15,024 results on '"A. Itay"'
Search Results
152. Generalized Longest Simple Path Problems: Speeding up Search Using SPQR Trees.
- Author
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Gal Dahan, Itay Tabib, Solomon Eyal Shimony, and Yefim Dinitz
- Published
- 2024
- Full Text
- View/download PDF
153. How Many Neurons Does it Take to Approximate the Maximum?
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Itay Safran, Daniel Reichman 0001, and Paul Valiant
- Published
- 2024
- Full Text
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154. Kitchef: A TUI for Parent-Child Cooking Together.
- Author
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Noa Morag Yaar, Ofir Sadka, Itay Shatil, Maayan Aharonson, Bar Efrima, Tal Barda, Mira Hayat, Oren Zuckerman, and Hadas Erel
- Published
- 2024
- Full Text
- View/download PDF
155. Aseptic Synovitis
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Ashkenazi, Itay, Schwarzkopf, Ran, Bono, James V., editor, and Scott, Richard D., editor
- Published
- 2024
- Full Text
- View/download PDF
156. The Democratic Teacher as Political Organizer
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Snir, Itay, Wittig, Steffen, editor, Mayer, Ralf, editor, and Sperschneider, Julia, editor
- Published
- 2024
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157. Integrating Distributed Component-Based Systems Through Deep Reinforcement Learning
- Author
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Cohen, Itay, Peled, Doron, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, and Yung, Moti, Editorial Board Member
- Published
- 2024
- Full Text
- View/download PDF
158. Glioblastoma Spheroid Invasion through Soft, Brain‐Like Matrices Depends on Hyaluronic Acid–CD44 Interactions
- Author
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Safarians, Gevick, Sohrabi, Alireza, Solomon, Itay, Xiao, Weikun, Bastola, Soniya, Rajput, Bushra W, Epperson, Mary, Rosenzweig, Isabella, Tamura, Kelly, Singer, Breahna, Huang, Joyce, Harrison, Mollie J, Sanazzaro, Talia, Condro, Michael C, Kornblum, Harley I, and Seidlits, Stephanie K
- Subjects
Engineering ,Biomedical Engineering ,Neurosciences ,Cancer ,Brain Disorders ,Rare Diseases ,Brain Cancer ,Humans ,Glioblastoma ,Hyaluronic Acid ,Cell Line ,Tumor ,Brain ,Cell Movement ,Hyaluronan Receptors ,CD44 ,ezrin ,glioblastoma ,hyaluronic acids ,hydrogels ,Medicinal and Biomolecular Chemistry ,Medical Biotechnology ,Medical biotechnology ,Biomedical engineering - Abstract
Increased secretion of hyaluronic acid (HA), a glycosaminoglycan abundant in the brain extracellular matrix (ECM), correlates with worse clinical outcomes for glioblastoma (GBM) patients. GBM cells aggressively invade the brain parenchyma while encountering spatiotemporal changes in their local ECM, including HA concentration. To investigate how varying HA concentrations affect GBM invasion, patient-derived GBM cells are cultured within a soft, 3D matrix in which HA concentration is precisely varied and cell migration observed. Data demonstrate that HA concentration can determine the invasive activity of patient-derived GBM cells in a biphasic and highly sensitive manner, where the absolute concentration of HA at which cell migration peaked is specific to each patient-derived line. Furthermore, evidence that this response relies on phosphorylated ezrin, which interacts with the intracellular domain of HA-engaged CD44 to effectively link the actin cytoskeleton to the local ECM is provided. Overall, this study highlights CD44-HA binding as a major mediator of GBM cell migration that acts independently of integrins and focal adhesion complexes and suggests that targeting HA-CD44-ezrin interactions represents a promising therapeutic strategy to prevent tumor cell invasion in the brain.
- Published
- 2023
159. Discontinuous metric programming in liquid crystalline elastomers
- Author
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Hebner, Tayler S., Bowman, Riley G. A., Duffy, Daniel, Mostajeran, Cyrus, Griniasty, Itay, Cohen, Itai, Warner, Mark, Bowman, Christopher N., and White, Timothy J.
- Subjects
Condensed Matter - Soft Condensed Matter ,Physics - Chemical Physics - Abstract
Liquid crystalline elastomers (LCEs) are shape-changing materials that exhibit large deformations in response to applied stimuli. Local control of the orientation of LCEs spatially directs the deformation of these materials to realize spontaneous shape change in response to stimuli. Prior approaches to shape programming in LCEs utilize patterning techniques that involve the detailed inscription of spatially varying nematic fields to produce sheets. These patterned sheets deform into elaborate geometries with complex Gaussian curvatures. Here, we present an alternative approach to realize shape-morphing in LCEs where spatial patterning of the crosslink density locally regulates the material deformation magnitude on either side of a prescribed interface curve. We also present a simple mathematical model describing the behavior of these materials. Further experiments coupled with the mathematical model demonstrate the control of the sign of Gaussian curvature, which is used in combination with heat transfer effects to design LCEs that self-clean as a result of temperature-dependent actuation properties.
- Published
- 2022
- Full Text
- View/download PDF
160. Highly-parallelized simulation of a pixelated LArTPC on a GPU
- Author
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DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Ahmad, Z., Ahmed, J., Aimard, B., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alt, C., Alton, A., Alvarez, R., Amedo, P., Anderson, J., Andrade, D. A., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Campanelli, W. L. Anicézio, Ankowski, A., Antoniassi, M., Antonova, M., Antoshkin, A., Antusch, S., Aranda-Fernandez, A., Arellano, L., Arnold, L. O., Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asquith, L., Aurisano, A., Aushev, V., Autiero, D., Ayala-Torres, M., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baller, B., Bambah, B., Barao, F., Barenboim, G., Alzás, P. Barham, Barker, G. J., Barkhouse, W., Barnes, C., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernardini, P., Berner, R. M., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhambure, J., Bhardwaj, A., Bhatnagar, V., Bhattacharjee, M., Bhattacharya, M., Bhattarai, D., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biassoni, M., Biery, K., Bilki, B., Bishai, M., Bisignani, V., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blend, D., Blucher, E., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Borkum, A., Bostan, N., Bour, P., Boyden, D., Bracinik, J., Braga, D., Brailsford, D., Branca, A., Brandt, A., Bravo-Moreno, M., Bremer, J., Brew, C., Brice, S. J., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., V., G. Caceres, Cagnoli, I., Cai, T., Caiulo, D., Calabrese, R., Calafiura, P., Calcutt, J., Calin, M., Calivers, L., Calvez, S., Calvo, E., Caminata, A., Caratelli, D., Carber, D., Carceller, J. C., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Forero, J. F. Castaño, Castillo, A., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavallaro, G., Cavanna, F., Centro, S., Cerati, G., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chalifour, M., Chappell, A., Chardonnet, E., Charitonidis, N., Chatterjee, A., Chattopadhyay, S., Chen, H., Chen, M., Chen, Y., Chen, Z., Chen-Wishart, Z., Cheon, Y., Cherdack, D., Chi, C., Childress, S., Chirco, R., Chiriacescu, A., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christensen, A., Christian, D., Christodoulou, G., Chukanov, A., Chung, M., Church, E., Cicero, V., Clapa, D., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, C., David, Q., Davies, G. S., Davini, S., Dawson, J., De, K., De, S., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, Deisting, A., De Jong, P., De la Torre, A., Delbart, A., De Leo, V., Delepine, D., Delgado, M., Dell'Acqua, A., Delmonte, N., De Lurgio, P., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., De Souza, G., Detje, J. P., Devi, R., Dharmapalan, R., Dias, M., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dvornikov, O., Dwyer, D. A., Dyshkant, A. S., Eads, M., Earle, A., Edmunds, D., Eisch, J., Emberger, L., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferraro, F., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fischer, V., Fitzpatrick, R. S., Flanagan, W., Fleming, B., Flight, R., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Franco, D., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gabrielli, A., Gago, A., Gallagher, H., Gallas, A., Gallego-Ros, A., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Ge, G., Geffroy, N., Gelli, B., Gendotti, A., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, P., Giammaria, T., Giangiacomi, N., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Gnani, D., Gogota, O., Gold, M., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goodwin, O., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D., Green, P., Greenberg, S., Greenler, L., Greer, J., Grenard, J., Griffith, W. C., Groetschla, F. T., Groh, M., Grzelak, K., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerard, E., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Gupta, A., Gupta, V., Guthikonda, K. K., Guzowski, P., Guzzo, M. M., Gwon, S., Ha, C., Haaf, K., Habig, A., Hadavand, H., Hadef, A., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hamacher-Baumann, P., Hamernik, T., Hamilton, P., Han, J., Hancock, J., Happacher, F., Harris, D. A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C., Hatcher, R., Hatfield, K. W., Hatzikoutelis, A., Hayes, C., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Henry, S., Morquecho, M. A. Hernandez, Herner, K., Hewes, V., Hilgenberg, C., Hill, T., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horton-Smith, G. A., Hostert, M., Houdy, T., Hourlier, A., Howard, B., Howell, R., Barrios, J. Hoyos, Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jediny, F., Jena, D., Jeong, Y. S., Jesús-Valls, C., Ji, X., Jiang, J., Jiang, L., Jipa, A., Jo, J. H., Joaquim, F. R., Johnson, W., Jones, B., Jones, R., Jovancevic, N., Judah, M., Jung, C. K., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Koseyan, O. Kamer, Kamiya, F., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kazaryan, N., Kearns, E., Keener, P., Kelly, K. J., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khabibullin, M., Khotjantsev, A., Khvedelidze, A., Kim, D., King, B., Kirby, B., Kirby, M., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koehler, K., Koerner, L. W., Koh, D. H., Kohn, S., Koller, P. P., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kozhukalov, V., Kralik, R., Kreczko, L., Krennrich, F., Kreslo, I., Kropp, W., Kroupova, T., Kubu, M., Kudenko, Y., Kudryavtsev, V. A., Kuhlmann, S., Kulagin, S., Kumar, J., Kumar, P., Kunze, P., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kvasnicka, J., Kwak, D., Lambert, A., Land, B. J., Lane, C. E., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laundrie, A., Laurenti, G., Lawrence, A., Laycock, P., Lazanu, I., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeBrun, P., LeCompte, T., Lee, C., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Lepin, L. M., Li, S. W., Li, Y., Liao, H., Lin, C. S., Lin, S., Lindebaum, D., Lineros, R. A., Ling, J., Lister, A., Littlejohn, B. R., Liu, J., Liu, Y., Lockwitz, S., Loew, T., Lokajicek, M., Lomidze, I., Long, K., Lord, T., LoSecco, J. M., Louis, W. C., Lu, X. -G., Luk, K. B., Lunday, B., Luo, X., Luppi, E., Lux, T., Luzio, V. P., Maalmi, J., MacFarlane, D., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., MacMahon, M., Maddalena, A., Madera, A., Madigan, P., Magill, S., Mahn, K., Maio, A., Major, A., Majumdar, K., Maloney, J. A., Man, M., Mandrioli, G., Mandujano, R. C., Maneira, J., Manenti, L., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marsden, D., Marshak, M., Marshall, C. M., Marshall, J., Marteau, J., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Mason, K., Mastbaum, A., Matichard, F., Matsuno, S., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., Mazzacane, A., McAskill, T., McCluskey, E., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Mefodiev, A., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Messier, M. D., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Michna, G., Mikola, V., Milincic, R., Miller, G., Miller, W., Mills, J., Mineev, O., Minotti, A., Miranda, O. G., Miryala, S., Miscetti, S., Mishra, C. S., Mishra, S. R., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Moffat, K., Mogan, A., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Moon, S. H., Mooney, M., Moor, A. F., Moreno, D., Morescalchi, L., Moretti, D., Morris, C., Mossey, C., Mote, M., Motuk, E., Moura, C. A., Mousseau, J., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mulhearn, M., Munford, D., Munteanu, L. J., Muramatsu, H., Muraz, J., Murphy, M., Murphy, S., Musser, J., Nachtman, J., Nagai, Y., Nagu, S., Nalbandyan, M., Nandakumar, R., Naples, D., Narita, S., Nath, A., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Negishi, K., Nelson, J. K., Nelson, M., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Newton, H., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Olivier, A., Olshevskiy, A., Onel, Y., Onishchuk, Y., Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Pan, S., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papadimitriou, V., Papaleo, R., Papanestis, A., Paramesvaran, S., Parke, S., Parozzi, E., Parsa, S., Parsa, Z., Parveen, S., Parvu, M., Pasciuto, D., Pascoli, S., Pasqualini, L., Pasternak, J., Pater, J., Patrick, C., Patrizii, L., Patterson, R. B., Patton, S. J., Patzak, T., Paudel, A., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Pec, V., Peeters, S. J. M., Perez, A. Pena, Pennacchio, E., Penzo, A., Peres, O. L. G., Gonzalez, Y. F. Perez, Pérez-Molina, L., Pernas, C., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pia, V., Piastra, F., Pickering, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Plows, K., Plunkett, R., Pollman, T., Pompa, F., Pons, X., Poonthottathil, N., Poppi, F., Pordes, S., Porter, J., Potekhin, M., Potenza, R., Potukuchi, B. V. K. S., Pozimski, J., Pozzato, M., Prakash, S., Prakash, T., Pratt, C., Prest, M., Psihas, F., Pugnere, D., Qian, X., Raaf, J. L., Radeka, V., Rademacker, J., Radev, R., Radics, B., Rafique, A., Raguzin, E., Rai, M., Rajaoalisoa, M., Rakhno, I., Rakotonandrasana, A., Rakotondravohitra, L., Rameika, R., Delgado, M. A. Ramirez, Ramson, B., Rappoldi, A., Raselli, G., Ratoff, P., Raut, S., Razafinime, H., Razakamiandra, R. F., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reggiani-Guzzo, M., Reichenbacher, J., Reitzner, S. D., Sfar, H. Rejeb, Renshaw, A., Rescia, S., Resnati, F., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Rice, L. C. J., Ricol, J. S., Rigamonti, A., Rigaut, Y., Rincón, E. V., Ritchie-Yates, A., Rivera, D., Rivera, R., Robert, A., Rocha, J. L. Rocabado, Rochester, L., Roda, M., Rodrigues, P., Alonso, M. J. Rodriguez, Rondon, J. Rodriguez, Romeo, E., Rosauro-Alcaraz, S., Rosier, P., Rossella, M., Rossi, M., Ross-Lonergan, M., Rout, J., Roy, P., Rubbia, A., Rubbia, C., Ferreira, G. Ruiz, Russell, B., Ruterbories, D., Rybnikov, A., Saa-Hernandez, A., Saakyan, R., Sacerdoti, S., Sahu, N., Sala, P., Samios, N., Samoylov, O., Sanchez, M. C., Sandberg, V., Sanders, D. A., Sankey, D., Santoro, D., Saoulidou, N., Sapienza, P., Sarasty, C., Sarcevic, I., Sarra, I., Savage, G., Savinov, V., Scanavini, G., Scaramelli, A., Scarff, A., Scarpelli, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Segreto, E., Selyunin, A., Senise, C. R., Sensenig, J., Sgalaberna, D., Shaevitz, M. H., Shafaq, S., Shaker, F., Shamma, M., Shanahan, P., Sharankova, R., Sharma, H. R., Sharma, R., Kumar, R., Shaw, K., Shaw, T., Shchablo, K., Shepherd-Themistocleous, C., Sheshukov, A., Shi, W., Shin, S., Shoemaker, I., Shooltz, D., Shrock, R., Silber, J., Simard, L., Sinclair, J., Sinev, G., Singh, Jaydip, Singh, J., Singh, L., Singh, P., Singh, V., Chauhan, S. Singh, Sipos, R., Sirri, G., Sitraka, A., Siyeon, K., Skarpaas, K., Smith, E., Smith, P., Smolik, J., Smy, M., Snider, E. L., Snopok, P., Snowden-Ifft, D., Nunes, M. Soares, Sobel, H., Soderberg, M., Sokolov, S., Salinas, C. J. Solano, Söldner-Rembold, S., Soleti, S. R., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Sotnikov, A., Soto-Oton, J., Sousa, A., Soustruznik, K., Spagliardi, F., Spanu, M., Spitz, J., Spooner, N. J. C., Spurgeon, K., Stalder, D., Stancari, M., Stanco, L., Steenis, J., Stein, R., Steiner, H. M., Lisbôa, A. F. Steklain, Stepanova, A., Stewart, J., Stillwell, B., Stock, J., Stocker, F., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Subash, J., Surdo, A., Susic, V., Suter, L., Sutera, C. M., Sutton, K., Suvorov, Y., Svoboda, R., Swain, S. K., Szczerbinska, B., Szelc, A. M., Taffara, A., Talukdar, N., Tamara, J., Tanaka, H. A., Tang, S., Taniuchi, N., Oregui, B. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tata, N., Tatar, E., Tayloe, R., Teklu, A. M., Tennessen, P., Tenti, M., Terao, K., Terranova, F., Testera, G., Thakore, T., Thea, A., Thompson, A., Thorn, C., Timm, S. C., Tishchenko, V., Todorović, N., Tomassetti, L., Tonazzo, A., Torbunov, D., Torti, M., Tortola, M., Tortorici, F., Tosi, N., Totani, D., Toups, M., Touramanis, C., Travaglini, R., Trevor, J., Trilov, S., Trzaska, W. H., Tsai, Y., Tsai, Y. -T., Tsamalaidze, Z., Tsang, K. V., Tsverava, N., Tu, S. Z., Tufanli, S., Tull, C., Turner, J., Tuzi, M., Tyler, J., Tyley, E., Tzanov, M., Uboldi, L., Uchida, M. A., Urheim, J., Usher, T., Utaegbulam, H., Uzunyan, S., Vagins, M. R., Vahle, P., Valder, S., Valdiviesso, G. A., Valencia, E., Valentim, R., Vallari, Z., Vallazza, E., Valle, J. W. F., Vallecorsa, S., Van Berg, R., Van de Water, R. G., Forero, D. Vanegas, Vannerom, D., Varanini, F., Oliva, D. Vargas, Varner, G., Vasina, S., Vaughan, N., Vaziri, K., Vega, J., Ventura, S., Verdugo, A., Vergani, S., Vermeulen, M. A., Verzocchi, M., Vicenzi, M., de Souza, H. Vieira, Vignoli, C., Vilela, C., Viren, B., Vizcaya-Hernandez, A., Vrba, T., Vuong, Q., Wachala, T., Waldron, A. V., Wallbank, M., Walton, T., Wang, H., Wang, J., Wang, L., Wang, M. H. L. S., Wang, X., Wang, Y., Warburton, K., Warner, D., Wascko, M. O., Waters, D., Watson, A., Wawrowska, K., Weatherly, P., Weber, A., Weber, M., Wei, H., Weinstein, A., Wenman, D., Wetstein, M., Whilhelmi, J., White, A., Whitehead, L. H., Whittington, D., Wilking, M. J., Wilkinson, A., Wilkinson, C., Williams, Z., Wilson, F., Wilson, R. J., Wisniewski, W., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wospakrik, M., Wresilo, K., Wret, C., Wu, S., Wu, W., Wurm, M., Wyenberg, J., Xiao, Y., Xiotidis, I., Yaeggy, B., Yahlali, N., Yandel, E., Yang, G., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Yoon, Y. S., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zazueta, L., Zeller, G. P., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhang, Y., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.
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Physics - Computational Physics ,Physics - Instrumentation and Detectors - Abstract
The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on $10^3$ pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype., Comment: 26 pages, 15 figures
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- 2022
161. First measurement of quasi-elastic $\Lambda$ baryon production in muon anti-neutrino interactions in the MicroBooNE detector
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MicroBooNE collaboration, Abratenko, P., Aldana, D. Andrade, Anthony, J., Arellano, L., Asaadi, J., Ashkenazi, A., Balasubramanian, S., Baller, B., Barr, G., Barrow, J., Basque, V., Rodrigues, O. Benevides, Berkman, S., Bhanderi, A., Bhattacharya, M., Bishai, M., Blake, A., Bogart, B., Bolton, T., Book, J. Y., Camilleri, L., Caratelli, D., Terrazas, I. Caro, Cavanna, F., Cerati, G., Chen, Y., Conrad, J. M., Convery, M., Cooper-Troendle, L., Crespo-Anadon, J. I., Del Tutto, M., Dennis, S. R., Detje, P., Devitt, A., Diurba, R., Djurcic, Z., Dorrill, R., Duffy, K., Dytman, S., Eberly, B., Ereditato, A., Evans, J. J., Fine, R., Finnerud, O. G., Fleming, B. T., Foppiani, N., Foreman, W., Franco, D., Furmanski, A. P., Garcia-Gamez, D., Gardiner, S., Ge, G., Gollapinni, S., Goodwin, O., Gramellini, E., Green, P., Greenlee, H., Gu, W., Guenette, R., Guzowski, P., Hagaman, L., Hen, O., Hicks, R., Hilgenberg, C., Horton-Smith, G. A., Irwin, B., Itay, R., James, C., Ji, X., Jiang, L., Jo, J. H., Johnson, R. A., Jwa, Y. J., Kalra, D., Kamp, N., Karagiorgi, G., Ketchum, W., Kirby, M., Kobilarcik, T., Kreslo, I., Leibovitch, M. B., Lepetic, I., Li, J. -Y., Li, K., Li, Y., Lin, K., Littlejohn, B. R., Louis, W. C., Luo, X., Mariani, C., Marsden, D., Marshall, J., Martinez, N., Caicedo, D. A. Martinez, Mason, K., Mastbaum, A., McConkey, N., Meddage, V., Miller, K., Mills, J., Mistry, K., Mohayai, T., Mogan, A., Mooney, M., Moor, A. F., Moore, C. D., Lepin, L. Mora, Mousseau, J., Babu, S. Mulleria, Naples, D., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nowak, J., Nunes, M., Oza, N., Palamara, O., Pallat, N., Paolone, V., Papadopoulou, A., Papavassiliou, V., Parkinson, H., Pate, S. F., Patel, N., Pavlovic, Z., Piasetzky, E., Ponce-Pinto, I., Pophale, I., Prince, S., Qian, X., Raaf, J. L., Radeka, V., Rafique, A., Reggiani-Guzzo, M., Ren, L., Rochester, L., Rondon, J. Rodriguez, Rosenberg, M., Ross-Lonergan, M., von Rohr, C. Rudolph, Scanavini, G., Schmitz, D. W., Schukraft, A., Seligman, W., Shaevitz, M. H., Sharankova, R., Shi, J., Snider, E. L., Soderberg, M., Soldner-Rembold, S., Spitz, J., Stancari, M., John, J. St., Strauss, T., Sword-Fehlberg, S., Szelc, A. M., Tang, W., Taniuchi, N., Terao, K., Thorpe, C., Torbunov, D., Totani, D., Toups, M., Tsai, Y. -T., Tyler, J., Uchida, M. A., Usher, T., Viren, B., Weber, M., Wei, H., White, A. J., Williams, Z., Wolbers, S., Wongjirad, T., Wospakrik, M., Wresilo, K., Wright, N., Wu, W., Yandel, E., Yang, T., Yates, L. E., Yu, H. W., Zeller, G. P., Zennamo, J., and Zhang, C.
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High Energy Physics - Experiment - Abstract
We present the first measurement of the cross section of Cabibbo-suppressed $\Lambda$ baryon production, using data collected with the MicroBooNE detector when exposed to the neutrinos from the Main Injector beam at the Fermi National Accelerator Laboratory. The data analyzed correspond to $2.2 \times 10^{20}$ protons on target of neutrino mode running and $4.9 \times 10^{20}$ protons on target of anti-neutrino mode running. An automated selection is combined with hand scanning, with the former identifying five candidate $\Lambda$ production events when the signal was unblinded, consistent with the GENIE prediction of $5.3 \pm 1.1$ events. Several scanners were employed, selecting between three and five events, compared with a prediction from a blinded Monte Carlo simulation study of $3.7 \pm 1.0$ events. Restricting the phase space to only include $\Lambda$ baryons that decay above MicroBooNE's detection thresholds, we obtain a flux averaged cross section of $2.0^{+2.2}_{-1.7} \times 10^{-40}$ cm$^2/$Ar, where statistical and systematic uncertainties are combined.
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- 2022
162. Diverse Demonstrations Improve In-context Compositional Generalization
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Levy, Itay, Bogin, Ben, and Berant, Jonathan
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Computer Science - Computation and Language - Abstract
In-context learning has shown great success in i.i.d semantic parsing splits, where the training and test sets are drawn from the same distribution. In this setup, models are typically prompted with demonstrations that are similar to the input utterance. However, in the setup of compositional generalization, where models are tested on outputs with structures that are absent from the training set, selecting similar demonstrations is insufficient, as often no example will be similar enough to the input. In this work, we propose a method to select diverse demonstrations that aims to collectively cover all of the structures required in the output program, in order to encourage the model to generalize to new structures from these demonstrations. We empirically show that combining diverse demonstrations with in-context learning substantially improves performance across three compositional generalization semantic parsing datasets in the pure in-context learning setup and when combined with finetuning., Comment: ACL 2023
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- 2022
163. First Measurement of Differential Cross Sections for Muon Neutrino Charged Current Interactions on Argon with a Two-proton Final State in the MicroBooNE Detector
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MicroBooNE collaboration, Abratenko, P., Aldana, D. Andrade, Anthony, J., Arellano, L., Asaadi, J., Ashkenazi, A., Balasubramanian, S., Baller, B., Barr, G., Barrow, J., Basque, V., Bathe-Peters, L., Rodrigues, O. Benevides, Berkman, S., Bhanderi, A., Bhattacharya, M., Bishai, M., Blake, A., Bogart, B., Bolton, T., Book, J. Y., Camilleri, L., Caratelli, D., Terrazas, I. Caro, Cavanna, F., Cerati, G., Chen, Y., Conrad, J. M., Convery, M., Cooper-Troendle, L., Crespo-Anadon, J. I., Del Tutto, M., Dennis, S. R., Detje, P., Devitt, A., Diurba, R., Dorrill, R., Duffy, K., Dytman, S., Eberly, B., Ereditato, A., Evans, J. J., Fine, R., Finnerud, O. G., Fleming, B. T., Foppiani, N., Foreman, W., Franco, D., Furmanski, A. P., Garcia-Gamez, D., Gardiner, S., Ge, G., Gollapinni, S., Goodwin, O., Gramellini, E., Green, P., Greenlee, H., Gu, W., Guenette, R., Guzowski, P., Hagaman, L., Hen, O., Hicks, R., Hilgenberg, C., Horton-Smith, G. A., Irwin, B., Itay, R., James, C., Ji, X., Jiang, L., Jo, J. H., Johnson, R. A., Jwa, Y. J., Kalra, D., Kamp, N., Karagiorgi, G., Ketchum, W., Kirby, M., Kobilarcik, T., Kreslo, I., Leibovitch, M. B., Lepetic, I., Li, J. -Y., Li, K., Li, Y., Lin, K., Littlejohn, B. R., Louis, W. C., Luo, X., Manivannan, K., Mariani, C., Marsden, D., Marshall, J., Caicedo, D. A. Martinez, Mason, K., Mastbaum, A., McConkey, N., Meddage, V., Miller, K., Mills, J., Mistry, K., Mohayai, T., Mogan, A., Mooney, M., Moor, A. F., Moore, C. D., Lepin, L. Mora, Mousseau, J., Babu, S. Mulleria, Naples, D., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nowak, J., Nunes, M., Oza, N., Palamara, O., Pallat, N., Paolone, V., Papadopoulou, A., Papavassiliou, V., Parkinson, H., Pate, S. F., Patel, N., Pavlovic, Z., Piasetzky, E., Ponce-Pinto, I., Pophale, I., Prince, S., Qian, X., Raaf, J. L., Radeka, V., Reggiani-Guzzo, M., Ren, L., Rochester, L., Rondon, J. Rodriguez, Rosenberg, M., Ross-Lonergan, M., von Rohr, C. Rudolph, Scanavini, G., Schmitz, D. W., Schukraft, A., Seligman, W., Shaevitz, M. H., Sharankova, R., Shi, J., Smith, A., Snider, E. L., Soderberg, M., Soldner-Rembold, S., Spitz, J., Stancari, M., John, J. St., Strauss, T., Sword-Fehlberg, S., Szelc, A. M., Tang, W., Taniuchi, N., Terao, K., Thorpe, C., Torbunov, D., Totani, D., Toups, M., Tsai, Y. -T., Tyler, J., Uchida, M. A., Usher, T., Viren, B., Weber, M., Wei, H., White, A. J., Williams, Z., Wolbers, S., Wongjirad, T., Wospakrik, M., Wresilo, K., Wright, N., Wu, W., Yandel, E., Yang, T., Yates, L. E., Yu, H. W., Zeller, G. P., Zennamo, J., and Zhang, C.
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High Energy Physics - Experiment ,Nuclear Experiment - Abstract
We present the first measurement of differential cross sections for charged-current muon neutrino interactions on argon with one muon, two protons, and no pions in the final state. Such interactions leave the target nucleus in a two-particle two-hole state; these states are of great interest, but currently there is limited information about their production in neutrino-nucleus interactions. Detailed investigations of the production of two-particle two-hole states are vital to support upcoming experiments exploring the nature of the neutrino, and the development of the liquid-argon time-projection-chamber has made possible the isolation of such final states. The opening angle between the two protons, the angle between the total proton momentum and the muon, and the total transverse momentum of the final state system are sensitive to the underlying physics processes as embodied in a variety of models. Realistic initial-state momentum distributions are shown to be important in reproducing the data., Comment: Resubmitted to PRL in response to reviewer comments
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- 2022
164. Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector
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DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Ahmad, Z., Ahmed, J., Aimard, B., Akbar, F., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alt, C., Alton, A., Alvarez, R., Amedo, P., Anderson, J., Andrade, D. A., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Campanelli, W. L. Anicézio, Ankowski, A., Antoniassi, M., Antonova, M., Antoshkin, A., Antusch, S., Aranda-Fernandez, A., Arellano, L., Arnold, L. O., Arroyave, M. A., Asaadi, J., Asquith, L., Aurisano, A., Aushev, V., Autiero, D., Ayala-Torres, M., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baller, B., Bambah, B., Barao, F., Barenboim, G., Barker, G. J., Barkhouse, W., Barnes, C., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernardini, P., Berner, R. M., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhambure, J., Bhardwaj, A., Bhatnagar, V., Bhattacharjee, M., Bhattarai, D., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biassoni, M., Biery, K., Bilki, B., Bishai, M., Bisignani, V., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blend, D., Blucher, E., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Borkum, A., Bostan, N., Bour, P., Boyden, D., Bracinik, J., Braga, D., Brailsford, D., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., V., G. Caceres, Cagnoli, I., Cai, T., Caiulo, D., Calabrese, R., Calafiura, P., Calcutt, J., Calin, M., Calivers, L., Calvez, S., Calvo, E., Caminata, A., Caratelli, D., Carber, D., Carceller, J. C., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Forero, J. F. Castaño, Castillo, A., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavallaro, G., Cavanna, F., Centro, S., Cerati, G., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chalifour, M., Chappell, A., Chardonnet, E., Charitonidis, N., Chatterjee, A., Chattopadhyay, S., Chen, H., Chen, M., Chen, Y., Chen, Z., Chen-Wishart, Z., Cheon, Y., Cherdack, D., Chi, C., Childress, S., Chirco, R., Chiriacescu, A., Chitirasreemadam, N., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Chowdhury, B., Christensen, A., Christian, D., Christodoulou, G., Chukanov, A., Chung, M., Church, E., Cicero, V., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cova, P., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Cussans, D., Dalager, O., Dallavalle, R., da Motta, H., Dar, Z. A., Peres, L. Da Silva, David, C., David, Q., Davies, G. S., Davini, S., Dawson, J., De, K., De, S., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, Deisting, A., De Jong, P., De la Torre, A., Delbart, A., De Leo, V., Delepine, D., Delgado, M., Dell'Acqua, A., Delmonte, N., De Lurgio, P., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Deptuch, G. W., De Roeck, A., De Romeri, V., De Souza, G., Detje, J. P., Devi, R., Dharmapalan, R., Dias, M., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Giulio, L., Ding, P., Di Noto, L., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dvornikov, O., Dwyer, D. A., Dyshkant, A. S., Eads, M., Earle, A., Edmunds, D., Eisch, J., Emberger, L., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferraro, F., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fischer, V., Fitzpatrick, R. S., Flanagan, W., Fleming, B., Flight, R., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Franco, D., Freeman, J., Freestone, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gabrielli, A., Gago, A., Gallagher, H., Gallas, A., Gallego-Ros, A., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Ge, G., Geffroy, N., Gelli, B., Gendotti, A., Gent, S., Ghorbani-Moghaddam, Z., Giammaria, P., Giammaria, T., Giangiacomi, N., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Girerd, C., Giri, A. K., Gnani, D., Gogota, O., Gold, M., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goodwin, O., Goswami, S., Gotti, C., Goudzovski, E., Grace, C., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D., Green, P., Greenberg, S., Greenler, L., Greer, J., Grenard, J., Griffith, W. C., Groetschla, F. T., Groh, M., Grzelak, K., Gu, W., Guardincerri, E., Guarino, V., Guarise, M., Guenette, R., Guerard, E., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Gupta, A., Gupta, V., Guthikonda, K. K., Guzowski, P., Guzzo, M. M., Gwon, S., Ha, C., Haaf, K., Habig, A., Hadavand, H., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hamacher-Baumann, P., Hamernik, T., Hamilton, P., Han, J., Harris, D. A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C., Hatcher, R., Hatfield, K. W., Hatzikoutelis, A., Hayes, C., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Henry, S., Morquecho, M. A. Hernandez, Herner, K., Hewes, V., Hilgenberg, C., Hill, T., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Hoff, J., Holin, A., Hoppe, E., Horton-Smith, G. A., Hostert, M., Hourlier, A., Howard, B., Howell, R., Barrios, J. Hoyos, Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jediny, F., Jena, D., Jeong, Y. S., Jesús-Valls, C., Ji, X., Jiang, J., Jiang, L., Jipa, A., Jo, J. H., Joaquim, F. R., Johnson, W., Jones, B., Jones, R., Jovancevic, N., Judah, M., Jung, C. K., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Koseyan, O. Kamer, Kamiya, F., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kazaryan, N., Kearns, E., Keener, P., Kelly, K. J., Kemp, E., Kemularia, O., Ketchum, W., Kettell, S. H., Khabibullin, M., Khotjantsev, A., Khvedelidze, A., Kim, D., King, B., Kirby, B., Kirby, M., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koehler, K., Koerner, L. W., Koh, D. H., Kohn, S., Koller, P. P., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kozhukalov, V., Kralik, R., Kreczko, L., Krennrich, F., Kreslo, I., Kropp, W., Kroupova, T., Kudenko, Y., Kudryavtsev, V. A., Kuhlmann, S., Kulagin, S., Kumar, J., Kumar, P., Kunze, P., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kvasnicka, J., Kwak, D., Lambert, A., Land, B. J., Lane, C. E., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laundrie, A., Laurenti, G., Lawrence, A., Laycock, P., Lazanu, I., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeBrun, P., LeCompte, T., Lee, C., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Lepin, L. M., Li, S. W., Li, Y., Liao, H., Lin, C. S., Lin, S., Lineros, R. A., Ling, J., Lister, A., Littlejohn, B. R., Liu, J., Liu, Y., Lockwitz, S., Loew, T., Lokajicek, M., Lomidze, I., Long, K., Lord, T., LoSecco, J. M., Louis, W. C., Lu, X. -G., Luk, K. B., Lunday, B., Luo, X., Luppi, E., Lux, T., Luzio, V. P., Maalmi, J., MacFarlane, D., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., Maddalena, A., Madera, A., Madigan, P., Magill, S., Mahn, K., Maio, A., Major, A., Majumdar, K., Maloney, J. A., Mandrioli, G., Mandujano, R. C., Maneira, J., Manenti, L., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marsden, D., Marshak, M., Marshall, C. M., Marshall, J., Marteau, J., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Mason, K., Mastbaum, A., Matichard, F., Matsuno, S., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., Mazzacane, A., McAskill, T., McCluskey, E., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Mefodiev, A., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Messier, M. D., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Michna, G., Mikola, V., Milincic, R., Miller, G., Miller, W., Mills, J., Mineev, O., Minotti, A., Miranda, O. G., Miryala, S., Mishra, C. S., Mishra, S. R., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Moffat, K., Mogan, A., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Moon, S. H., Mooney, M., Moor, A. F., Moreno, D., Moretti, D., Morris, C., Mossey, C., Mote, M., Motuk, E., Moura, C. A., Mousseau, J., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mulhearn, M., Munford, D., Muramatsu, H., Murphy, M., Murphy, S., Musser, J., Nachtman, J., Nagai, Y., Nagu, S., Nalbandyan, M., Nandakumar, R., Naples, D., Narita, S., Nath, A., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Negishi, K., Nelson, J. K., Nelson, M., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Newton, H., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Olivier, A., Olshevskiy, A., Onel, Y., Onishchuk, Y., Ormachea, L. Otiniano, Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Pan, S., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papadimitriou, V., Papaleo, R., Papanestis, A., Paramesvaran, S., Parke, S., Parozzi, E., Parsa, S., Parsa, Z., Parveen, S., Parvu, M., Pasciuto, D., Pascoli, S., Pasqualini, L., Pasternak, J., Pater, J., Patrick, C., Patrizii, L., Patterson, R. B., Patton, S. J., Patzak, T., Paudel, A., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Pec, V., Peeters, S. J. M., Perez, A. Pena, Pennacchio, E., Penzo, A., Peres, O. L. G., Pernas, C., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pia, V., Pickering, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Plows, K., Plunkett, R., Pompa, F., Pons, X., Poonthottathil, N., Poppi, F., Pordes, S., Porter, J., Porzio, S. D., Potekhin, M., Potenza, R., Potukuchi, B. V. K. S., Pozimski, J., Pozzato, M., Prakash, S., Prakash, T., Pratt, C., Prest, M., Psihas, F., Pugnere, D., Qian, X., Raaf, J. L., Radeka, V., Rademacker, J., Radev, R., Radics, B., Rafique, A., Raguzin, E., Rai, M., Rajaoalisoa, M., Rakhno, I., Rakotonandrasana, A., Rakotondravohitra, L., Rameika, R., Delgado, M. A. Ramirez, Ramson, B., Rappoldi, A., Raselli, G., Ratoff, P., Raut, S., Razafinime, H., Razakamiandra, R. F., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reggiani-Guzzo, M., Reichenbacher, J., Reitzner, S. D., Sfar, H. Rejeb, Renshaw, A., Rescia, S., Resnati, F., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Rice, L. C. J., Ricol, J. S., Rigamonti, A., Rigaut, Y., Rincón, E. V., Ritchie-Yates, A., Rivera, D., Rivera, R., Robert, A., Rocha, J. L. Rocabado, Rochester, L., Roda, M., Rodrigues, P., Alonso, M. J. Rodriguez, Rondon, J. Rodriguez, Romeo, E., Rosauro-Alcaraz, S., Rosier, P., Rossella, M., Rossi, M., Ross-Lonergan, M., Rout, J., Roy, P., Rubbia, A., Rubbia, C., Russell, B., Ruterbories, D., Rybnikov, A., Saa-Hernandez, A., Saakyan, R., Sacerdoti, S., Sahu, N., Sala, P., Samios, N., Samoylov, O., Sanchez, M. C., Sandberg, V., Sanders, D. A., Sankey, D., Santoro, D., Saoulidou, N., Sapienza, P., Sarasty, C., Sarcevic, I., Savage, G., Savinov, V., Scanavini, G., Scaramelli, A., Scarff, A., Scarpelli, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Segreto, E., Selyunin, A., Senise, C. R., Sensenig, J., Sgalaberna, D., Shaevitz, M. H., Shafaq, S., Shaker, F., Shamma, M., Shanahan, P., Sharankova, R., Sharma, H. R., Sharma, R., Kumar, R., Shaw, K., Shaw, T., Shchablo, K., Shepherd-Themistocleous, C., Sheshukov, A., Shi, W., Shin, S., Shoemaker, I., Shooltz, D., Shrock, R., Silber, J., Simard, L., Sinclair, J., Sinev, G., Singh, Jaydip, Singh, J., Singh, L., Singh, P., Singh, V., Chauhan, S. Singh, Sipos, R., Sirri, G., Sitraka, A., Siyeon, K., Skarpaas, K., Smith, E., Smith, P., Smolik, J., Smy, M., Snider, E. L., Snopok, P., Snowden-Ifft, D., Nunes, M. Soares, Sobel, H., Soderberg, M., Sokolov, S., Salinas, C. J. Solano, Söldner-Rembold, S., Soleti, S. R., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Sotnikov, A., Soto-Oton, J., Sousa, A., Soustruznik, K., Spagliardi, F., Spanu, M., Spitz, J., Spooner, N. J. C., Spurgeon, K., Stalder, D., Stancari, M., Stanco, L., Steenis, J., Stein, R., Steiner, H. M., Lisbôa, A. F. Steklain, Stepanova, A., Stewart, J., Stillwell, B., Stock, J., Stocker, F., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Subash, J., Surdo, A., Susic, V., Suter, L., Sutera, C. M., Suvorov, Y., Svoboda, R., Szczerbinska, B., Szelc, A. M., Talukdar, N., Tamara, J., Tanaka, H. A., Tang, S., Oregui, B. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tata, N., Tatar, E., Tayloe, R., Teklu, A. M., Tennessen, P., Tenti, M., Terao, K., Terranova, F., Testera, G., Thakore, T., Thea, A., Thompson, A., Thorn, C., Timm, S. C., Tishchenko, V., Todorović, N., Tomassetti, L., Tonazzo, A., Torbunov, D., Torti, M., Tortola, M., Tortorici, F., Tosi, N., Totani, D., Toups, M., Touramanis, C., Travaglini, R., Trevor, J., Trilov, S., Trzaska, W. H., Tsai, Y., Tsai, Y. -T., Tsamalaidze, Z., Tsang, K. V., Tsverava, N., Tufanli, S., Tull, C., Turner, J., Tyler, J., Tyley, E., Tzanov, M., Uboldi, L., Uchida, M. A., Urheim, J., Usher, T., Utaegbulam, H., Uzunyan, S., Vagins, M. R., Vahle, P., Valder, S., Valdiviesso, G. D. A., Valencia, E., Valentim, R., Vallari, Z., Vallazza, E., Valle, J. W. F., Vallecorsa, S., Van Berg, R., Van de Water, R. G., Forero, D. Vanegas, Vannerom, D., Varanini, F., Oliva, D. Vargas, Varner, G., Vasina, S., Vaughan, N., Vaziri, K., Vega, J., Ventura, S., Verdugo, A., Vergani, S., Vermeulen, M. A., Verzocchi, M., Vicenzi, M., de Souza, H. Vieira, Vignoli, C., Vilela, C., Viren, B., Vrba, T., Vuong, Q., Wachala, T., Waldron, A. V., Wallbank, M., Walton, T., Wang, H., Wang, J., Wang, L., Wang, M. H. L. S., Wang, X., Wang, Y., Warburton, K., Warner, D., Wascko, M. O., Waters, D., Watson, A., Wawrowska, K., Weatherly, P., Weber, A., Weber, M., Wei, H., Weinstein, A., Wenman, D., Wetstein, M., Whilhelmi, J., White, A., Whitehead, L. H., Whittington, D., Wilking, M. J., Wilkinson, A., Wilkinson, C., Williams, Z., Wilson, F., Wilson, R. J., Wisniewski, W., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wospakrik, M., Wresilo, K., Wret, C., Wu, S., Wu, W., Xiao, Y., Xiotidis, I., Yaeggy, B., Yandel, E., Yang, G., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Yoon, Y. S., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zazueta, L., Zeller, G. P., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhang, Y., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.
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High Energy Physics - Experiment ,Physics - Instrumentation and Detectors - Abstract
Measurements of electrons from $\nu_e$ interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyond the standard model, supernova neutrino detection, and solar neutrino measurements. This article describes the selection and reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector. ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and operated at CERN as a charged particle test beam experiment. A sample of low-energy electrons produced by the decay of cosmic muons is selected with a purity of 95%. This sample is used to calibrate the low-energy electron energy scale with two techniques. An electron energy calibration based on a cosmic ray muon sample uses calibration constants derived from measured and simulated cosmic ray muon events. Another calibration technique makes use of the theoretically well-understood Michel electron energy spectrum to convert reconstructed charge to electron energy. In addition, the effects of detector response to low-energy electron energy scale and its resolution including readout electronics threshold effects are quantified. Finally, the relation between the theoretical and reconstructed low-energy electron energy spectrum is derived and the energy resolution is characterized. The low-energy electron selection presented here accounts for about 75% of the total electron deposited energy. After the addition of lost energy using a Monte Carlo simulation, the energy resolution improves from about 40% to 25% at 50~MeV. These results are used to validate the expected capabilities of the DUNE far detector to reconstruct low-energy electrons., Comment: 19 pages, 10 figures
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- 2022
165. A picture of the space of typical learnable tasks
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Ramesh, Rahul, Mao, Jialin, Griniasty, Itay, Yang, Rubing, Teoh, Han Kheng, Transtrum, Mark, Sethna, James P., and Chaudhari, Pratik
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Computer Science - Machine Learning - Abstract
We develop information geometric techniques to understand the representations learned by deep networks when they are trained on different tasks using supervised, meta-, semi-supervised and contrastive learning. We shed light on the following phenomena that relate to the structure of the space of tasks: (1) the manifold of probabilistic models trained on different tasks using different representation learning methods is effectively low-dimensional; (2) supervised learning on one task results in a surprising amount of progress even on seemingly dissimilar tasks; progress on other tasks is larger if the training task has diverse classes; (3) the structure of the space of tasks indicated by our analysis is consistent with parts of the Wordnet phylogenetic tree; (4) episodic meta-learning algorithms and supervised learning traverse different trajectories during training but they fit similar models eventually; (5) contrastive and semi-supervised learning methods traverse trajectories similar to those of supervised learning. We use classification tasks constructed from the CIFAR-10 and Imagenet datasets to study these phenomena.
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- 2022
166. Noise Injection Node Regularization for Robust Learning
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Levi, Noam, Bloch, Itay M., Freytsis, Marat, and Volansky, Tomer
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Computer Science - Machine Learning ,Condensed Matter - Disordered Systems and Neural Networks ,Condensed Matter - Statistical Mechanics ,Computer Science - Artificial Intelligence ,Statistics - Machine Learning - Abstract
We introduce Noise Injection Node Regularization (NINR), a method of injecting structured noise into Deep Neural Networks (DNN) during the training stage, resulting in an emergent regularizing effect. We present theoretical and empirical evidence for substantial improvement in robustness against various test data perturbations for feed-forward DNNs when trained under NINR. The novelty in our approach comes from the interplay of adaptive noise injection and initialization conditions such that noise is the dominant driver of dynamics at the start of training. As it simply requires the addition of external nodes without altering the existing network structure or optimization algorithms, this method can be easily incorporated into many standard problem specifications. We find improved stability against a number of data perturbations, including domain shifts, with the most dramatic improvement obtained for unstructured noise, where our technique outperforms other existing methods such as Dropout or $L_2$ regularization, in some cases. We further show that desirable generalization properties on clean data are generally maintained., Comment: 16 pages, 9 figures
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- 2022
167. Useful Confidence Measures: Beyond the Max Score
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Yona, Gal, Feder, Amir, and Laish, Itay
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Computer Science - Machine Learning - Abstract
An important component in deploying machine learning (ML) in safety-critic applications is having a reliable measure of confidence in the ML model's predictions. For a classifier $f$ producing a probability vector $f(x)$ over the candidate classes, the confidence is typically taken to be $\max_i f(x)_i$. This approach is potentially limited, as it disregards the rest of the probability vector. In this work, we derive several confidence measures that depend on information beyond the maximum score, such as margin-based and entropy-based measures, and empirically evaluate their usefulness, focusing on NLP tasks with distribution shifts and Transformer-based models. We show that when models are evaluated on the out-of-distribution data ``out of the box'', using only the maximum score to inform the confidence measure is highly suboptimal. In the post-processing regime (where the scores of $f$ can be improved using additional in-distribution held-out data), this remains true, albeit less significant. Overall, our results suggest that entropy-based confidence is a surprisingly useful measure., Comment: Short paper; appeared in the Workshop on Distribution Shifts @ NeurIPS 2022
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- 2022
168. Noise Injection as a Probe of Deep Learning Dynamics
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Levi, Noam, Bloch, Itay, Freytsis, Marat, and Volansky, Tomer
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Computer Science - Machine Learning ,Condensed Matter - Statistical Mechanics ,Computer Science - Artificial Intelligence ,Statistics - Machine Learning - Abstract
We propose a new method to probe the learning mechanism of Deep Neural Networks (DNN) by perturbing the system using Noise Injection Nodes (NINs). These nodes inject uncorrelated noise via additional optimizable weights to existing feed-forward network architectures, without changing the optimization algorithm. We find that the system displays distinct phases during training, dictated by the scale of injected noise. We first derive expressions for the dynamics of the network and utilize a simple linear model as a test case. We find that in some cases, the evolution of the noise nodes is similar to that of the unperturbed loss, thus indicating the possibility of using NINs to learn more about the full system in the future., Comment: 11 pages, 3 figures
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- 2022
169. Unreachability of Inductive-Like Pointclasses in $L(\mathbb{R})$
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Levinson, Derek, Neeman, Itay, and Sargsyan, Grigor
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Mathematics - Logic - Abstract
Hjorth proved from $ZF + AD + DC$ that there is no sequence of distinct $\Sigma^1_2$ sets of length $\delta^1_2$. Sargsyan extended Hjorth's technique to show there is no sequence of distinct $\Sigma^1_{2n}$ sets of length $\delta^1_{2n}$. Sargsyan conjectured an analogous property is true for any regular Suslin pointclass in $L(R)$ -- i.e. if $\kappa$ is a regular Suslin cardinal in $L(R)$, then there is no sequence of distinct $\kappa$-Suslin sets of length $\kappa^+$ in $L(R)$. We prove this in the case that the pointclass $S(\kappa)$ is inductive-like.
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- 2022
170. First constraints on light sterile neutrino oscillations from combined appearance and disappearance searches with the MicroBooNE detector
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MicroBooNE collaboration, Abratenko, P., Aldana, D. Andrade, Anthony, J., Arellano, L., Asaadi, J., Ashkenazi, A., Balasubramanian, S., Baller, B., Barr, G., Barrow, J., Basque, V., Bathe-Peters, L., Rodrigues, O. Benevides, Berkman, S., Bhanderi, A., Bhattacharya, M., Bishai, M., Blake, A., Bogart, B., Bolton, T., Book, J. Y., Camilleri, L., Caratelli, D., Terrazas, I. Caro, Cavanna, F., Cerati, G., Chen, Y., Conrad, J. M., Convery, M., Cooper-Troendle, L., Crespo-Anadon, J. I., Del Tutto, M., Dennis, S. R., Detje, P., Devitt, A., Diurba, R., Dorrill, R., Duffy, K., Dytman, S., Eberly, B., Ereditato, A., Evans, J. J., Fine, R., Finnerud, O. G., Fleming, B. T., Foppiani, N., Foreman, W., Franco, D., Furmanski, A. P., Garcia-Gamez, D., Gardiner, S., Ge, G., Gollapinni, S., Goodwin, O., Gramellini, E., Green, P., Greenlee, H., Gu, W., Guenette, R., Guzowski, P., Hagaman, L., Hen, O., Hicks, R., Hilgenberg, C., Horton-Smith, G. A., Irwin, B., Itay, R., James, C., Ji, X., Jiang, L., Jo, J. H., Johnson, R. A., Jwa, Y. J., Kalra, D., Kamp, N., Karagiorgi, G., Ketchum, W., Kirby, M., Kobilarcik, T., Kreslo, I., Leibovitch, M. B., Lepetic, I., Li, J. -Y., Li, K., Li, Y., Lin, K., Littlejohn, B. R., Louis, W. C., Luo, X., Manivannan, K., Mariani, C., Marsden, D., Marshall, J., Martinez, N., Caicedo, D. A. Martinez, Mason, K., Mastbaum, A., McConkey, N., Meddage, V., Miller, K., Mills, J., Mistry, K., Mohayai, T., Mogan, A., Mooney, M., Moor, A. F., Moore, C. D., Lepin, L. Mora, Mousseau, J., Babu, S. Mulleria, Naples, D., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nowak, J., Nunes, M., Oza, N., Palamara, O., Pallat, N., Paolone, V., Papadopoulou, A., Papavassiliou, V., Parkinson, H., Pate, S. F., Patel, N., Pavlovic, Z., Piasetzky, E., Ponce-Pinto, I., Pophale, I., Prince, S., Qian, X., Raaf, J. L., Radeka, V., Reggiani-Guzzo, M., Ren, L., Rochester, L., Rondon, J. Rodriguez, Rosenberg, M., Ross-Lonergan, M., von Rohr, C. Rudolph, Scanavini, G., Schmitz, D. W., Schukraft, A., Seligman, W., Shaevitz, M. H., Sharankova, R., Shi, J., Smith, A., Snider, E. L., Soderberg, M., Soldner-Rembold, S., Spitz, J., Stancari, M., John, J. St., Strauss, T., Sword-Fehlberg, S., Szelc, A. M., Tang, W., Taniuchi, N., Terao, K., Thorpe, C., Torbunov, D., Totani, D., Toups, M., Tsai, Y. -T., Tyler, J., Uchida, M. A., Usher, T., Viren, B., Weber, M., Wei, H., White, A. J., Williams, Z., Wolbers, S., Wongjirad, T., Wospakrik, M., Wresilo, K., Wright, N., Wu, W., Yandel, E., Yang, T., Yates, L. E., Yu, H. W., Zeller, G. P., Zennamo, J., and Zhang, C.
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High Energy Physics - Experiment - Abstract
We present a search for eV-scale sterile neutrino oscillations in the MicroBooNE liquid argon detector, simultaneously considering all possible appearance and disappearance effects within the $3+1$ active-to-sterile neutrino oscillation framework. We analyze the neutrino candidate events for the recent measurements of charged-current $\nu_e$ and $\nu_{\mu}$ interactions in the MicroBooNE detector, using data corresponding to an exposure of 6.37$\times$10$^{20}$ protons on target from the Fermilab booster neutrino beam. We observe no evidence of light sterile neutrino oscillations and derive exclusion contours at the $95\%$ confidence level in the plane of the mass-squared splitting $\Delta m^2_{41}$ and the sterile neutrino mixing angles $\theta_{\mu e}$ and $\theta_{ee}$, excluding part of the parameter space allowed by experimental anomalies. Cancellation of $\nu_e$ appearance and $\nu_e$ disappearance effects due to the full $3+1$ treatment of the analysis leads to a degeneracy when determining the oscillation parameters, which is discussed in this paper and will be addressed by future analyses., Comment: 9 pages, 4 figures; supplemental: 6 pages, 8 figures
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- 2022
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171. Adversarial Attack Against Image-Based Localization Neural Networks
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Brand, Meir, Naeh, Itay, and Teitelman, Daniel
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning - Abstract
In this paper, we present a proof of concept for adversarially attacking the image-based localization module of an autonomous vehicle. This attack aims to cause the vehicle to perform a wrong navigational decisions and prevent it from reaching a desired predefined destination in a simulated urban environment. A database of rendered images allowed us to train a deep neural network that performs a localization task and implement, develop and assess the adversarial pattern. Our tests show that using this adversarial attack we can prevent the vehicle from turning at a given intersection. This is done by manipulating the vehicle's navigational module to falsely estimate its current position and thus fail to initialize the turning procedure until the vehicle misses the last opportunity to perform a safe turn in a given intersection., Comment: 13 pages, 10 figures
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- 2022
172. A definable $(p,q)$-theorem for NIP theories
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Kaplan, Itay
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Mathematics - Logic - Abstract
We prove a definable version of Matou\v{s}ek's $(p,q)$-theorem in NIP theories. This answers a question of Chernikov and Simon. We also prove a uniform version. The proof builds on a proof of Boxall and Kestner who proved this theorem in the distal case, utilizing the notion of locally compressible types which appeared in the work of the author with Bays and Simon., Comment: Added section 4.1 about VC-density
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- 2022
173. On the Fourier coefficients of word maps on unitary groups
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Avni, Nir and Glazer, Itay
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Mathematics - Probability ,Mathematics - Group Theory ,60B15, 60B20 (Primary) 43A75, 20P05, 20B30 (Secondary) - Abstract
Given a word $w(x_{1},\ldots,x_{r})$, i.e., an element in the free group on $r$ elements, and an integer $d\geq1$, we study the characteristic polynomial of the random matrix $w(X_{1},\ldots,X_{r})$, where $X_{i}$ are Haar-random independent $d\times d$ unitary matrices. If $c_{m}(X)$ denotes the $m$-th coefficient of the characteristic polynomial of $X$, our main theorem implies that there is a positive constant $\epsilon(w)$, depending only on $w$, such that \[ \left|\mathbb{E}\left(c_{m}\left(w(X_{1},\ldots,X_{r})\right)\right)\right|\leq\left(\begin{array}{c} d\\ m \end{array}\right)^{1-\epsilon(w)}, \] for every $d$ and every $1\leq m\leq d$. Our main computational tool is the Weingarten Calculus, which allows us to express integrals on unitary groups such as the expectation above, as certain sums on symmetric groups. We exploit a hidden symmetry to find cancellations in the sum expressing $\mathbb{E}\left(c_{m}(w)\right)$. These cancellations, coming from averaging a Weingarten function over cosets, follow from Schur's orthogonality relations., Comment: 30 pages, second version following feedback from the referees. To appear in Compositio Mathematica
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- 2022
174. Progressing, not regressing: A possible solution to the problem of regression to the mean in unconscious processing studies
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Yaron, Itay, Zeevi, Yoav, Korisky, Uri, Marshall, William, and Mudrik, Liad
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- 2024
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175. Informal Volunteering and Immigrant Generations: Exploring Overlooked Dimensions in Immigrant Volunteering Research
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Greenspan, Itay and Walk, Marlene
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- 2024
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176. Blepharoptosis and cognitive performance: a population-based study of 1.4 million adolescents
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Nitzan, Itay, Derazne, Estela, Afek, Arnon, Gur, Zvi, Weinstein, Orly, Twig, Gilad, and Zloto, Ofira
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- 2024
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177. Does experience with total knee arthroplasty in morbidly obese patients effect surgical outcomes
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Shichman, Ittai, Oakley, Christian T., Ashkenazi, Itay, Marwin, Scott, Meftah, Morteza, and Schwarzkopf, Ran
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- 2024
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178. NASDUCK SERF: New constraints on axion-like dark matter from a SERF comagnetometer
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Bloch, Itay M., Shaham, Roy, Hochberg, Yonit, Kuflik, Eric, Volansky, Tomer, and Katz, Or
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High Energy Physics - Phenomenology ,High Energy Physics - Experiment ,Physics - Atomic Physics ,Quantum Physics - Abstract
Ultralight axion-like particles are well-motivated relics that might compose the cosmological dark matter and source anomalous time-dependent magnetic fields. We report on new terrestrial bounds on the coupling of axion-like particles to neutrons and protons using the nuclei of noble-gas and alkali-metal atoms in a comagnetometer detector operating in the Spin-Exchange Relaxation-Free~(SERF) regime. Conducting a month-long search, we cover the mass range of $1.4\times 10^{-12}$ eV/$c^2$ to $2\times 10^{-10}$~eV/$c^2$ and provide world-leading limits which supersede robust astrophysical bounds and improve upon previous terrestrial constraints by up to two orders of magnitudes for many masses within this range. These are the first reliable terrestrial bounds reported on the coupling of protons with axion-like dark matter, covering a new and unexplored terrain in its parameter space.
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- 2022
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179. Quasi-spiral solution to the mixed intracluster medium and the universal entropy profile of galaxy clusters
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Keshet, Uri, Raveh, Itay, and Ghosh, Arka
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Astrophysics - Cosmology and Nongalactic Astrophysics ,Astrophysics - Astrophysics of Galaxies - Abstract
Well-resolved galaxy clusters often show a large-scale quasi-spiral structure in deprojected density $\rho$ and temperature $T$ fields, delineated by a tangential discontinuity known as a cold front, superimposed on a universal radial entropy profile with a linear $K(r)\propto T\rho^{-2/3}\propto r$ adiabat. We show that a spiral structure provides a natural quasi-stationary solution for the mixed intracluster medium (ICM), introducing a modest pressure spiral that confines the locally buoyant or heavy plasma phases. The solution persists in the presence of uniform or differential rotation, and can accommodate both an inflow and an outflow. Hydrodynamic adiabatic simulations with perturbations that deposit angular momentum and mix the plasma thus asymptote to a self-similar spiral structure. We find similar spirals in Eulerian and Lagrangian simulations of 2D and 3D, merger and offset, clusters. The discontinuity surface is given in spherical coordinates $\{r,\theta,\phi\}$ by $\phi(r,\theta)\propto \Phi(r)$, where $\Phi$ is the gravitational potential, combining a trailing spiral in the equatorial ($\theta=\pi/2$) plane and semicircles perpendicular to the plane, in resemblance of a snail shell. A local convective instability can develop between spiral windings, driving a modified global instability in sublinear $K(r)$ regions; evolved spirals thus imprint the observed $K\propto r$ onto the ICM even after they dissipate. The spiral structure brings hot and cold phases to close proximity, suggesting that the observed fast outflows could sustain the structure even in the presence of radiative cooling., Comment: Revised version to appear in MNRAS
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- 2022
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180. Differential cross section measurement of charged current $\nu_{e}$ interactions without final-state pions in MicroBooNE
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MicroBooNE collaboration, Abratenko, P., Anthony, J., Arellano, L., Asaadi, J., Ashkenazi, A., Balasubramanian, S., Baller, B., Barnes, C., Barr, G., Barrow, J., Basque, V., Bathe-Peters, L., Rodrigues, O. Benevides, Berkman, S., Bhanderi, A., Bhattacharya, M., Bishai, M., Blake, A., Bogart, B., Bolton, T., Book, J. Y., Camilleri, L., Caratelli, D., Terrazas, I. Caro, Cavanna, F., Cerati, G., Chen, Y., Conrad, J. M., Convery, M., Cooper-Troendle, L., Crespo-Anadon, J. I., Del Tutto, M., Dennis, S. R., Detje, P., Devitt, A., Diurba, R., Dorrill, R., Duffy, K., Dytman, S., Eberly, B., Ereditato, A., Evans, J. J., Fine, R., Finnerud, O. G., Fleming, B. T., Foppiani, N., Foreman, W., Franco, D., Furmanski, A. P., Garcia-Gamez, D., Gardiner, S., Ge, G., Gollapinni, S., Goodwin, O., Gramellini, E., Green, P., Greenlee, H., Gu, W., Guenette, R., Guzowski, P., Hagaman, L., Hen, O., Hicks, R., Hilgenberg, C., Horton-Smith, G. A., Irwin, B., Itay, R., James, C., Ji, X., Jiang, L., Jo, J. H., Johnson, R. A., Jwa, Y. J., Kalra, D., Kamp, N., Karagiorgi, G., Ketchum, W., Kirby, M., Kobilarcik, T., Kreslo, I., Leibovitch, M. B., Lepetic, I., Li, J. -Y., Li, K., Li, Y., Lin, K., Littlejohn, B. R., Louis, W. C., Luo, X., Manivannan, K., Mariani, C., Marsden, D., Marshall, J., Caicedo, D. A. Martinez, Mason, K., Mastbaum, A., McConkey, N., Meddage, V., Miller, K., Mills, J., Mistry, K., Mohayai, T., Mogan, A., Mooney, M., Moor, A. F., Moore, C. D., Lepin, L. Mora, Mousseau, J., Babu, S. Mulleria, Naples, D., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Newmark, D. A., Nowak, J., Nunes, M., Oza, N., Palamara, O., Pallat, N., Paolone, V., Papadopoulou, A., Papavassiliou, V., Parkinson, H., Pate, S. F., Patel, N., Pavlovic, Z., Piasetzky, E., Ponce-Pinto, I., Prince, S., Qian, X., Raaf, J. L., Radeka, V., Reggiani-Guzzo, M., Ren, L., Rochester, L., Rondon, J. Rodriguez, Rosenberg, M., Ross-Lonergan, M., von Rohr, C. Rudolph, Scanavini, G., Schmitz, D. W., Schukraft, A., Seligman, W., Shaevitz, M. H., Sharankova, R., Shi, J., Smith, A., Snider, E. L., Soderberg, M., Soldner-Rembold, S., Spitz, J., Stancari, M., John, J. St., Strauss, T., Sword-Fehlberg, S., Szelc, A. M., Tang, W., Taniuchi, N., Terao, K., Thorpe, C., Torbunov, D., Totani, D., Toups, M., Tsai, Y. -T., Tyler, J., Uchida, M. A., Usher, T., Viren, B., Weber, M., Wei, H., White, A. J., Williams, Z., Wolbers, S., Wongjirad, T., Wospakrik, M., Wresilo, K., Wright, N., Wu, W., Yandel, E., Yang, T., Yates, L. E., Yu, H. W., Zeller, G. P., Zennamo, J., and Zhang, C.
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High Energy Physics - Experiment - Abstract
In this letter we present the first measurements of an exclusive electron neutrino cross section with the MicroBooNE experiment using data from the Booster Neutrino Beamline at Fermilab. These measurements are made for a selection of charged-current electron neutrinos without final-state pions. Differential cross sections are extracted in energy and angle with respect to the beam for the electron and the leading proton. The differential cross section as a function of proton energy is measured using events with protons both above and below the visibility threshold. This is done by including a separate selection of electron neutrino events without reconstructed proton candidates in addition to those with proton candidates. Results are compared to the predictions from several modern generators, and we find the data agrees well with these models. The data shows best agreement, as quantified by $p$-value, with the generators that predict a lower overall cross section, such as GENIE v3 and NuWro.
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- 2022
181. The Coven-Meyerowitz tiling conditions for 3 prime factors: the even case
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Laba, Izabella and Londner, Itay
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Mathematics - Combinatorics ,Mathematics - Classical Analysis and ODEs ,Mathematics - Number Theory ,05B45, 11B75, 20K01 - Abstract
We consider finite sets $A\subset\mathbb{Z}$ tiles the integers by translations. By periodicity, any such tiling is equivalent to a factorization $A\oplus B=\mathbb{Z}_M$ of a finite cyclic group. Building on por previous work, we prove that a tentative characterization of finite tiles proposed by Coven and Meyerowitz holds for all integer tilings of period $M=(p_ip_jp_k)^2$, where $p_i,p_j,p_k$ are distinct primes. This extends the main result of [15] (Invent. Math. 2023), where we assumed that $M$ is odd. We also improve parts of the argument from [15]. We have split the earlier (70-page) version into two papers. The current version (49 pages) is the first of the two. The main result is the same as in the previous version: we prove (T2) in the 3-prime even case. The second paper will be posted shortly as a new submission. It will have a new main result where we prove (T2) for a new class of tilings (proved very recently, not included in v1 of this paper). Splitting-related results from the earlier 70-page version of this paper have been moved there., Comment: 49 pages. This is the first one of the two papers replacing v1; see abstract for details. arXiv admin note: text overlap with arXiv:2106.14044
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- 2022
182. Search for long-lived heavy neutral leptons and Higgs portal scalars decaying in the MicroBooNE detector
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MicroBooNE collaboration, Abratenko, P., Anthony, J., Arellano, L., Asaadi, J., Ashkenazi, A., Balasubramanian, S., Baller, B., Barnes, C., Barr, G., Barrow, J., Basque, V., Bathe-Peters, L., Rodrigues, O. Benevides, Berkman, S., Bhanderi, A., Bhattacharya, M., Bishai, M., Blake, A., Bogart, B., Bolton, T., Book, J. Y., Camilleri, L., Caratelli, D., Terrazas, I. Caro, Cavanna, F., Cerati, G., Chen, Y., Conrad, J. M., Convery, M., Cooper-Troendle, L., Crespo-Anadon, J. I., Del Tutto, M., Dennis, S. R., Detje, P., Devitt, A., Diurba, R., Dorrill, R., Duffy, K., Dytman, S., Eberly, B., Ereditato, A., Evans, J. J., Fine, R., Finnerud, O. G., Fleming, B. T., Foppiani, N., Foreman, W., Franco, D., Furmanski, A. P., Garcia-Gamez, D., Gardiner, S., Ge, G., Gollapinni, S., Goodwin, O., Gramellini, E., Green, P., Greenlee, H., Gu, W., Guenette, R., Guzowski, P., Hagaman, L., Hen, O., Hicks, R., Hilgenberg, C., Horton-Smith, G. A., Itay, R., James, C., Ji, X., Jiang, L., Jo, J. H., Johnson, R. A., Jwa, Y. J., Kalra, D., Kamp, N., Kaneshige, N., Karagiorgi, G., Ketchum, W., Kirby, M., Kobilarcik, T., Kreslo, I., Leibovitch, M. B., Lepetic, I., Li, J. -Y., Li, K., Li, Y., Lin, K., Littlejohn, B. R., Louis, W. C., Luo, X., Manivannan, K., Mariani, C., Marsden, D., Marshall, J., Caicedo, D. A. Martinez, Mason, K., Mastbaum, A., McConkey, N., Meddage, V., Miller, K., Mills, J., Mistry, K., Mohayai, T., Mogan, A., Mooney, M., Moor, A. F., Moore, C. D., Lepin, L. Mora, Mousseau, J., Babu, S. Mulleria, Naples, D., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Newmark, D. A., Nowak, J., Nunes, M., Oza, N., Palamara, O., Pallat, N., Paolone, V., Papadopoulou, A., Papavassiliou, V., Parkinson, H., Pate, S. F., Patel, N., Pavlovic, Z., Piasetzky, E., Ponce-Pinto, I., Prince, S., Qian, X., Raaf, J. L., Radeka, V., Rafique, A., Reggiani-Guzzo, M., Ren, L., Rice, L. C. J., Rochester, L., Rondon, J. Rodriguez, Rosenberg, M., Ross-Lonergan, M., von Rohr, C. Rudolph, Scanavini, G., Schmitz, D. W., Schukraft, A., Seligman, W., Shaevitz, M. H., Sharankova, R., Shi, J., Smith, A., Snider, E. L., Soderberg, M., Soldner-Rembold, S., Spitz, J., Stancari, M., John, J. St., Strauss, T., Sword-Fehlberg, S., Szelc, A. M., Tang, W., Taniuchi, N., Terao, K., Thorpe, C., Torbunov, D., Totani, D., Toups, M., Tsai, Y. -T., Tyler, J., Uchida, M. A., Usher, T., Viren, B., Weber, M., Wei, H., White, A. J., Williams, Z., Wolbers, S., Wongjirad, T., Wospakrik, M., Wresilo, K., Wright, N., Wu, W., Yandel, E., Yang, T., Yates, L. E., Yu, H. W., Zeller, G. P., Zennamo, J., and Zhang, C.
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High Energy Physics - Experiment - Abstract
We present a search for long-lived Higgs portal scalars (HPS) and heavy neutral leptons (HNL) decaying in the MicroBooNE liquid-argon time projection chamber. The measurement is performed using data collected synchronously with the NuMI neutrino beam from Fermilab's Main Injector with a total exposure corresponding to $7.01 \times 10^{20}$ protons on target. We set upper limits at the $90\%$ confidence level on the mixing parameter $\lvert U_{\mu 4}\rvert^2$ ranging from $\lvert U_{\mu 4}\rvert^2<12.9\times 10^{-8}$ for Majorana HNLs with a mass of $m_{\rm HNL}=246$ MeV to $\lvert U_{\mu 4}\rvert^2<0.92 \times 10^{-8}$ for $m_{\rm HNL}=385$ MeV, assuming $\lvert U_{e 4}\rvert^2 = \lvert U_{\tau 4}\rvert^2 = 0$ and HNL decays into $\mu^\pm\pi^\mp$ pairs. These limits on $\lvert U_{\mu 4}\rvert^2$ represent an order of magnitude improvement in sensitivity compared to the previous MicroBooNE result. We also constrain the scalar-Higgs mixing angle $\theta$ by searching for HPS decays into $\mu^+\mu^-$ final states, excluding a contour in the parameter space with lower bounds of $\theta^2<31.3 \times 10^{-9}$ for $m_{\rm HPS}=212$ GeV and $\theta^2<1.09 \times 10^{-9}$ for $m_{\rm HPS}=275$ GeV. These are the first constraints on the scalar-Higgs mixing angle $\theta$ from a dedicated experimental search in this mass range., Comment: This paper is dedicated to the memory of Salvatore Davide Porzio. This is the journal accepted version with only minor presentational changes compared to preprint
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- 2022
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183. Roadmap to Thermal Dark Matter Beyond the WIMP Unitarity Bound
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Frumkin, Ronny, Kuflik, Eric, Lavie, Itay, and Silverwater, Tal
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High Energy Physics - Phenomenology - Abstract
We study the general properties of the freezeout of a thermal relic. We give analytic estimates of the relic abundance for an arbitrary freezeout process, showing when instantaneous freezeout is appropriate and how it can be corrected when freezeout is slow. This is used to generalize the relationship between the dark mater mass and coupling that matches the observed abundance. The result encompasses well-studied particular examples, such as WIMPs, SIMPs, coannihilation, coscattering, inverse decays, and forbidden channels, and generalizes beyond them. In turn, this gives an approximate perturbative unitarity bound on the dark matter mass for an arbitrary thermal freezeout process. We show that going beyond the maximal masses allowed for freezeout via dark matter self-annihilations (WIMP-like, $m_{\rm DM}\gg\mathcal{O}(100~\rm TeV)$) predicts that there are nearly degenerate states with the dark matter and that the dark matter is generically metastable. We show how freezeout of a thermal relic may allow for dark matter masses up to the Planck scale., Comment: 8 pages, 4 figrues
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- 2022
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184. Isolating sensory artifacts in the suprathreshold TMS-EEG signal over DLPFC
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Poorganji, Mohsen, Zomorrodi, Reza, Hawco, Colin, Hill, Aron T, Hadas, Itay, Zrenner, Christoph, Rajji, Tarek K, Chen, Robert, Voineskos, Daphne, Blumberger, Daniel M, and Daskalakis, Zafiris J
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Biomedical and Clinical Sciences ,Clinical Sciences ,Physical Sciences ,Neurosciences ,Clinical Research ,Brain Disorders ,Humans ,Dorsolateral Prefrontal Cortex ,Artifacts ,Electroencephalography ,Evoked Potentials ,Transcranial Magnetic Stimulation ,Evoked Potentials ,Motor - Abstract
Combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) is an effective way to evaluate neurophysiological processes at the level of the cortex. To further characterize the TMS-evoked potential (TEP) generated with TMS-EEG, beyond the motor cortex, we aimed to distinguish between cortical reactivity to TMS versus non-specific somatosensory and auditory co-activations using both single-pulse and paired-pulse protocols at suprathreshold stimulation intensities over the left dorsolateral prefrontal cortex (DLPFC). Fifteen right-handed healthy participants received six blocks of stimulation including single and paired TMS delivered as active-masked (i.e., TMS-EEG with auditory masking and foam spacing), active-unmasked (TMS-EEG without auditory masking and foam spacing) and sham (sham TMS coil). We evaluated cortical excitability following single-pulse TMS, and cortical inhibition following a paired-pulse paradigm (long-interval cortical inhibition (LICI)). Repeated measure ANOVAs revealed significant differences in mean cortical evoked activity (CEA) of active-masked, active-unmasked, and sham conditions for both the single-pulse (F(1.76, 24.63) = 21.88, p
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- 2023
185. Pre-Stimulus Power but Not Phase Predicts Prefrontal Cortical Excitability in TMS-EEG
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Poorganji, Mohsen, Zomorrodi, Reza, Zrenner, Christoph, Bansal, Aiyush, Hawco, Colin, Hill, Aron T, Hadas, Itay, Rajji, Tarek K, Chen, Robert, Zrenner, Brigitte, Voineskos, Daphne, Blumberger, Daniel M, and Daskalakis, Zafiris J
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Analytical Chemistry ,Biochemistry and Cell Biology ,Chemical Sciences ,Biological Sciences ,Neurosciences ,Brain Disorders ,Clinical Research ,Neurological ,Humans ,Brain ,Cortical Excitability ,Electroencephalography ,Transcranial Magnetic Stimulation ,TMS-EEG ,cortical oscillations ,brain state ,phase before TMS ,EEG power before TMS ,Biochemistry and cell biology ,Analytical chemistry - Abstract
The cortical response to transcranial magnetic stimulation (TMS) has notable inter-trial variability. One source of this variability can be the influence of the phase and power of pre-stimulus neuronal oscillations on single-trial TMS responses. Here, we investigate the effect of brain oscillatory activity on TMS response in 49 distinct healthy participants (64 datasets) who had received single-pulse TMS over the left dorsolateral prefrontal cortex. Across all frequency bands of theta (4-7 Hz), alpha (8-13 Hz), and beta (14-30 Hz), there was no significant effect of pre-TMS phase on single-trial cortical evoked activity. After high-powered oscillations, whether followed by a TMS pulse or not, the subsequent activity was larger than after low-powered oscillations. We further defined a measure, corrected_effect, to enable us to investigate brain responses to the TMS pulse disentangled from the power of ongoing (spontaneous) oscillations. The corrected_effect was significantly different from zero (meaningful added effect of TMS) only in theta and beta bands. Our results suggest that brain state prior to stimulation might play some role in shaping the subsequent TMS-EEG response. Specifically, our findings indicate that the power of ongoing oscillatory activity, but not phase, can influence brain responses to TMS. Aligning the TMS pulse with specific power thresholds of an EEG signal might therefore reduce variability in neurophysiological measurements and also has the potential to facilitate more robust therapeutic effects of stimulation.
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- 2023
186. Bringing the field into the lab: a novel virtual reality outdoor march simulator for evaluating cognitive and physical performance
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Kimel Naor, Shani, Ketko, Itay, Yanovich, Ran, Gottlieb, Amihai, Bahat, Yotam, Ben-Gal, Oran, Heled, Yuval, and Plotnik, Meir
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- 2024
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187. How Many Neurons Does it Take to Approximate the Maximum?
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Safran, Itay, primary, Reichman, Daniel, additional, and Valiant, Paul, additional
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- 2024
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188. Design and Control of a Novel Semi-Passive Knee Exoskeleton.
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Alon Sade, Itay Coifman, Raziel Riemer, and David Zarrouk
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- 2024
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189. PD-Explain: A Unified Python-native Framework for Query Explanations Over DataFrames.
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Itay Elyashiv, Amir Gilad, Edna Isakov, Tal Tikochinsky, and Amit Somech
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- 2024
190. DIPER: Detection and Identification of Pathogens Using Edit Distance-Tolerant Resistive CAM.
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Itay Merlin, Esteban Garzón, Alexander Fish, and Leonid Yavits
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- 2024
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191. GSP-KalmanNet: Tracking Graph Signals via Neural-Aided Kalman Filtering.
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Itay Buchnik, Guy Sagi, Nimrod Leinwand, Yuval Loya, Nir Shlezinger, and Tirza Routtenberg
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- 2024
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192. Effort Peer Effects in Team Production: Evidence from Professional Football.
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Danny Cohen-Zada, Itay Dayag, and Naomi Gershoni
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- 2024
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193. Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora
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DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Ahmad, Z., Ahmed, J., Aimard, B., Akbar, F., Ali-Mohammadzadeh, B., Allison, K., Monsalve, S. Alonso, AlRashed, M., Alt, C., Alton, A., Alvarez, R., Amedo, P., Anderson, J., Andreopoulos, C., Andreotti, M., Andrews, M., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antoniassi, M., Antonova, M., Antoshkin, A., Antusch, S., Aranda-Fernandez, A., Arellano, L., Arnold, L. O., Arroyave, M. A., Asaadi, J., Asquith, L., Aurisano, A., Aushev, V., Autiero, D., Lara, V. Ayala, Ayala-Torres, M., Azfar, F., Back, A., Back, H., Back, J. J., Backhouse, C., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baller, B., Bambah, B., Barao, F., Barenboim, G., Barker, G., Barkhouse, W., Barnes, C., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Battat, J., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Chagas, E. Belchior Batista das, Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Neves, F. Bento, Berger, J., Berkman, S., Bernardini, P., Berner, R. M., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhardwaj, A., Bhatnagar, V., Bhattacharjee, M., Bhattarai, D., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biassoni, M., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. d. M., Blazey, G. C., Blucher, E., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Borkum, A., Bostan, N., Bour, P., Boyden, D., Bracinik, J., Braga, D., Brailsford, D., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Butorov, I., Cagnoli, I., Cai, T., Caiulo, D., Calabrese, R., Calafiura, P., Calcutt, J., Calin, M., Calvez, S., Calvo, E., Caminata, A., Benitez, A. Campos, Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carroll, T., Forero, J. F. Castaño, Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavallaro, G., Cavanna, F., Centro, S., Cerati, G., Cervelli, A., Villanueva, A. Cervera, Chalifour, M., Chappell, A., Chardonnet, E., Charitonidis, N., Chatterjee, A., Chattopadhyay, S., Neyra, M. S. Chavarry, Chen, H., Chen, M., Chen, Y., Chen, Z., Chen-Wishart, Z., Cheon, Y., Cherdack, D., Chi, C., Childress, S., Chirco, R., Chiriacescu, A., Cho, K., Choate, S., Chokheli, D., Chong, P. S., Christensen, A., Christian, D., Christodoulou, G., Chukanov, A., Chung, M., Church, E., Cicero, V., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J., Collot, J., Colton, N., Conley, E., Conley, R., Conrad, J., Convery, M., Copello, S., Cova, P., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Cussans, D., Dai, J., Dalager, O., Da Motta, H., Peres, L. Da Silva, David, C., David, Q., Davies, G. S., Davini, S., Dawson, J., De, K., De, S., Debbins, P., De Bonis, I., Decowski, M., De Gouvea, A., De Holanda, P. C., Astiz, I. L. De Icaza, Deisting, A., De Jong, P., Delbart, A., De Leo, V., Delepine, D., Delgado, M., Dell'Acqua, A., Delmonte, N., De Lurgio, P., Neto, J. R. De Mello, DeMuth, D. M., Dennis, S., Densham, C., Deptuch, G. W., De Roeck, A., De Romeri, V., De Souza, G., Devi, R., Dharmapalan, R., Dias, M., Diaz, J., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Giulio, L., Ding, P., Di Noto, L., Dirkx, G., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M., Domine, L., Donon, Y., Douglas, D., Dragone, A., Drake, G., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dunne, P., Dutta, B., Duyang, H., Dvornikov, O., Dwyer, D., Dyshkant, A., Eads, M., Earle, A., Edmunds, D., Eisch, J., Emberger, L., Emery, S., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C., Sanchez, L. Escudero, Eurin, G., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Falcone, A., Fani', M., Farnese, C., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Menendez, P. Fernandez, Ferraro, F., Fields, L., Filip, P., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fischer, V., Fitzpatrick, R. S., Flanagan, W., Fleming, B., Flight, R., Fogarty, S., Foreman, W., Fowler, J., Fox, W., Franc, J., Francis, K., Franco, D., Freeman, J., Freestone, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gabrielli, A., Gago, A., Gallagher, H., Gallas, A., Gallego-Ros, A., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardiner, S., Gastler, D., Gauvreau, J., Gauzzi, P., Ge, G., Geffroy, N., Gelli, B., Gendotti, A., Gent, S., Ghorbani-Moghaddam, Z., Giammaria, P., Giammaria, T., Giangiacomi, N., Gibin, D., Gil-Botella, I., Gilligan, S., Girerd, C., Giri, A., Gnani, D., Gogota, O., Gold, M., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Caamaño, D. González, Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goodwin, O., Goswami, S., Gotti, C., Goudzovski, E., Grace, C., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D., Green, P., Green, S., Greenberg, S., Greenler, L., Greer, J., Grenard, J., Griffith, C., Groh, M., Grudzinski, J., Grzelak, K., Gu, W., Guardincerri, E., Guarino, V., Guarise, M., Guenette, R., Guerard, E., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Gupta, A., Gupta, V., Guthikonda, K., Guzowski, P., Guzzo, M. M., Gwon, S., Ha, C., Haaf, K., Habig, A., Hadavand, H., Haenni, R., Hahn, A., Haiston, J., Hamacher-Baumann, P., Hamernik, T., Hamilton, P., Han, J., Harris, D. A., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C., Hatcher, R., Hatfield, K. W., Hatzikoutelis, A., Hayes, C., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Henry, S., Morquecho, M. Hernandez, Herner, K., Hewes, V, Hilgenberg, C., Hill, T., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Hoppe, E., Horton-Smith, G. A., Hostert, M., Hourlier, A., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Hulcher, Z., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jediny, F., Jena, D., Jeong, Y., Jesús-Valls, C., Ji, X., Jiang, J., Jiang, L., Jiménez, S., Jipa, A., Joaquim, F., Johnson, W., Johnston, N., Jones, B., Judah, M., Jung, C., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Kamiya, F., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karolak, M., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Kazaryan, N., Kearns, E., Keener, P., Kelly, K. J., Kemp, E., Kemularia, O., Ketchum, W., Kettell, S. H., Khabibullin, M., Khotjantsev, A., Khvedelidze, A., Kim, D., King, B., Kirby, B., Kirby, M., Klein, J., Klustova, A., Kobilarcik, T., Koehler, K., Koerner, L. W., Koh, D. H., Kohn, S., Koller, P. P., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecky, V., Kothekar, K., Kralik, R., Kreczko, L., Krennrich, F., Kreslo, I., Kropp, W., Kroupova, T., Kubota, S., Kudenko, Y., Kudryavtsev, V. A., Kuhlmann, S., Kulagin, S., Kumar, J., Kumar, P., Kunze, P., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kvasnicka, J., Kwak, D., Lambert, A., Land, B., Lane, C. E., Lang, K., Langford, T., Langstaff, M., Larkin, J., Lasorak, P., Last, D., Laundrie, A., Laurenti, G., Lawrence, A., Lazanu, I., LaZur, R., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeBrun, P., LeCompte, T., Lee, C., Lee, S., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. Leigui, Leitner, M., Lepin, L. M., Li, S., Li, Y., Liao, H., Lin, C., Lin, Q., Lin, S., Lineros, R. A., Ling, J., Lister, A., Littlejohn, B. R., Liu, J., Liu, Y., Lockwitz, S., Loew, T., Lokajicek, M., Lomidze, I., Long, K., Lord, T., LoSecco, J., Louis, W. C., Lu, X., Luk, K., Lunday, B., Luo, X., Luppi, E., Lux, T., Luzio, V. P., Maalmi, J., MacFarlane, D., Machado, A., Machado, P., Macias, C., Macier, J., Maddalena, A., Madera, A., Madigan, P., Magill, S., Mahn, K., Maio, A., Major, A., Maloney, J. A., Mandrioli, G., Mandujano, R. C., Maneira, J. C., Manenti, L., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marie, R., Marinho, F., Marino, A. D., Markiewicz, T., Marsden, D., Marshak, M., Marshall, C., Marshall, J., Marteau, J., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Mason, K., Mastbaum, A., Matichard, F., Matsuno, S., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., Mazzacane, A., Mazzucato, E., McAskill, T., McCluskey, E., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Mefodiev, A., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Messier, M., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Michna, G., Mikola, V., Milincic, R., Miller, G., Miller, W., Mills, J., Mineev, O., Minotti, A., Miranda, O. G., Miryala, S., Mishra, C., Mishra, S., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Moffat, K., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J. A., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Moon, S., Mooney, M., Moor, A. F., Moreno, D., Moretti, D., Morris, C., Mossey, C., Mote, M., Motuk, E., Moura, C. A., Mousseau, J., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Mufson, S., Muheim, F., Muir, A., Mulhearn, M., Munford, D., Muramatsu, H., Murphy, M., Murphy, S., Musser, J., Nachtman, J., Nagai, Y., Nagu, S., Nalbandyan, M., Nandakumar, R., Naples, D., Narita, S., Nath, A., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Negishi, K., Nelson, J. K., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Newton, H., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Niner, E., Nishimura, K., Norman, A., Norrick, A., Northrop, R., Novella, P., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J., Olivier, A., Olshevskiy, A., Onel, Y., Onishchuk, Y., Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papadimitriou, V., Papaleo, R., Papanestis, A., Paramesvaran, S., Parke, S., Parozzi, E., Parsa, Z., Parvu, M., Pascoli, S., Pasqualini, L., Pasternak, J., Pater, J., Patrick, C., Patrizii, L., Patterson, R. B., Patton, S., Patzak, T., Paudel, A., Paulos, B., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Pec, V., Peeters, S. J., Perez, A. Pena, Pennacchio, E., Penzo, A., Peres, O. L., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pia, V., Piastra, F., Pickering, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Plows, K., Plunkett, R., Pompa, F., Pons, X., Poonthottathil, N., Poppi, F., Pordes, S., Porter, J., Porzio, S., Potekhin, M., Potenza, R., Potukuchi, B. V., Pozimski, J., Pozzato, M., Prakash, S., Prakash, T., Prest, M., Prince, S., Psihas, F., Pugnere, D., Qian, X., Raaf, J., Radeka, V., Rademacker, J., Radics, B., Rafique, A., Raguzin, E., Rai, M., Rajaoalisoa, M., Rakhno, I., Rakotonandrasana, A., Rakotondravohitra, L., Rameika, R., Delgado, M. Ramirez, Ramson, B., Rappoldi, A., Raselli, G., Ratoff, P., Raut, S., Razafinime, H., Razakamiandra, R., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reggiani-Guzzo, M., Reichenbacher, J., Reitzner, S. D., Sfar, H. Rejeb, Renshaw, A., Rescia, S., Resnati, F., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Rice, L. C., Ricol, J. S., Rigamonti, A., Rigaut, Y., Rincón, E. V., Ritchie-Yates, H., Rivera, D., Robert, A., Rocha, J. Rocabado, Rochester, L., Roda, M., Rodrigues, P., Leite, J. V. Rodrigues da Silva, Alonso, M. J. Rodriguez, Rondon, J. Rodriguez, Rosauro-Alcaraz, S., Rosier, P., Roskovec, B., Rossella, M., Rossi, M., Rout, J., Roy, P., Rubbia, A., Rubbia, C., Russell, B., Ruterbories, D., Rybnikov, A., Saa-Hernandez, A., Saakyan, R., Sacerdoti, S., Sahu, N., Sala, P., Samios, N., Samoylov, O., Sanchez, M., Sandberg, V., Sanders, D. A., Sankey, D., Saoulidou, N., Sapienza, P., Sarasty, C., Sarcevic, I., Savage, G., Savinov, V., Scaramelli, A., Scarff, A., Scarpelli, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Segreto, E., Selyunin, A., Senise Jr., C. R., Sensenig, J., Sgalaberna, D., Shaevitz, M., Shafaq, S., Shaker, F., Shamma, M., Sharankova, R., Sharma, H. R., Sharma, R., Sharma, R. K., Shaw, K., Shaw, T., Shchablo, K., Shepherd-Themistocleous, C., Sheshukov, A., Shin, S., Shoemaker, I., Shooltz, D., Shrock, R., Siegel, H., Simard, L., Sinclair, J., Sinev, G., Singh, J., Singh, L., Singh, P., Singh, V., Sipos, R., Sippach, F., Sirri, G., Sitraka, A., Siyeon, K., Skarpaas, K., Smith, E., Smith, P., Smolik, J., Smy, M., Snider, E., Snopok, P., Snowden-Ifft, D., Nunes, M. Soares, Sobel, H., Soderberg, M., Sokolov, S., Salinas, C. J. Solano, Söldner-Rembold, S., Soleti, S., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Sotnikov, A., Soto-Oton, J., Ugaldi, F. Soto, Sousa, A., Soustruznik, K., Spagliardi, F., Spanu, M., Spitz, J., Spooner, N. J., Spurgeon, K., Stancari, M., Stanco, L., Stanford, C., Stein, R., Steiner, H., Lisbôa, A. F. Steklain, Stewart, J., Stillwell, B., Stock, J., Stocker, F., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Sunción, J. Suárez, Sullivan, H., Surdo, A., Susic, V., Suter, L., Sutera, C., Suvorov, Y., Svoboda, R., Szczerbinska, B., Szelc, A. M., Talukdar, N., Tanaka, H., Tang, S., Oregui, B. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tata, N., Tatar, E., Tayloe, R., Teklu, A., Tennessen, P., Tenti, M., Terao, K., Ternes, C. A., Terranova, F., Testera, G., Thakore, T., Thea, A., Thorn, C., Timm, S., Tishchenko, V., Tomassetti, L., Tonazzo, A., Torbunov, D., Torti, M., Tortola, M., Tortorici, F., Tosi, N., Totani, D., Toups, M., Touramanis, C., Travaglini, R., Trevor, J., Trilov, S., Trzaska, W. H., Tsai, Y., Tsamalaidze, Z., Tsang, K., Tsverava, N., Tu, S. Z., Tufanli, S., Tull, C., Tyler, J., Tyley, E., Tzanov, M., Uboldi, L., Uchida, M. A., Urheim, J., Usher, T., Uzunyan, S., Vagins, M. R., Vahle, P., Valder, S., Valdiviesso, G. D., Valencia, E., Valentim, R., Vallari, Z., Vallazza, E., Valle, J. W., Vallecorsa, S., Van Berg, R., Van de Water, R. G., Forero, D. Vanegas, Vannerom, D., Varanini, F., Oliva, D. Vargas, Varner, G., Vasel, J., Vasina, S., Vasseur, G., Vaughan, N., Vaziri, K., Ventura, S., Verdugo, A., Vergani, S., Vermeulen, M. A., Verzocchi, M., Vicenzi, M., de Souza, H. Vieira, Vignoli, C., Vilela, C., Viren, B., Vrba, T., Wachala, T., Waldron, A. V., Wallbank, M., Wallis, C., Walton, T., Wang, H., Wang, J., Wang, L., Wang, M. H., Wang, X., Wang, Y., Warburton, K., Warner, D., Wascko, M., Waters, D., Watson, A., Wawrowska, K., Weatherly, P., Weber, A., Weber, M., Wei, H., Weinstein, A., Wenman, D., Wetstein, M., White, A., Whitehead, L. H., Whittington, D., Wilking, M. J., Wilkinson, A., Wilkinson, C., Williams, Z., Wilson, F., Wilson, R. J., Wisniewski, W., Wolcott, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wresilo, K., Wret, C., Wu, W., Xiao, Y., Yaeggy, B., Yandel, E., Yang, G., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Yoon, Y., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zazueta, L., Zeller, G., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhang, Y., Zhao, M., Zhivun, E., Zhu, G., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.
- Subjects
High Energy Physics - Experiment ,Physics - Instrumentation and Detectors - Abstract
The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation., Comment: 39 pages, 20 figures. Accepted version. Published version available in Eur. Phys. J. C 83, 618 (2023) https://doi.org/10.1140/epjc/s10052-023-11733-2
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- 2022
- Full Text
- View/download PDF
194. Simultaneous Enantiomer-Resolved Ramsey Spectroscopy Scheme for Chiral Molecules
- Author
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Erez, Itay, Wallach, Eliana Ruth, and Shagam, Yuval
- Subjects
Physics - Atomic Physics ,Physics - Chemical Physics - Abstract
We theoretically introduce a scheme to perform Ramsey spectroscopy on a racemic mixture of chiral molecules, simultaneously extracting the transition frequencies of the left- and right-handed molecules, known as enantiomers. By taking the difference between the enantio-specific frequencies, we isolate the weak force parity violation (PV) shift, which is predicted to break the symmetry between enantiomers. To perform the scheme, we design a pulse sequence that creates enantio-specific superpositions in a three-level system using the enantiomer-dependent sign of the electric-dipole moment components' triple product. A delayed second pulse sequence completes the Ramsey interrogation sequence, enabling readout of the phase evolution for each enantiomer's transition through a separate quantum state. Our technique overcomes the need to alternate between enantio-pure samples to measure PV. We describe the advantages of the proposed method for precision metrology., Comment: 9 pages, 4 figures, added 2 appendix sections
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- 2022
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195. Strategic Classification with Graph Neural Networks
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Eilat, Itay, Finkelshtein, Ben, Baskin, Chaim, and Rosenfeld, Nir
- Subjects
Computer Science - Machine Learning - Abstract
Strategic classification studies learning in settings where users can modify their features to obtain favorable predictions. Most current works focus on simple classifiers that trigger independent user responses. Here we examine the implications of learning with more elaborate models that break the independence assumption. Motivated by the idea that applications of strategic classification are often social in nature, we focus on \emph{graph neural networks}, which make use of social relations between users to improve predictions. Using a graph for learning introduces inter-user dependencies in prediction; our key point is that strategic users can exploit these to promote their goals. As we show through analysis and simulation, this can work either against the system -- or for it. Based on this, we propose a differentiable framework for strategically-robust learning of graph-based classifiers. Experiments on several real networked datasets demonstrate the utility of our approach., Comment: ICLR 2023
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- 2022
196. Shalika models for general linear groups
- Author
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Naor, Itay
- Subjects
Mathematics - Representation Theory ,20G05 (Primary) 46F10, 22E50, 20C33, 22E50 (Secondary) - Abstract
We define a generalization of Shalika models for $GL_{n+m}(F)$ and prove that they are multiplicity-free, where $F$ is either a non-Archimedean local field or a finite field and $n,m$ are any natural numbers. In particular, we give new proof for the case of $n=m$. We also show that the Bernstein-Zelevinsky product of an irreducible representation of $GL_n(F)$ and the trivial representation of $GL_m(F)$ is multiplicity-free. We relate the two results by a conjecture about twisted parabolic induction of Gelfand pairs., Comment: 24 pages. M.Sc. thesis completed at Weizmann Institute of Science under the guidance of Prof. Dmitry Gourevitch
- Published
- 2022
197. Sub-Rate Linear Network Coding
- Author
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Grinboim, Ben, Shrem, Itay, and Amrani, Ofer
- Subjects
Computer Science - Information Theory ,Electrical Engineering and Systems Science - Signal Processing - Abstract
Increasing network utilization is often considered as the holy grail of communications. In this article, the concept of sub-rate coding and decoding in the framework of linear network coding (LNC) is discussed for single-source multiple-sinks finite acyclic networks. Sub-rate coding offers an add-on to existing LNC. It allows sinks whose max-flow is smaller than the source message-rate, termed \emph{sub-rate sinks}, to decode a portion of the transmitted message without degrading the maximum achievable rate of LNC sinks whose max-flow is equal (or greater) than the rate of the source node. The article studies theoretical aspects of sub-rate coding by formulating the conditions a node (and indeed the network) must fulfill so as to qualify as a legitimate sub-rate sink.
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- 2022
198. On large externally definable sets in NIP
- Author
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Bays, Martin, Ben-Neria, Omer, Kaplan, Itay, and Simon, Pierre
- Subjects
Mathematics - Logic ,03C45 - Abstract
We study cofinal systems of finite subsets of $\omega_1$. We show that while such systems can be NIP, they cannot be defined in an NIP structure. We deduce a positive answer to a question of Chernikov and Simon from 2013: in an NIP theory, any uncountable externally definable set contains an infinite definable subset. A similar result holds for larger cardinals., Comment: v2: Corollary 3.11 in v1 had an erroneous proof; it now appears as Theorem 3.8 with a new proof, and part of section 3 has been moved to an appendix v3: Small local improvements
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- 2022
- Full Text
- View/download PDF
199. A Dataset for Sentence Retrieval for Open-Ended Dialogues
- Author
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Harel, Itay, Taitelbaum, Hagai, Szpektor, Idan, and Kurland, Oren
- Subjects
Computer Science - Information Retrieval - Abstract
We address the task of sentence retrieval for open-ended dialogues. The goal is to retrieve sentences from a document corpus that contain information useful for generating the next turn in a given dialogue. Prior work on dialogue-based retrieval focused on specific types of dialogues: either conversational QA or conversational search. To address a broader scope of this task where any type of dialogue can be used, we constructed a dataset that includes open-ended dialogues from Reddit, candidate sentences from Wikipedia for each dialogue and human annotations for the sentences. We report the performance of several retrieval baselines, including neural retrieval models, over the dataset. To adapt neural models to the types of dialogues in the dataset, we explored an approach to induce a large-scale weakly supervised training data from Reddit. Using this training set significantly improved the performance over training on the MS MARCO dataset.
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- 2022
- Full Text
- View/download PDF
200. How catastrophic can catastrophic forgetting be in linear regression?
- Author
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Evron, Itay, Moroshko, Edward, Ward, Rachel, Srebro, Nati, and Soudry, Daniel
- Subjects
Computer Science - Machine Learning ,Mathematics - Numerical Analysis - Abstract
To better understand catastrophic forgetting, we study fitting an overparameterized linear model to a sequence of tasks with different input distributions. We analyze how much the model forgets the true labels of earlier tasks after training on subsequent tasks, obtaining exact expressions and bounds. We establish connections between continual learning in the linear setting and two other research areas: alternating projections and the Kaczmarz method. In specific settings, we highlight differences between forgetting and convergence to the offline solution as studied in those areas. In particular, when T tasks in d dimensions are presented cyclically for k iterations, we prove an upper bound of T^2 * min{1/sqrt(k), d/k} on the forgetting. This stands in contrast to the convergence to the offline solution, which can be arbitrarily slow according to existing alternating projection results. We further show that the T^2 factor can be lifted when tasks are presented in a random ordering.
- Published
- 2022
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