makemake. The excess, detected by the MIRI instrument of the James Webb Space Telescope, along with previous measurements from the Spitzer and Herschel space telescopes, indicates the occurrence of temperatures of about 150 K, much higher than what solid surfaces at Makemake's heliocentric distance could reach by solar irradiation. We identify two potential explanations: a continuously visible, currently active region, powered by subsurface upwelling and possibly cryovolcanic activity, covering <1% of Makemake's surface, or an as yet undetected ring containing very small carbonaceous dust grains, which have not been seen before in trans-Neptunian or Centaur rings. Both scenarios point to unprecedented phenomena among trans-Neptunian objects and could greatly impact our understanding of these distant worlds., Comment: Accepted for publication in The Astrophysical Journal Letters
Published: 2024

43. Morphogenesis of Spin Cycloids in a Non-collinear Antiferromagnet

Author: Ojha, Shashank Kumar, Pal, Pratap, Prokhorenko, Sergei, Husain, Sajid, Ramesh, Maya, Meisenheimer, Peter, Schlom, Darrell G., Stevenson, Paul, Caretta, Lucas, Nahas, Yousra, Martin, Lane W., Bellaiche, Laurent, Eom, Chang-Beom, and Ramesh, Ramamoorthy
Subjects: Condensed Matter - Materials Science, Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Strongly Correlated Electrons
Abstract: Pattern formation in spin systems with continuous-rotational symmetry (CRS) provides a powerful platform to study emergent complex magnetic phases and topological defects in condensed-matter physics. However, its understanding and correlation with unconventional magnetic order along with high-resolution nanoscale imaging is challenging. Here, we employ scanning NV magnetometry to unveil the morphogenesis of spin cycloids at both the local and global scales within a single ferroelectric domain of (111)-oriented BiFeO$_3$ (which is a non-collinear antiferromagnet), resulting in formation of a glassy labyrinthine pattern. We find that the domains of locally oriented cycloids are interconnected by an array of topological defects and exhibit isotropic energy landscape predicted by first-principles calculations. We propose that the CRS of spin-cycloid propagation directions within the (111) drives the formation of the labyrinthine pattern and the associated topological defects such as antiferromagnetic skyrmions. Unexpectedly, reversing the as-grown ferroelectric polarization from [$\bar{1}$$\bar{1}$$\bar{1}$] to [111] induces a magnetic phase transition, destroying the labyrinthine pattern and producing a deterministic non-volatile non cycloidal, uniformly magnetized state. These findings highlight that (111)-oriented BiFeO$_3$ is not only important for studying the fascinating subject of pattern formation but could also be utilized as an ideal platform for integrating novel topological defects in the field of antiferromagnetic spintronics., Comment: 20 pages, 15 figures
Published: 2024

44. Symmetry controlled single spin cycloid switching in multiferroic BiFeO3

Author: Pal, Pratap, Schad, Jonathon L., Vibhakar, Anuradha M., Ojha, Shashank Kumar, Kim, Gi-Yeop, Shenoy, Saurav, Xue, Fei, Rzchowski, Mark S., Bombardi, A., Johnson, Roger D., Choi, Si-Young, Chen, Long-Qing, Ramesh, Ramamoorthy, Radaelli, Paolo G., and Eom, Chang-Beom
Subjects: Condensed Matter - Materials Science, Condensed Matter - Strongly Correlated Electrons
Abstract: The single variant spin cycloid and associated antiferromagnetic order in multiferroic BiFeO3 can provide a direct and predictable magnetoelectric coupling to ferroelectric order for deterministic switching, and also a key to fundamental understanding of spin transport and magnon-based applications in the system. (111) oriented BiFeO3 supplies an easy magnetic plane for the spin cycloid, but despite previous efforts, achieving deterministic switching of the single spin cycloid over multiple cycles remains challenging due to the presence of multiple spin cycloid domains in the (111) plane. Here we show that anisotropic in-plane strain engineering can stabilize a single antiferromagnetic domain and provide robust, deterministic switching. We grow BiFeO3 on orthorhombic NdGaO3 (011)o [(111)pc] substrates, breaking the spin cycloid degeneracy and by imposing a uniaxial strain in the (111) plane. This stabilization is confirmed through direct imaging with scanning NV microscopy and non-resonant X-ray diffraction. Remarkably, we achieved deterministic and non-volatile 180{\deg} switching of ferroelectric and associated antiferromagnetic domains over 1,000 cycles, significantly outperforming existing approaches. Our findings underscore that anisotropic strain engineering opens up exciting possibilities for (111)pc monodomain BiFeO3 in potential magnetoelectric and emerging magnonic applications., Comment: 17 pages, 4 figures
Published: 2024

45. Non-minimally coupled teleparallel scalar field reconstruction of matter bounce scenario

Author: Tripathy, S. K., Pal, Sasmita, and Mishra, B.
Subjects: General Relativity and Quantum Cosmology, High Energy Physics - Theory
Abstract: Teleparallel description of gravity theories where the gravity is mediated through the tetrad field and consequent torsion provide an alternative route to explain the late time cosmic speed up issue. Generalization of the teleparallel gravity theory with different functional forms of the torsion scalar $T$ leads to $f(T)$ gravity. The role of scalar field played in addressing issues in cosmology and astrophysics has developed an interest in the inclusion of a scalar field along with an interaction potential in the action. Such a generalized gravity theory is dubbed as $f(T,\phi)$ theory. We have explored such a gravity theory to reconstruct the interaction potential of the scalar field required for an extended matter bounce scenario. The cosmological implications of the reconstructed scalar field potential are studied considering two viable and well known functional forms of $f(T,\phi)$. The energy conditions of these model are discussed to assess the viability of the cosmological models., Comment: 14 pages, 15 figures, accepted version of Eur. Phys. J. C
Published: 2024

46. History-Matching of Imbibition Flow in Multiscale Fractured Porous Media Using Physics-Informed Neural Networks (PINNs)

Author: Abbasi, Jassem, Moseley, Ben, Kurotori, Takeshi, Jagtap, Ameya D., Kovscek, Anthony R., Hiorth, Aksel, and Andersen, Pål Østebø
Subjects: Computer Science - Computational Engineering, Finance, and Science
Abstract: We propose a workflow based on physics-informed neural networks (PINNs) to model multiphase fluid flow in fractured porous media. After validating the workflow in forward and inverse modeling of a synthetic problem of flow in fractured porous media, we applied it to a real experimental dataset in which brine is injected at a constant pressure drop into a CO2 saturated naturally fractured shale core plug. The exact spatial positions of natural fractures and the dynamic in-situ distribution of fluids were imaged using a CT-scan setup. To model the targeted system, we followed a domain decomposition approach for matrix and fractures and a multi-network architecture for the separate calculation of water saturation and pressure. The flow equations in the matrix, fractures and interplay between them were solved during training. Prior to fully-coupled simulations, we proposed pre-training the model. This aided in a more efficient and successful training of the coupled system. Both for the synthetic and experimental inverse problems, we determined flow parameters within the matrix and the fractures. Multiple random initializations of network and system parameters were performed to assess the uncertainty and uniqueness of the results. The results confirmed the precision of the inverse calculated parameters in retrieving the main flow characteristics of the system. The consideration of multiscale matrix-fracture impacts is commonly overlooked in existing workflows. Accounting for them led to several orders of magnitude variations in the calculated flow properties compared to not accounting for them. To the best of our knowledge, the proposed PINNs-based workflow is the first to offer a reliable and computationally efficient solution for inverse modeling of multiphase flow in fractured porous media, achieved through history-matching noisy and multi-fidelity experimental measurements., Comment: 47 pages of paper, including 19 figures
Published: 2024

47. PepDoRA: A Unified Peptide Language Model via Weight-Decomposed Low-Rank Adaptation

Author: Wang, Leyao, Pulugurta, Rishab, Vure, Pranay, Zhang, Yinuo, Pal, Aastha, and Chatterjee, Pranam
Subjects: Quantitative Biology - Biomolecules
Abstract: Peptide therapeutics, including macrocycles, peptide inhibitors, and bioactive linear peptides, play a crucial role in therapeutic development due to their unique physicochemical properties. However, predicting these properties remains challenging. While structure-based models primarily focus on local interactions, language models are capable of capturing global therapeutic properties of both modified and linear peptides. Protein language models like ESM-2, though effective for natural peptides, cannot however encode chemical modifications. Conversely, pre-trained chemical language models excel in representing small molecule properties but are not optimized for peptides. To bridge this gap, we introduce PepDoRA, a unified peptide representation model. Leveraging Weight-Decomposed Low-Rank Adaptation (DoRA), PepDoRA efficiently fine-tunes the ChemBERTa-77M-MLM on a masked language model objective to generate optimized embeddings for downstream property prediction tasks involving both modified and unmodified peptides. By tuning on a diverse and experimentally valid set of 100,000 modified, bioactive, and binding peptides, we show that PepDoRA embeddings capture functional properties of input peptides, enabling the accurate prediction of membrane permeability, non-fouling and hemolysis propensity, and via contrastive learning, target protein-specific binding. Overall, by providing a unified representation for chemically and biologically diverse peptides, PepDoRA serves as a versatile tool for function and activity prediction, facilitating the development of peptide therapeutics across a broad spectrum of applications.
Published: 2024

48. Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD

Author: Das, Aniket, Nagaraj, Dheeraj, Pal, Soumyabrata, Suggala, Arun, and Varshney, Prateek
Subjects: Statistics - Machine Learning, Computer Science - Machine Learning
Abstract: We consider the problem of high-dimensional heavy-tailed statistical estimation in the streaming setting, which is much harder than the traditional batch setting due to memory constraints. We cast this problem as stochastic convex optimization with heavy tailed stochastic gradients, and prove that the widely used Clipped-SGD algorithm attains near-optimal sub-Gaussian statistical rates whenever the second moment of the stochastic gradient noise is finite. More precisely, with $T$ samples, we show that Clipped-SGD, for smooth and strongly convex objectives, achieves an error of $\sqrt{\frac{\mathsf{Tr}(\Sigma)+\sqrt{\mathsf{Tr}(\Sigma)\|\Sigma\|_2}\log(\frac{\log(T)}{\delta})}{T}}$ with probability $1-\delta$, where $\Sigma$ is the covariance of the clipped gradient. Note that the fluctuations (depending on $\frac{1}{\delta}$) are of lower order than the term $\mathsf{Tr}(\Sigma)$. This improves upon the current best rate of $\sqrt{\frac{\mathsf{Tr}(\Sigma)\log(\frac{1}{\delta})}{T}}$ for Clipped-SGD, known only for smooth and strongly convex objectives. Our results also extend to smooth convex and lipschitz convex objectives. Key to our result is a novel iterative refinement strategy for martingale concentration, improving upon the PAC-Bayes approach of Catoni and Giulini., Comment: Accepted at NeurIPS 2024
Published: 2024

49. Annotation Efficiency: Identifying Hard Samples via Blocked Sparse Linear Bandits

Author: Jain, Adit, Pal, Soumyabrata, Choudhary, Sunav, Narayanam, Ramasuri, and Krishnamurthy, Vikram
Subjects: Computer Science - Machine Learning
Abstract: This paper considers the problem of annotating datapoints using an expert with only a few annotation rounds in a label-scarce setting. We propose soliciting reliable feedback on difficulty in annotating a datapoint from the expert in addition to ground truth label. Existing literature in active learning or coreset selection turns out to be less relevant to our setting since they presume the existence of a reliable trained model, which is absent in the label-scarce regime. However, the literature on coreset selection emphasizes the presence of difficult data points in the training set to perform supervised learning in downstream tasks (Mindermann et al., 2022). Therefore, for a given fixed annotation budget of $\mathsf{T}$ rounds, we model the sequential decision-making problem of which (difficult) datapoints to choose for annotation in a sparse linear bandits framework with the constraint that no arm can be pulled more than once (blocking constraint). With mild assumptions on the datapoints, our (computationally efficient) Explore-Then-Commit algorithm BSLB achieves a regret guarantee of $\widetilde{\mathsf{O}}(k^{\frac{1}{3}} \mathsf{T}^{\frac{2}{3}} +k^{-\frac{1}{2}} \beta_k + k^{-\frac{1}{12}} \beta_k^{\frac{1}{2}}\mathsf{T}^{\frac{5}{6}})$ where the unknown parameter vector has tail magnitude $\beta_k$ at sparsity level $k$. To this end, we show offline statistical guarantees of Lasso estimator with mild Restricted Eigenvalue (RE) condition that is also robust to sparsity. Finally, we propose a meta-algorithm C-BSLB that does not need knowledge of the optimal sparsity parameters at a no-regret cost. We demonstrate the efficacy of our BSLB algorithm for annotation in the label-scarce setting for an image classification task on the PASCAL-VOC dataset, where we use real-world annotation difficulty scores., Comment: 31 Pages
Published: 2024

50. Arithmetic Bohr radius of bounded linear operators

Author: Allu, Vasudevarao and Pal, Subhadip
Subjects: Mathematics - Functional Analysis, Mathematics - Complex Variables, Primary 32A05, 32A10, 46B07, Secondary 46G20
Abstract: In this paper, we investigate the arithmetic Bohr radius of bounded linear operators between arbitrary complex Banach spaces. We establish the close connection between the classical Bohr radius and the arithmetic Bohr radius of bounded linear operators. Further, we study the asymptotic estimates of arithmetic Bohr radius for identity operator on infinite dimensional complex Banach spaces. Finally, we obtain the correct asymptotic behavior of Bohr radii of operators between sequence spaces., Comment: 16 Pages. Some minor corrections have been fixed
Published: 2024

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