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152. Ultralight vector dark matter search using data from the KAGRA O3GK run

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The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abe, H., Abouelfettouh, I., Acernese, F., Ackley, K., Adamcewicz, C., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Arun, K. G., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Bai, Y., Baier, J. G., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Barthelmy, S. D., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Bazzan, M., Bécsy, B., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Beniwal, D., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Bogaert, G., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boumerdassi, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Santoro, G. Caneva, Cannavacciuolo, M., Cannon, K. C., Cao, H., Cao, Z., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castaldi, G., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, C., Chan, J. C. L., Chan, K. H. M., Chan, M., Chan, W. L., Chandra, K., Chang, R. -J., Chanial, P., Chao, S., Chapman-Bird, C., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chatziioannou, K., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, K. H., Chen, X., Chen, Yi-Ru, Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Chia, H. Y., Chiadini, F., Chiang, C., Chiarini, G., Chiba, A., Chiba, R., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chung, K. W., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Clara, F., Clark, J. A., Clarke, T. A., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Codazzo, E., Cohadon, P. -F., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Conti, L., Cooper, S. J., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Cousins, B., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, D. C., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Croquette, M., Crouch, R., Crowder, S. G., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Daw, E. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., Del Favero, V., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., De Simone, R., Dhani, A., Dhurandhar, S., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Donahue, L., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Drori, Y., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Emma, M., Engelby, E., Engl, A. J., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Fan, P. C., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Fenyvesi, E., Ferguson, D. L., Ferrante, I., Ferreira, T. A., Fidecaro, F., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fukunaga, I., Fulda, P., Fyffe, M., Gabella, W. E., Gadre, B., Gair, J. R., Galaudage, S., Gallardo, S., Gallego, B., Gamba, R., Gamboa, A., Ganapathy, D., Ganguly, A., Gaonkar, S. G., Garaventa, B., Garcia-Bellido, J., García-Núñez, C., García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garron, A., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., George, J., George, R., Gerberding, O., Gergely, L., Ghadiri, N., Ghosh, Archisman, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gibson, D. T., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Gleckl, A. E., Glotin, F., Godfrey, J., Godwin, P., Goebbels, N. L., Goetz, E., Golomb, J., Lopez, S. Gomez, Goncharov, B., González, G., Goodarzi, P., Goodwin-Jones, A. W., Gosselin, M., Göttel, A. S., Gouaty, R., Gould, D. W., Goyal, S., Grace, B., Grado, A., Graham, V., Granados, A. E., Granata, M., Granata, V., Argianas, L. Granda, Gras, S., Grassia, P., Gray, C., Gray, R., Greco, G., Green, A. C., Green, S. M., Green, S. R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimaud, C., Grote, H., Gruson, A. S., Guerra, D., Guetta, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H., Guo, W., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, Ish, Gupta, N. C., Gupta, P., Gupta, S. K., Gupta, T., Gupte, N., Gurav, R., Gurs, J., Gutierrez, N., Guzman, F., Haba, D., Haberland, M., Haegel, L., Hain, G., Haino, S., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hanselman, A. G., Hansen, H., Hanson, J., Harada, R., Harder, T., Haris, K., Harmark, T., Harms, J., Harry, G. M., Harry, I. W., Haskell, B., Haster, C. -J., Hathaway, J. S., Haughian, K., Hayakawa, H., Hayama, K., Healy, J., Heffernan, A., Heidmann, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Hendry, M., Heng, I. S., Hennes, E., Hennig, J. -S., Hennig, M., Henshaw, C., Hernandez, A., Hertog, T., Heurs, M., Hewitt, A. L., Higginbotham, S., Hild, S., Hill, P., Hill, S., Himemoto, Y., Hines, A. S., Hirata, N., Hirose, C., Ho, J., Hoang, S., Hochheim, S., Hofman, D., Holland, N. A., Holley-Bockelmann, K., Hollows, I. J., Holmes, Z. J., Holz, D. E., Hong, C., Hornung, J., Hoshino, S., Hourihane, S., Howell, E. J., Hoy, C. G., Hoyland, D., Hrishikesh, C. A., Hsieh, H. -F., Hsiung, C., Hsu, H. C., Hsu, S. -C., Hsu, W. -F., Hu, P., Hu, Q., Huang, H. Y., Huang, Y. -J., Huang, Y., Huang, Y. T., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V., Hur, R., Husa, S., Huxford, R., Huynh-Dinh, T., Iakovlev, A., Iandolo, G. A., Iess, A., Inayoshi, K., Inoue, Y., Iorio, G., Irwin, J., Isi, M., Ismail, M. A., Itoh, Y., Iwaya, M., Iyer, B. R., JaberianHamedan, V., Jacquet, P. -E., Jadhav, S. J., Jadhav, S. P., Jain, T., James, A. L., James, P. A., Jamshidi, R., Jan, A. Z., Jani, K., Janiurek, L., Janquart, J., Janssens, K., Janthalur, N. N., Jaraba, S., Jaranowski, P., Jasal, P., Jaume, R., Javed, W., Jennings, A., Jia, W., Jiang, J., Jin, H. -B., Johansmeyer, K., Johns, G. R., Johnson, N. A., Johnston, R., Johny, N., Jones, D. H., Jones, D. I., Jones, R., Jose, S., Joshi, P., Ju, L., Jung, K., Junker, J., Juste, V., Kajita, T., Kalaghatgi, C., Kalogera, V., Kamiizumi, M., Kanda, N., Kandhasamy, S., Kang, G., Kanner, J. B., Kapadia, S. J., Kapasi, D. P., Karat, S., Karathanasis, C., Karki, S., Kashyap, R., Kasprzack, M., Kastaun, W., Kato, J., Kato, T., Katsanevas, S., Katsavounidis, E., Katzman, W., Kaur, T., Kaushik, R., Kawabe, K., Keitel, D., Kelley-Derzon, J., Kennington, J., Kesharwani, R., Key, J. S., Khadka, S., Khalili, F. Y., Khan, F., Khan, I., Khanam, T., Khazanov, E. A., Khursheed, M., Kiendrebeogo, W., Kijbunchoo, N., Kim, C., Kim, J. C., Kim, K., Kim, M. H., Kim, S., Kim, W. S., Kim, Y. -M., Kimball, C., Kimura, N., Kinley-Hanlon, M., Kinnear, M., Kissel, J. S., Kiyota, T., Klimenko, S., Klinger, T., Knee, A. M., Knust, N., Koch, P., Koehlenbeck, S. M., Koekoek, G., Kohri, K., Kokeyama, K., Koley, S., Kolitsidou, P., Kolstein, M., Komori, K., Kong, A. K. H., Kontos, A., Korobko, M., Kossak, R. V., Kou, X., Koushik, A., Kouvatsos, N., Kovalam, M., Koyama, N., Kozak, D. B., Kranzhoff, S. L., Kringel, V., Krishnendu, N. V., Królak, A., Kuehn, G., Kuijer, P., Kulkarni, S., Ramamohan, A. Kulur, Kumar, A., Kumar, Praveen, Kumar, Prayush, Kumar, Rahul, Kumar, Rakesh, Kume, J., Kuns, K., Kuroyanagi, S., Kuwahara, S., Kwak, K., Kwan, K., Lacaille, G., Lagabbe, P., Laghi, D., Lai, S., Laity, A. H., Lakkis, M. H., Lalande, E., Lalleman, M., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., La Rana, A., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Lawrence, J., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., LeBohec, S., Lecoeuche, Y. K., Lee, H. M., Lee, H. W., Lee, K., Lee, R. -K., Lee, R., Lee, S., Lee, Y., Legred, I. N., Lehmann, J., Lehner, L., Lemaître, A., Lenti, M., Leonardi, M., Leonova, E., Lequime, M., Leroy, N., Lesovsky, M., Letendre, N., Lethuillier, M., Levesque, C., Levin, Y., Leyde, K., Li, A. K. Y., Li, K. L., Li, T. G. F., Li, X., Lin, Chien-Yu, Lin, Chun-Yu, Lin, E. T., Lin, F., Lin, H., Lin, L. C. -C., Linde, F., Linker, S. D., Littenberg, T. B., Liu, A., Liu, G. C., Liu, Jian, Llamas, F., Llobera-Querol, J., Lo, R. K. L., Locquet, J. -P., London, L., Longo, A., Lopez, D., Portilla, M. Lopez, Lorenzini, M., Loriette, V., Lormand, M., Losurdo, G., Lott IV, T. P., Lough, J. D., Loughlin, H. A., Lousto, C. O., Lowry, M. J., Lück, H., Lumaca, D., Lundgren, A. P., Lussier, A. W., Ma, L. -T., Ma, S., Ma'arif, M., Macas, R., MacInnis, M., Maciy, R. R., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Macri, D., Maeda, K., Maenaut, S., Hernandez, I. Magaña, Magare, S. S., Magazzù, C., Magee, R. M., Maggio, E., Maggiore, R., Magnozzi, M., Mahesh, M., Mahesh, S., Maini, M., Majhi, S., Majorana, E., Makarem, C. N., Malaquias-Reis, J. A., Maliakal, S., Malik, A., Man, N., Mandic, V., Mangano, V., Mannix, B., Mansell, G. L., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Pina, D. Marín, Marion, F., Márka, S., Márka, Z., Markakis, C., Markosyan, A. S., Markowitz, A., Maros, E., Marquina, A., Marsat, S., Martelli, F., Martin, I. W., Martin, R. M., Martinez, B. B., Martinez, M., Martinez, V., Martini, A., Martinovic, K., Martins, J. C., Martynov, D. V., Marx, E. J., Massaro, L., Masserot, A., Masso-Reid, M., Mastrodicasa, M., Mastrogiovanni, S., Mateu-Lucena, M., Matiushechkina, M., Matsuyama, M., Mavalvala, N., Maxwell, N., McCarrol, G., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McGhee, G. I., McGowan, K. B. M., Mchedlidze, M., McIsaac, C., McIver, J., McKinney, K., McLeod, A., McRae, T., McWilliams, S. T., Meacher, D., Mehta, A. K., Meijer, Q., Melatos, A., Mellaerts, S., Menendez-Vazquez, A., Menoni, C. S., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Mérou, J. R., Merritt, J. D., Merzougui, M., Messenger, C., Messick, C., Meyer-Conde, M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Miller, A. L., Miller, S., Millhouse, M., Milotti, E., Minenkov, Y., Mio, N., Mir, Ll. M., Mirasola, L., Miravet-Tenés, M., Miritescu, C. -A., Mishra, A. K., Mishra, A., Mishra, C., Mishra, T., Mitchell, A. L., Mitchell, J. G., Mitra, S., Mitrofanov, V. P., Mitselmakher, G., Mittleman, R., Miyakawa, O., Miyamoto, S., Miyoki, S., Mo, G., Mobilia, L., Modafferi, L. M., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondal, C., Mondin, M., Montani, M., Moore, C. J., Morales, M., Moraru, D., Morawski, F., More, A., More, S., Moreno, C., Moreno, G., Morisaki, S., Moriwaki, Y., Morras, G., Moscatello, A., Mourier, P., Mours, B., Mow-Lowry, C. M., Mozzon, S., Muciaccia, F., Mukherjee, D., Mukherjee, Samanwaya, Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Mungioli, C. L., Munn, M., Oberg, W. R. Munn, Murakoshi, M., Murray, P. G., Muusse, S., Nadji, S. L., Nagar, A., Nagarajan, N., Nagler, K. N., Nakamura, K., Nakano, H., Nakano, M., Nandi, D., Napolano, V., Narayan, P., Nardecchia, I., Narola, H., Naticchioni, L., Nayak, R. K., Neil, B. F., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Neunzert, A., Ng, S., Nguyen, C., Nguyen, P., Quynh, L. Nguyen, Nichols, S. A., Nielsen, A. B., Nieradka, G., Niko, A., Nishino, Y., Nishizawa, A., Nissanke, S., Nitoglia, E., Niu, W., Nocera, F., Norman, M., North, C., Novak, J., Siles, J. F. Nuño, Nurbek, G., Nuttall, L. K., Obayashi, K., Oberling, J., O'Dell, J., Oertel, M., Offermans, A., Oganesyan, G., Oh, J. J., Oh, K., Oh, S. H., O'Hanlon, T., Ohashi, M., Ohkawa, M., Ohme, F., Ohta, H., Oliveira, A. S., Oliveri, R., Oloworaran, V., O'Neal, B., Oohara, K., O'Reilly, B., Ormsby, N. D., Orselli, M., O'Shaughnessy, R., Oshima, Y., Oshino, S., Ossokine, S., Osthelder, C., Ottaway, D. J., Ouzriat, A., Overmier, H., Owen, B. J., Pace, A. E., Pagano, R., Page, M. A., Pai, A., Pai, S. A., Pal, A., Pal, S., Palaia, M. A., Palashov, O., Pálfi, M., Palma, P. P., Palomba, C., Pan, K. C., Panda, P. K., Panebianco, L., Pang, P. T. H., Pannarale, F., Pant, B. C., Panther, F. H., Panzer, C. D., Paoletti, F., Paoli, A., Paolone, A., Papalexakis, E. E., Papalini, L., Papigkiotis, G., Parisi, A., Park, J., Parker, W., Pascale, G., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passuello, D., Patane, O., Patel, M., Pathak, D., Pathak, M., Patra, A., Patricelli, B., Patron, A. S., Paul, S., Payne, E., Pearce, T., Pedraza, M., Pegna, R., Pele, A., Arellano, F. E. Peña, Penn, S., Penuliar, M. D., Perego, A., Pereira, A., Perez, J. J., Périgois, C., Perkins, C. C., Perna, G., Perreca, A., Perret, J., Perriès, S., Perry, J. W., Pesios, D., Petrillo, C., Pfeiffer, H. P., Pham, H., Pham, K. A., Phukon, K. S., Phurailatpam, H., Piccinni, O. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierini, L., Pierra, G., Pierro, V., Pietrzak, M., Pillas, M., Pilo, F., Pinard, L., Pineda-Bosque, C., Pinto, I. M., Pinto, M., Piotrzkowski, B. J., Pirello, M., Pitkin, M. D., Placidi, A., Placidi, E., Planas, M. L., Plastino, W., Poggiani, R., Polini, E., Pompili, L., Poon, J., Porcelli, E., Portell, J., Porter, E. K., Posnansky, C., Poulton, R., Powell, J., Pracchia, M., Pradhan, B. K., Pradier, T., Prajapati, A. K., Prasai, K., Prasanna, R., Prasia, P., Pratten, G., Principe, M., Prodi, G. A., Prokhorov, L., Prosposito, P., Prudenzi, L., Puecher, A., Pullin, J., Punturo, M., Puosi, F., Puppo, P., Pürrer, M., Qi, H., Qin, J., Quéméner, G., Quetschke, V., Quigley, C., Quinonez, P. J., Quitzow-James, R., Raab, F. J., Raaijmakers, G., Radulesco, N., Raffai, P., Rail, S. X., Raja, S., Rajan, C., Rajbhandari, B., Ramirez, D. S., Ramirez, K. E., Vidal, F. A. Ramis, Ramos-Buades, A., Rana, D., Randel, E., Ranjan, S., Rapagnani, P., Ratto, B., Rawat, S., Ray, A., Raymond, V., Razzano, M., Read, J., Payo, M. Recaman, Regimbau, T., Rei, L., Reid, S., Reid, S. W., Reitze, D. H., Relton, P., Renzini, A., Rettegno, P., Revenu, B., Reza, A., Rezac, M., Rezaei, A. S., Ricci, F., Ricci, M., Richards, D., Richardson, C. J., Richardson, J. W., Rijal, A., Riles, K., Riley, H. K., Rinaldi, S., Rittmeyer, J., Robertson, C., Robinet, F., Robinson, M., Rocchi, A., Rolland, L., Rollins, J. G., Romanelli, M., Romano, A. E., Romano, R., Romero, A., Romero-Shaw, I. M., Romie, J. H., Ronchini, S., Roocke, T. J., Rosa, L., Rosauer, T. J., Rose, C. A., Rosińska, D., Ross, M. P., Rossello, M., Rowan, S., Roy, S. K., Roy, S., Rozza, D., Ruggi, P., Morales, E. Ruiz, Ruiz-Rocha, K., Sachdev, S., Sadecki, T., Sadiq, J., Saffarieh, P., Sah, M. R., Saha, S. S., Sainrat, T., Menon, S. Sajith, Sakai, K., Sakellariadou, M., Sako, T., Sakon, S., Salafia, O. S., Salces-Carcoba, F., Salconi, L., Saleem, M., Salemi, F., Sallé, M., Salvador, S., Sanchez, A., Sanchez, E. J., Sanchez, J. H., Sanchez, L. E., Sanchis-Gual, N., Sanders, J. R., Sänger, E. M., Saravanan, T. R., Sarin, N., Sasli, A., Sassi, P., Sassolas, B., Satari, H., Sato, R., Sato, S., Sato, Y., Sauter, O., Savage, R. L., Sawada, T., Sawant, H. L., Sayah, S., Schaetzl, D., Scheel, M., Scheuer, J., Schiworski, M. G., Schmidt, P., Schmidt, S., Schnabel, R., Schneewind, M., Schofield, R. M. S., Schouteden, K., Schuler, H., Schulte, B. W., Schutz, B. F., Schwartz, E., Scott, J., Scott, S. M., Seetharamu, T. C., Seglar-Arroyo, M., Sekiguchi, Y., Sellers, D., Sengupta, A. S., Sentenac, D., Seo, E. G., Seo, J. W., Sequino, V., Sergeev, A., Serra, M., Servignat, G., Setyawati, Y., Shaffer, T., Shah, U. S., Shahriar, M. S., Shaikh, M. A., Shams, B., Shao, L., Sharma, A. K., Sharma, P., Sharma-Chaudhary, S., Shawhan, P., Shcheblanov, N. S., Shen, B., Shikano, Y., Shikauchi, M., Shimode, K., Shinkai, H., Shiota, J., Shoemaker, D. H., Shoemaker, D. M., Short, R. W., ShyamSundar, S., Sider, A., Siegel, H., Sieniawska, M., Sigg, D., Silenzi, L., Simmonds, M., Singer, L. P., Singh, A., Singh, D., Singh, M. K., Singha, A., Sintes, A. M., Sipala, V., Skliris, V., Slagmolen, B. J. J., Slaven-Blair, T. J., Smetana, J., Smith, J. R., Smith, L., Smith, R. J. E., Smith, W. J., Soldateschi, J., Somala, S. N., Somiya, K., Soni, K., Soni, S., Sordini, V., Sorrentino, F., Sorrentino, N., Soulard, R., Souradeep, T., Southgate, A., Sowell, E., Spagnuolo, V., Spencer, A. P., Spera, M., Spinicelli, P., Srivastava, A. K., Stachurski, F., Steer, D. A., Steinlechner, J., Steinlechner, S., Stergioulas, N., Stevens, P., StPierre, M., Strang, L. C., Stratta, G., Strong, M. D., Strunk, A., Sturani, R., Stuver, A. L., Suchenek, M., Sudhagar, S., Sueltmann, N., Sullivan, A. G., Sullivan, K. D., Sun, L., Sunil, S., Sur, A., Suresh, J., Sutton, P. J., Suzuki, Takamasa, Suzuki, Takanori, Swinkels, B. L., Syx, A., Szczepańczyk, M. J., Szewczyk, P., Tacca, M., Tagoshi, H., Tait, S. C., Takahashi, H., Takahashi, R., Takamori, A., Takatani, K., Takeda, H., Takeda, M., Talbot, C. J., Talbot, C., Tamaki, M., Tamanini, N., Tanabe, D., Tanaka, K., Tanaka, S. J., Tanaka, T., Tanasijczuk, A. J., Tang, D., Tanioka, S., Tanner, D. B., Tao, L., Tapia, R. D., Martín, E. N. Tapia San, Tarafder, R., Taranto, C., Taruya, A., Tasson, J. D., Teloi, M., Tenorio, R., Themann, H., Theodoropoulos, A., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tissino, J., Tiwari, A., Tiwari, Shubhanshu, Tiwari, Srishti, Tiwari, V., Todd, M. R., Toivonen, A. M., Toland, K., Tolley, A. E., Tomaru, T., Tomita, K., Tomura, T., Tong-Yu, C., Toriyama, A., Toropov, N., Torres-Forné, A., Torrie, C. I., Toscani, M., Melo, I. Tosta e, Tournefier, E., Trani, A. A., Trapananti, A., Travasso, F., Traylor, G., Trenado, J., Trevor, M., Tringali, M. C., Tripathee, A., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. J., Tsang, T. T. L., Tso, R., Tsuchida, S., Tsukada, L., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Ubach, H., Ubhi, A. S., Uchiyama, T., Udall, R. P., Uehara, T., Ueno, K., Unnikrishnan, C. S., Ushiba, T., Utina, A., Vacatello, M., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valencia, J., Valentini, M., Vallejo-Peña, S. A., Vallero, S., Valsan, V., van Bakel, N., van Beuzekom, M., van Dael, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Sluys, M., Van de Walle, A., van Dongen, J., Vandra, K., van Haevermaet, H., van Heijningen, J. V., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venikoudis, S., Venneberg, J., Verdier, P., Verkindt, D., Verma, B., Verma, P., Verma, Y., Vermeulen, S. M., Veske, D., Vetrano, F., Veutro, A., Vibhute, A. M., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Vilkha, A., Villa-Ortega, V., Vincent, E. T., Vinet, J. -Y., Viret, S., Virtuoso, A., Vitale, S., Vocca, H., Voigt, D., von Reis, E. R. G., von Wrangel, J. S. A., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Walet, R. C., Walker, M., Wallace, G. S., Wallace, L., Wang, H., Wang, J. Z., Wang, W. H., Wang, Z., Waratkar, G., Ward, R. L., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watarai, D., Wayt, K. E., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Weller, C. M., Weller, R. A., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., White, D. D., Whiting, B. F., Whittle, C., Wildberger, J. B., Wilk, O. S., Wilken, D., Willetts, K., Williams, D., Williams, M. J., Williams, N. S., Willis, J. L., Willke, B., Wils, M., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wolfe, N. E., Wong, D., Wong, H. T., Wong, H. W. Y., Wong, I. C. F., Wright, J. L., Wright, M., Wu, C., Wu, D. S., Wu, H., Wysocki, D. M., Xiao, L., Xu, V. A., Xu, Y., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, M., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yan, T., Yang, F. W., Yang, F., Yang, K. Z., Yang, L. -C., Yang, Y., Yarbrough, Z., Yeh, S. -W., Yelikar, A. B., Yeung, S. M. C., Yin, X., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuzurihara, H., Zadrożny, A., Zannelli, A. J., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zeoli, M., Zerrad, M., Zevin, M., Zhang, A. C., Zhang, J., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhong, S., Zhou, R., Zhu, Z. -H., Zucker, M. E., Zweizig, J., Fujimori, T., Fujimoto, H., Fujita, T., Manita, Y., Obata, I., and Takidera, H.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Phenomenology
Abstract

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for $U(1)_{B-L}$ gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the $U(1)_{B-L}$ gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM., Comment: 20 pages, 5 figures

Published
2024

158. Improving Performance Prediction of Electrolyte Formulations with Transformer-based Molecular Representation Model

Author

Priyadarsini, Indra, Sharma, Vidushi, Takeda, Seiji, Kishimoto, Akihiro, Hamada, Lisa, and Shinohara, Hajime

Subjects
Computer Science - Machine Learning, Computer Science - Emerging Technologies
Abstract

Development of efficient and high-performing electrolytes is crucial for advancing energy storage technologies, particularly in batteries. Predicting the performance of battery electrolytes rely on complex interactions between the individual constituents. Consequently, a strategy that adeptly captures these relationships and forms a robust representation of the formulation is essential for integrating with machine learning models to predict properties accurately. In this paper, we introduce a novel approach leveraging a transformer-based molecular representation model to effectively and efficiently capture the representation of electrolyte formulations. The performance of the proposed approach is evaluated on two battery property prediction tasks and the results show superior performance compared to the state-of-the-art methods., Comment: Accepted in ML4LMS Workshop at ICML 2024

Published
2024

160. Isotropy of cosmic rays beyond $10^{20}$ eV favors their heavy mass composition

Author

Telescope Array Collaboration, Abbasi, R. U., Abe, Y., Abu-Zayyad, T., Allen, M., Arai, Y., Arimura, R., Barcikowski, E., Belz, J. W., Bergman, D. R., Blake, S. A., Buckland, I., Cheon, B. G., Chikawa, M., Fujii, T., Fujisue, K., Fujita, K., Fujiwara, R., Fukushima, M., Furlich, G., Globus, N., Gonzalez, R., Hanlon, W., Hayashida, N., He, H., Hibi, R., Hibino, K., Higuchi, R., Honda, K., Ikeda, D., Inoue, N., Ishii, T., Ito, H., Ivanov, D., Iwasaki, A., Jeong, H. M., Jeong, S., Jui, C. C. H., Kadota, K., Kakimoto, F., Kalashev, O., Kasahara, K., Kasami, S., Kawakami, S., Kawata, K., Kharuk, I., Kido, E., Kim, H. B., Kim, J. H., Kim, S. W., Kimura, Y., Komae, I., Kuzmin, V., Kuznetsov, M., Kwon, Y. J., Lee, K. H., Lubsandorzhiev, B., Lundquist, J. P., Matsumiya, H., Matsuyama, T., Matthews, J. N., Mayta, R., Mizuno, K., Murakami, M., Myers, I., Nagataki, S., Nakai, K., Nakamura, T., Nishio, E., Nonaka, T., Oda, H., Ogio, S., Onishi, M., Ohoka, H., Okazaki, N., Oku, Y., Okuda, T., Omura, Y., Ono, M., Oshima, A., Oshima, H., Ozawa, S., Park, I. H., Park, K. Y., Potts, M., Pshirkov, M. S., Remington, J., Rodriguez, D. C., Rott, C., Rubtsov, G. I., Ryu, D., Sagawa, H., Saito, R., Sakaki, N., Sako, T., Sakurai, N., Sato, D., Sato, K., Sato, S., Sekino, K., Shah, P. D., Shibata, N., Shibata, T., Shikita, J., Shimodaira, H., Shin, B. K., Shin, H. S., Shinto, D., Smith, J. D., Sokolsky, P., Stokes, B. T., Stroman, T. A., Takagi, Y., Takahashi, K., Takamura, M., Takeda, M., Takeishi, R., Taketa, A., Takita, M., Tameda, Y., Tanaka, K., Tanaka, M., Tanoue, Y., Thomas, S. B., Thomson, G. B., Tinyakov, P., Tkachev, I., Tokuno, H., Tomida, T., Troitsky, S., Tsuda, R., Tsunesada, Y., Udo, S., Urban, F., Warren, D., Wong, T., Yamazaki, K., Yashiro, K., Yoshida, F., Zhezher, Y., and Zundel, Z.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

We report an estimation of the injected mass composition of ultra-high energy cosmic rays (UHECRs) at energies higher than 10 EeV. The composition is inferred from an energy-dependent sky distribution of UHECR events observed by the Telescope Array surface detector by comparing it to the Large Scale Structure of the local Universe. In the case of negligible extra-galactic magnetic fields the results are consistent with a relatively heavy injected composition at E ~ 10 EeV that becomes lighter up to E ~ 100 EeV, while the composition at E > 100 EeV is very heavy. The latter is true even in the presence of highest experimentally allowed extra-galactic magnetic fields, while the composition at lower energies can be light if a strong EGMF is present. The effect of the uncertainty in the galactic magnetic field on these results is subdominant., Comment: 8 pages, 3 figures, accepted for publication in PRL

Published
2024

161. Mass composition of ultra-high energy cosmic rays from distribution of their arrival directions with the Telescope Array

Author

Telescope Array Collaboration, Abbasi, R. U., Abe, Y., Abu-Zayyad, T., Allen, M., Arai, Y., Arimura, R., Barcikowski, E., Belz, J. W., Bergman, D. R., Blake, S. A., Buckland, I., Cheon, B. G., Chikawa, M., Fujii, T., Fujisue, K., Fujita, K., Fujiwara, R., Fukushima, M., Furlich, G., Globus, N., Gonzalez, R., Hanlon, W., Hayashida, N., He, H., Hibi, R., Hibino, K., Higuchi, R., Honda, K., Ikeda, D., Inoue, N., Ishii, T., Ito, H., Ivanov, D., Iwasaki, A., Jeong, H. M., Jeong, S., Jui, C. C. H., Kadota, K., Kakimoto, F., Kalashev, O., Kasahara, K., Kasami, S., Kawakami, S., Kawata, K., Kharuk, I., Kido, E., Kim, H. B., Kim, J. H., Kim, S. W., Kimura, Y., Komae, I., Kuzmin, V., Kuznetsov, M., Kwon, Y. J., Lee, K. H., Lubsandorzhiev, B., Lundquist, J. P., Matsumiya, H., Matsuyama, T., Matthews, J. N., Mayta, R., Mizuno, K., Murakami, M., Myers, I., Nagataki, S., Nakai, K., Nakamura, T., Nishio, E., Nonaka, T., Oda, H., Ogio, S., Onishi, M., Ohoka, H., Okazaki, N., Oku, Y., Okuda, T., Omura, Y., Ono, M., Oshima, A., Oshima, H., Ozawa, S., Park, I. H., Park, K. Y., Potts, M., Pshirkov, M. S., Remington, J., Rodriguez, D. C., Rott, C., Rubtsov, G. I., Ryu, D., Sagawa, H., Saito, R., Sakaki, N., Sako, T., Sakurai, N., Sato, D., Sato, K., Sato, S., Sekino, K., Shah, P. D., Shibata, N., Shibata, T., Shikita, J., Shimodaira, H., Shin, B. K., Shin, H. S., Shinto, D., Smith, J. D., Sokolsky, P., Stokes, B. T., Stroman, T. A., Takagi, Y., Takahashi, K., Takamura, M., Takeda, M., Takeishi, R., Taketa, A., Takita, M., Tameda, Y., Tanaka, K., Tanaka, M., Tanoue, Y., Thomas, S. B., Thomson, G. B., Tinyakov, P., Tkachev, I., Tokuno, H., Tomida, T., Troitsky, S., Tsuda, R., Tsunesada, Y., Udo, S., Urban, F., Warren, D., Wong, T., Yamazaki, K., Yashiro, K., Yoshida, F., Zhezher, Y., and Zundel, Z.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

We use a new method to estimate the injected mass composition of ultrahigh cosmic rays (UHECRs) at energies higher than 10 EeV. The method is based on comparison of the energy-dependent distribution of cosmic ray arrival directions as measured by the Telescope Array experiment (TA) with that calculated in a given putative model of UHECR under the assumption that sources trace the large-scale structure (LSS) of the Universe. As we report in the companion letter, the TA data show large deflections with respect to the LSS which can be explained, assuming small extra-galactic magnetic fields (EGMF), by an intermediate composition changing to a heavy one (iron) in the highest energy bin. Here we show that these results are robust to uncertainties in UHECR injection spectra, the energy scale of the experiment and galactic magnetic fields (GMF). The assumption of weak EGMF, however, strongly affects this interpretation at all but the highest energies E > 100 EeV, where the remarkable isotropy of the data implies a heavy injected composition even in the case of strong EGMF. This result also holds if UHECR sources are as rare as $2 \times 10^{-5}$ Mpc$^{-3}$, that is the conservative lower limit for the source number density., Comment: 18 pages, 11 figures, accepted for publication in PRD

Published
2024

163. Measurement of Solar Differential Rotation by Absolutely Calibrated Iodine-Cell Spectroscopy

Author

Takeda, Yoichi

Subjects
Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Earth and Planetary Astrophysics
Abstract

The iodine-cell technique, which is known to be efficient in precisely establishing Doppler velocity shifts, was once applied by the author to measuring the solar differential rotation based on full-disk spectroscopic observations (Takeda and Ueno, Sol. Phys. 270, 447, 2011). However, the data reduction procedure (in simple analogy with the stellar case) adopted therein was not necessarily adequate, because specific characteristic involved with the disk-resolved Sun (i.e., center-limb variation of line strengths) was not properly taken into consideration. Therefore, this problem is revisited based on the same data but with an application to theoretical spectrum fitting, which can yield absolute heliocentric radial velocities (v_obs) in a consistent manner as shown in the study of solar gravitational redshift (Takeda and Ueno, Sol. Phys. 281, 551, 2012). Likewise, instead of converting v_obs into omega (angular velocity) at each disk point, which suffers considerable errors especially near the central meridian, omega was derived this time by applying the least squares analysis to a dataset comprising v_obs values at many points. This new analysis resulted in omega (deg/day) = 13.92 (+/- 0.03) -1.69(+/- 0.34)(sin psi)^2 -2.37(+/- 0.62) (sin psi)^4 (psi: the heliographic latitude) along with the gravitational redshift of 675 m/s, which are favorably compared with previous publications. In addition, how the distribution of observing points on the disk affects the result is also examined, which reveals that rotation parameters may suffer appreciable errors depending on cases., Comment: 18 pages, 8 figures, with ancillary material; accepted for publication in Solar Physics

Published
2024

165. A four-operator splitting algorithm for nonconvex and nonsmooth optimization

Author

Alcantara, Jan Harold, Lee, Ching-pei, and Takeda, Akiko

Subjects
Mathematics - Optimization and Control, 90C26, 90C30
Abstract

In this work, we address a class of nonconvex nonsmooth optimization problems where the objective function is the sum of two smooth functions (one of which is proximable) and two nonsmooth functions (one proper, closed and proximable, and the other continuous and weakly concave). We introduce a new splitting algorithm that extends the Davis-Yin splitting (DYS) algorithm to handle such four-term nonconvex nonsmooth problems. We prove that with appropriately chosen step sizes, our algorithm exhibits global subsequential convergence to stationary points with a stationarity measure converging at a rate of $1/k$. When specialized to the setting of the DYS algorithm, our results allow for larger stepsizes compared to existing bounds in the literature. Experimental results demonstrate the practical applicability and effectiveness of our proposed algorithm., Comment: 26 pages, 3 figures

Published
2024

166. Explosion by Killing and Maximum Principle in Symmetric Markov Processes

Author

Takeda, Masayoshi

Subjects
Mathematics - Probability
Abstract

Keller and Lenz \cite{KL} define a concept of {\it stochastic completeness at infinity} (SCI) for a regular symmetric Dirichlet form $(\cE,\cF)$. We show that (SCI) can be characterized probabilistically by using the predictable part $\zeta^p$ of the life time $\zeta$ of the symmetric Markov process $X=({\bf P}_x,X_t)$ generated by $(\cE,\cF)$, that is, (SCI) is equivalent to $\bfP_x(\zeta=\zeta^p<\infty)=0$. We define a concept, {\it explosion by killing} (EK), by $\bfP_x(\zeta=\zeta^i<\infty)=1$. Here $\zeta^i$ is the totally inaccessible part of $\zeta$. We see that (EK) is equivalent to (SCI) and $\bfP_x(\zeta=\infty)=1$. Let $X^{\rm res}$ be the {\it resurrected process} generated by the {\it resurrected form}, a regular Dirichlet form constructed by removing the killing part from $(\cE, \cF)$. Extending work of Masamune and Schmidt (\cite{MS}), we show that (EK) is also equivalent to the ordinary conservation property of time changed process of $X^{\rm res}$ by $A^k_t$, where the $A^k_t$ is the positive continuous additive functional in the Revuz correspondence to the killing measure $k$ in the Beurling-Deny formula (Theorem \ref{ma-sh}). We consider the maximum principle for Schr\"odinger-type operator $\cL^\mu=\cL-\mu$. Here $\cL$ is the self-adjoint operator associated with $(\cE,\cF)$ %with non-local part and $\mu$ is a Green-tight Kato measure. Let $\lambda(\mu)$ be the principal eigenvalue of the trace of $(\cE,\cF)$ relative to $\mu$. We prove that if (EK) holds, then $\lambda(\mu)>1$ implies a Liouville property that every bounded solution to $\cL^\mu u=0$ is zero quasi-everywhere and that the {\it refined maximum principle} in the sense of Berestycki-Nirenberg-Varadhan \cite{BNV} holds for $\cL^\mu$ if and only if $\lambda(\mu)>1$ (Theorem \ref{RMP}).

Published
2024

169. Fast Convergence to Second-Order Stationary Point through Random Subspace Optimization

Author

Higuchi, Rei, Poirion, Pierre-Louis, and Takeda, Akiko

Subjects
Mathematics - Optimization and Control, 90C06, 90C26, 90C30
Abstract

We propose the Random Subspace Homogenized Trust Region (RSHTR) method, which efficiently solves high-dimensional non-convex optimization problems by identifying descent directions within randomly selected subspaces. RSHTR provides the strongest theoretical guarantees among random subspace algorithms for non-convex optimization, achieving an $\varepsilon$-approximate first-order stationary point in $O(\varepsilon^{-3/2})$ iterations and converging locally at a linear rate. Furthermore, under rank-deficient conditions, RSHTR satisfies $\varepsilon$-approximate second-order necessary condition in $O(\varepsilon^{-3/2})$ iterations and exhibits a local quadratic convergence., Comment: 39 pages, 1 figure

Published
2024

170. Sparse Sub-gaussian Random Projections for Semidefinite Programming Relaxations

Author

Guedes-Ayala, Monse, Poirion, Pierre-Louis, Schewe, Lars, and Takeda, Akiko

Subjects
Mathematics - Optimization and Control
Abstract

Random projection, a dimensionality reduction technique, has been found useful in recent years for reducing the size of optimization problems. In this paper, we explore the use of sparse sub-gaussian random projections to approximate semidefinite programming (SDP) problems by reducing the size of matrix variables, thereby solving the original problem with much less computational effort. We provide some theoretical bounds on the quality of the projection in terms of feasibility and optimality that explicitly depend on the sparsity parameter of the projector. We investigate the performance of the approach for semidefinite relaxations appearing in polynomial optimization, with a focus on combinatorial optimization problems. In particular, we apply our method to the semidefinite relaxations of MAXCUT and MAX-2-SAT. We show that for large unweighted graphs, we can obtain a good bound by solving a projection of the semidefinite relaxation of MAXCUT. We also explore how to apply our method to find the stability number of four classes of imperfect graphs by solving a projection of the second level of the Lasserre Hierarchy. Overall, our computational experiments show that semidefinite programming problems appearing as relaxations of combinatorial optimization problems can be approximately solved using random projections as long as the number of constraints is not too large.

Published
2024

171. XENONnT WIMP Search: Signal & Background Modeling and Statistical Inference

Author

XENON Collaboration, Aprile, E., Aalbers, J., Abe, K., Maouloud, S. Ahmed, Althueser, L., Andrieu, B., Angelino, E., Martin, D. Antón, Arneodo, F., Baudis, L., Bazyk, M., Bellagamba, L., Biondi, R., Bismark, A., Boese, K., Brown, A., Bruno, G., Budnik, R., Cardoso, J. M. R., Chávez, A. P. Cimental, Colijn, A. P., Conrad, J., Cuenca-García, J. J., D'Andrea, V., Garcia, L. C. Daniel, Decowski, M. P., Di Donato, C., Di Gangi, P., Diglio, S., Eitel, K., Elykov, A., Ferella, A. D., Ferrari, C., Fischer, H., Flehmke, T., Flierman, M., Fulgione, W., Fuselli, C., Gaemers, P., Gaior, R., Galloway, M., Gao, F., Ghosh, S., Giacomobono, R., Glade-Beucke, R., Grandi, L., Grigat, J., Guan, H., Guida, M., Gyoergy, P., Hammann, R., Higuera, A., Hils, C., Hoetzsch, L., Hood, N. F., Iacovacci, M., Itow, Y., Jakob, J., Joerg, F., Kaminaga, Y., Kara, M., Kavrigin, P., Kazama, S., Kobayashi, M., Kopec, A., Kuger, F., Landsman, H., Lang, R. F., Levinson, L., Li, I., Li, S., Liang, S., Lin, Y. -T., Lindemann, S., Lindner, M., Liu, K., Loizeau, J., Lombardi, F., Long, J., Lopes, J. A. M., Luce, T., Ma, Y., Macolino, C., Mahlstedt, J., Mancuso, A., Manenti, L., Marignetti, F., Undagoitia, T. Marrodán, Martens, K., Masbou, J., Masson, E., Mastroianni, S., Melchiorre, A., Messina, M., Michael, A., Miuchi, K., Molinario, A., Moriyama, S., Morå, K., Mosbacher, Y., Murra, M., Müller, J., Ni, K., Oberlack, U., Paetsch, B., Pan, Y., Pellegrini, Q., Peres, R., Peters, C., Pienaar, J., Pierre, M., Plante, G., Pollmann, T. R., Principe, L., Qi, J., Qin, J., García, D. Ramírez, Rajado, M., Singh, R., Sanchez, L., Santos, J. M. F. dos, Sarnoff, I., Sartorelli, G., Schreiner, J., Schulte, D., Schulte, P., Eißing, H. Schulze, Schumann, M., Lavina, L. Scotto, Selvi, M., Semeria, F., Shagin, P., Shi, S., Shi, J., Silva, M., Simgen, H., Takeda, A., Tan, P. -L., Terliuk, A., Thers, D., Toschi, F., Trinchero, G., Tunnell, C. D., Tönnies, F., Valerius, K., Vecchi, S., Vetter, S., Solar, F. I. Villazon, Volta, G., Weinheimer, C., Weiss, M., Wenz, D., Wittweg, C., Wu, V. H. S., Xing, Y., Xu, D., Xu, Z., Yamashita, M., Yang, L., Ye, J., Yuan, L., Zavattini, G., and Zhong, M.

Subjects
Physics - Data Analysis, Statistics and Probability, Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract

The XENONnT experiment searches for weakly-interacting massive particle (WIMP) dark matter scattering off a xenon nucleus. In particular, XENONnT uses a dual-phase time projection chamber with a 5.9-tonne liquid xenon target, detecting both scintillation and ionization signals to reconstruct the energy, position, and type of recoil. A blind search for nuclear recoil WIMPs with an exposure of 1.1 tonne-years yielded no signal excess over background expectations, from which competitive exclusion limits were derived on WIMP-nucleon elastic scatter cross sections, for WIMP masses ranging from 6 GeV/$c^2$ up to the TeV/$c^2$ scale. This work details the modeling and statistical methods employed in this search. By means of calibration data, we model the detector response, which is then used to derive background and signal models. The construction and validation of these models is discussed, alongside additional purely data-driven backgrounds. We also describe the statistical inference framework, including the definition of the likelihood function and the construction of confidence intervals., Comment: 20 pages, 10 figures

Published
2024

175. Bloch sphere representation for Rabi oscillation driven by Rashba field in the two-dimensional harmonic confinement

Author

Arai, Kaichi, Tojo, Tatsuki, and Takeda, Kyozaburo

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science, Computer Science - Computational Engineering, Finance, and Science, Physics - Computational Physics, Quantum Physics
Abstract

We studied the dynamical properties of Rabi oscillations driven by an alternating Rashba field applied to a two-dimensional (2D) harmonic confinement system. We solve the time-dependent (TD) Schr\"{o}dinger equation numerically and rewrite the resulting TD wavefunction onto the Bloch sphere (BS) using two BS parameters of the zenith ($\theta_B$) and azimuthal ($\phi_B$) angles, extracting the phase information $\phi_B$ as well as the mixing ratio $\theta_B$ between the two BS-pole states. We employed a two-state rotating wave (TSRW) approach and studied the fundamental features of $\theta_B$ and $\phi_B$ over time. The TSRW approach reveals a triangular wave formation in $\theta_B$. Moreover, at each apex of the triangular wave, the TD wavefunction passes through the BS pole, and the state is completely replaced by the opposite spin state. The TSRW approach also elucidates a linear change in $\phi_B$. The slope of $\phi_B$ vs. time is equal to the difference between the dynamical terms, leading to a confinement potential in the harmonic system. The TSRW approach further demonstrates a jump in the phase difference by $\pi$ when the wavefunction passes through the BS pole. The alternating Rashba field causes multiple successive Rabi transitions in the 2D harmonic system. We then introduce the effective BS (EBS) and transform these complicated transitions into an equivalent "single" Rabi one. Consequently, the EBS parameters $\theta_B^{\mathrm{eff}}$ and $\phi_B^{\mathrm{eff}}$ exhibit mixing and phase difference between two spin states $\alpha$ and $\beta$, leading to a deep understanding of the TD features of multi-Rabi oscillations. Furthermore, the combination of the BS representation with the TSRW approach successfully reveals the dynamical properties of the Rabi oscillation, even beyond the TSRW approximation., Comment: 31 pages, 10 figures

Published
2024

179. Observation of Declination Dependence in the Cosmic Ray Energy Spectrum

Author

The Telescope Array Collaboration, Abbasi, R. U., Abu-Zayyad, T., Allen, M., Belz, J. W., Bergman, D. R., Buckland, I., Campbell, W., Cheon, B. G., Endo, K., Fedynitch, A., Fujii, T., Fujisue, K., Fujita, K., Fukushima, M., Furlich, G., Gerber, Z., Globus, N., Hanlon, W., Hayashida, N., He, H., Hibino, K., Higuchi, R., Ikeda, D., Ishii, T., Ivanov, D., Jeong, S., Jui, C. C. H., Kadota, K., Kakimoto, F., Kalashev, O., Kasahara, K., Kawachi, Y., Kawata, K., Kharuk, I., Kido, E., Kim, H. B., Kim, J. H., Kim, S. W., Kobo, R., Komae, I., Komatsu, K., Komori, K., Koyama, C., Kudenko, M., Kuroiwa, M., Kusumori, Y., Kuznetsov, M., Kwon, Y. J., Lee, K. H., Lee, M. J., Lubsandorzhiev, B., Lundquist, J. P., Matsuzawa, A., Matthews, J. A., Matthews, J. N., Mizuno, K., Mori, M., Murakami, M., Nagataki, S., Nakahara, M., Nakamura, T., Nakayama, T., Nakayama, Y., Nonaka, T., Ogio, S., Ohoka, H., Okazaki, N., Onishi, M., Oshima, A., Oshima, H., Ozawa, S., Park, I. H., Park, K. Y., Potts, M., Przybylak, M., Pshirkov, M. S., Remington, J., Rott, C., Rubtsov, G. I., Ryu, D., Sagawa, H., Sakaki, N., Sakamoto, R., Sako, T., Sakurai, N., Sakurai, S., Sato, D., Sato, S., Sekino, K., Shibata, T., Shikita, J., Shimodaira, H., Shin, B. K., Shin, H. S., Shinozaki, K., Smith, J. D., Sokolsky, P., Stokes, B. T., Stroman, T. A., Takagi, Y., Takahashi, K., Takeda, M., Takeishi, R., Taketa, A., Takita, M., Tameda, Y., Tanaka, K., Tanaka, M., Thomas, S. B., Thomson, G. B., Tinyakov, P., Tkachev, I., Tomida, T., Troitsky, S., Tsunesada, Y., Udo, S., Urban, F., Vaiman, I. A., Vrábel, M., Warren, D., Yamazaki, K., Zhezher, Y., Zundel, Z., and Zvirzdin, J.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

We report on an observation of the difference between northern and southern skies of the ultrahigh energy cosmic ray energy spectrum with a significance of ${\sim}8\sigma$. We use measurements from the two largest experiments$\unicode{x2014}$the Telescope Array observing the northern hemisphere and the Pierre Auger Observatory viewing the southern hemisphere. Since the comparison of two measurements from different observatories introduces the issue of possible systematic differences between detectors and analyses, we validate the methodology of the comparison by examining the region of the sky where the apertures of the two observatories overlap. Although the spectra differ in this region, we find that there is only a $1.8\sigma$ difference between the spectrum measurements when anisotropic regions are removed and a fiducial cut in the aperture is applied., Comment: 8 pages, 6 figures

Published
2024

180. Primitive Heavy-ball Dynamics Achieves $O(\varepsilon^{-7/4})$ Convergence for Nonconvex Optimization

Author

Okamura, Kaito, Marumo, Naoki, and Takeda, Akiko

Subjects
Mathematics - Optimization and Control, 90C26 (Primary), 90C30 (Secondary), 65K05, 90C06
Abstract

First-order optimization methods for nonconvex functions with Lipschitz continuous gradients and Hessian have been studied intensively in both machine learning and optimization. State-of-the-art methods finding an $\varepsilon$-stationary point within $O(\varepsilon^{-{7/4}})$ or $\tilde{O}(\varepsilon^{-{7/4}})$ gradient evaluations are based on Nesterov's accelerated gradient descent (AGD) or Polyak's heavy-ball method. However, these algorithms employ additional mechanisms, such as restart schemes and negative curvature exploitation, which complicate the algorithms' behavior and make it challenging to apply them to more advanced settings (e.g., stochastic optimization). To realize a simpler algorithm, we investigate the heavy-ball differential equation, a continuous-time analogy of the AGD and heavy-ball methods; we prove that the dynamics attains an $\varepsilon$-stationary point within $O(\varepsilon^{-{7/4}})$ time. We also show that a vanilla heavy-ball algorithm, obtained by discretizing the dynamics, achieves the complexity of $O(\varepsilon^{-{7/4}})$ under an additional assumption., Comment: 31 pages and 1 figure

Published
2024

181. SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining

Author

Han, Andi, Li, Jiaxiang, Huang, Wei, Hong, Mingyi, Takeda, Akiko, Jawanpuria, Pratik, and Mishra, Bamdev

Subjects
Computer Science - Machine Learning
Abstract

Large language models (LLMs) have shown impressive capabilities across various tasks. However, training LLMs from scratch requires significant computational power and extensive memory capacity. Recent studies have explored low-rank structures on weights for efficient fine-tuning in terms of parameters and memory, either through low-rank adaptation or factorization. While effective for fine-tuning, low-rank structures are generally less suitable for pretraining because they restrict parameters to a low-dimensional subspace. In this work, we propose to parameterize the weights as a sum of low-rank and sparse matrices for pretraining, which we call SLTrain. The low-rank component is learned via matrix factorization, while for the sparse component, we employ a simple strategy of uniformly selecting the sparsity support at random and learning only the non-zero entries with the fixed support. While being simple, the random fixed-support sparse learning strategy significantly enhances pretraining when combined with low-rank learning. Our results show that SLTrain adds minimal extra parameters and memory costs compared to pretraining with low-rank parameterization, yet achieves substantially better performance, which is comparable to full-rank training. Remarkably, when combined with quantization and per-layer updates, SLTrain can reduce memory requirements by up to 73% when pretraining the LLaMA 7B model.

Published
2024

182. Subspace Quasi-Newton Method with Gradient Approximation

Author

Miyaishi, Taisei, Nozawa, Ryota, Poirion, Pierre-Louis, and Takeda, Akiko

Subjects
Mathematics - Optimization and Control
Abstract

In recent years, various subspace algorithms have been developed to handle large-scale optimization problems. Although existing subspace Newton methods require fewer iterations to converge in practice, the matrix operations and full gradient computation are bottlenecks when dealing with large-scale problems. %In this study, We propose a subspace quasi-Newton method that is restricted to a deterministic-subspace together with a gradient approximation based on random matrix theory. Our method does not require full gradients, let alone Hessian matrices. Yet, it achieves the same order of the worst-case iteration complexities in average for convex and nonconvex cases, compared to existing subspace methods. In numerical experiments, we confirm the superiority of our algorithm in terms of computation time.

Published
2024

183. Design of a High-Performance Tomographic Tactile Sensor by Manipulating the Detector Conductivity

Author

Yoshimoto, Shunsuke, Sakamoto, Koji, Takeda, Rina, and Yamamoto, Akio

Subjects
Computer Science - Human-Computer Interaction
Abstract

Recent advancements in soft robots, human-machine interfaces, and wearable electronics have led to an increased demand for high-performance soft tactile sensors. Tomographic tactile sensor based on resistive coupling is a novel contact pressure imaging method that allows the use of an arbitrary conductive material in a detector. However, the influence of material properties on the sensing performance remains unclear and the efficient and appropriate selection of materials is difficult. In this study, the relationship between the conductivity distribution of the material used as a detector and the sensing performance including sensitivity, force range, spatial resolution, and position accuracy is clarified to develop a high-performance tomographic tactile sensor. The performance maps reveal that a material with a conductivity of approximately 0.2 S/m can serve as an effective detector for touch interactions involving a force range of several Newtons. Additionally, incorporating gradient conductivity in the cross-section of the detector and multi-layer conductive porous media with anisotropic conductive bonding can help expand the design flexibility for enhanced performance. Based on these findings, various tomographic tactile sensors for soft grippers, tangible input interfaces, flexible touch displays, and wearable electronics are demonstrated by using a conductive porous media.

Published
2024
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188. The Myelin Disorders Biorepository Project (MDBP)

Author

National Institutes of Health (NIH), National Institute of Neurological Disorders and Stroke (NINDS), National Center for Advancing Translational Sciences (NCATS), Biogen, Eli Lilly and Company, Myrtelle Inc., Orchard Therapeutics Ltd., Passage Bio, Inc., Synaptix Biotherapeutics Ltd., Takeda, Boehringer Ingelheim, Ionis Pharmaceuticals, Inc., Sanofi Winthrop Industrie, Sana Biotechnology, Yaya Foundation for 4H Leukodystrophy, University of Pennsylvania, United MSD Foundation, Foundation to Fight H-ABC, Calliope Joy Foundation, Don't Forget Me Foundation, and Adeline Vanderver, MD, Program Director, Leukodystrophy Center

Published
2024

193. First joint oscillation analysis of Super-Kamiokande atmospheric and T2K accelerator neutrino data

Author

Super-Kamiokande, collaborations, T2K, Abe, S., Abe, K., Akhlaq, N., Akutsu, R., Alarakia-Charles, H., Ali, A., Hakim, Y. I. Alj, Monsalve, S. Alonso, Amanai, S., Andreopoulos, C., Anthony, L. H. V., Antonova, M., Aoki, S., Apte, K. A., Arai, T., Arihara, T., Arimoto, S., Asada, Y., Asaka, R., Ashida, Y., Atkin, E. T., Babu, N., Barbi, M., Barker, G. J., Barr, G., Barrow, D., Bates, P., Batkiewicz-Kwasniak, M., Beauchêne, A., Berardi, V., Berns, L., Bhadra, S., Bhuiyan, N., Bian, J., Blanchet, A., Blondel, A., Bodur, B., Bolognesi, S., Bordoni, S., Boyd, S. B., Bravar, A., Bronner, C., Bubak, A., Avanzini, M. Buizza, Burton, G. T., Caballero, J. A., Calabria, N. F., Cao, S., Carabadjac, D., Carter, A. J., Cartwright, S. L., Casado, M. P., Catanesi, M. G., Cervera, A., Chakrani, J., Chalumeau, A., Chen, S., Cherdack, D., Choi, K., Chong, P. S., Chvirova, A., Cicerchia, M., Coleman, J., Collazuol, G., Cook, L., Cormier, F., Cudd, A., Dalmazzone, C., Daret, T., Dasgupta, P., Davis, C., Davydov, Yu. I., De Roeck, A., De Rosa, G., Dealtry, T., Delogu, C. C., Densham, C., Dergacheva, A., Dharmapal, R., Di Lodovico, F., Lopez, G. Diaz, Dolan, S., Douqa, D., Doyle, T. A., Drapier, O., Duffy, K. E., Dumarchez, J., Dunne, P., Dygnarowicz, K., D'ago, D., Edwards, R., Eguchi, A., Elias, J., Emery-Schrenk, S., Erofeev, G., Ershova, A., Eurin, G., Fannon, J. E. P., Fedorova, D., Fedotov, S., Feltre, M., Feng, J., Feng, L., Ferlewicz, D., Fernandez, P., Finch, A. J., Aguirre, G. A. Fiorentini, Fiorillo, G., Fitton, M. D., Patiño, J. M. Franco, Friend, M., Fujii, Y., Fujisawa, C., Fujita, S., Fukuda, Y., Furui, Y., Gao, J., Gaur, R., Giampaolo, A., Giannessi, L., Giganti, C., Glagolev, V., Goldsack, A., Gonin, M., Rosa, J. González, Goodman, E. A. G., Gorin, A., Gorshanov, K., Gousy-Leblanc, V., Grassi, M., Griskevich, N. J., Guigue, M., Hadley, D., Haigh, J. T., Han, S., Harada, M., Harris, D. A., Hartz, M., Hasegawa, T., Hassani, S., Hastings, N. C., Hayato, Y., Heitkamp, I., Henaff, D., Hill, J., Hino, Y., Hiraide, K., Hogan, M., Holeczek, J., Holin, A., Holvey, T., Van, N. T. Hong, Honjo, T., Horiuchi, S., Hosokawa, K., Hu, Z., Hu, J., Iacob, F., Ichikawa, A. K., Ieki, K., Ikeda, M., Iovine, N., Ishida, T., Ishino, H., Ishitsuka, M., Ishizuka, T., Ito, H., Itow, Y., Izmaylov, A., Izumiyama, S., Jakkapu, M., Jamieson, B., Jang, M. C., Jang, J. S., Jenkins, S. J., Jesús-Valls, C., Ji, J. Y., Jia, M., Jiang, J., Jonsson, P., Joshi, S., Jung, C. K., Jung, S., Kabirnezhad, M., Kaboth, A. C., Kajita, T., Kakuno, H., Kameda, J., Kanemura, Y., Kaneshima, R., Karpova, S., Kasetti, S. P., Kashiwagi, Y., Kasturi, V. S., Kataoka, Y., Katori, T., Kawamura, Y., Kawaue, M., Kearns, E., Khabibullin, M., Khotjantsev, A., Kikawa, T., Kim, S. B., King, S., Kiseeva, V., Kisiel, J., Kneale, L., Kobayashi, H., Kobayashi, T., Kobayashi, M., Koch, L., Kodama, S., Kolupanova, M., Konaka, A., Kormos, L. L., Koshio, Y., Koto, T., Kowalik, K., Kudenko, Y., Kudo, Y., Kuribayashi, S., Kurjata, R., Kurochka, V., Kutter, T., Kuze, M., Kwon, E., La Commara, M., Labarga, L., Lachat, M., Lachner, K., Lagoda, J., Lakshmi, S. M., LamersJames, M., Langella, A., Laporte, J. -F., Last, D., Latham, N., Laveder, M., Lavitola, L., Lawe, M., Learned, J. G., Lee, Y., Lee, S. H., Silverio, D. Leon, Levorato, S., Lewis, S., Li, X., Li, W., Lin, C., Litchfield, R. P., Liu, S. L., Liu, Y. M., Long, K. R., Longhin, A., Moreno, A. Lopez, Lu, X., Ludovici, L., Lux, T., Machado, L. N., Maekawa, Y., Magaletti, L., Mahn, K., Mahtani, K. K., Malek, M., Mandal, M., Manly, S., Marino, A. D., Martens, K., Marti, Ll., Martin, D. G. R., Martin, J. F., Martin, D., Martini, M., Maruyama, T., Matsubara, T., Matsumoto, R., Mattiazzi, M., Matveev, V., Mauger, C., Mavrokoridis, K., Mazzucato, E., McCauley, N., McElwee, J. M., McFarland, K. S., McGrew, C., McKean, J., Mefodiev, A., Megias, G. D., Mehta, P., Mellet, L., Menjo, H., Metelko, C., Mezzetto, M., Migenda, J., Mijakowski, P., Miki, S., Miller, E., Minamino, A., Mine, S., Mineev, O., Mirabito, J., Miura, M., Bueno, L. Molina, Moon, D. H., Mori, M., Moriyama, S., Morrison, P., Muñoz, A., Mueller, Th. A., Munford, D., Munteanu, L., Nagai, Y., Nagai, K., Nakadaira, T., Nakagiri, K., Nakahata, M., Nakajima, Y., Nakamura, A., Nakamura, K., Nakamura, K. D., Nakamura, T., Nakanishi, F., Nakano, Y., Nakaya, T., Nakayama, S., Nakayoshi, K., Naseby, C. E. R., Ngoc, T. V., Nguyen, V. Q., Nguyen, D. T., Nicholson, M., Niewczas, K., Ninomiya, K., Nishijima, K., Nishimori, S., Nishimura, Y., Noguchi, Y., Nosek, T., Nova, F., Novella, P., Nugent, J. C., Odagawa, T., Okazaki, R., Okazawa, H., Okinaga, W., Okumura, K., Okusawa, T., Ommura, Y., Onda, N., Ospina, N., Osu, L., Oyama, Y., O'Flaherty, M., O'Keeffe, H. M., O'Sullivan, L., Périssé, L., Paganini, P., Palladino, V., Paolone, V., Pari, M., Park, R. G., Parlone, J., Pasternak, J., Payne, D., Penn, G. C., de Perio, P., Pershey, D., Pfaff, M., Pickering, L., Pintaudi, G., Pistillo, C., Pointon, B. W., Popov, B., Yrey, A. Portocarrero, Porwit, K., Posiadala-Zezula, M., Prabhu, Y. S., Prasad, H., Pronost, G., Prouse, N. W., Pupilli, F., Quilain, B., Quyen, P. T., Raaf, J. L., Radermacher, T., Radicioni, E., Radics, B., Ramirez, M. A., Ramsden, R. M., Ratoff, P. N., Reh, M., Riccio, C., Richards, B., Rogly, R., Rondio, E., Roth, S., Roy, N., Rubbia, A., Russo, L., Rychter, A., Saenz, W., Sakai, S., Sakashita, K., Samani, S., Santos, A. D., Sato, Y., Sato, K., Schefke, T., Schloesser, C. M., Scholberg, K., Scott, M., Seiya, Y., Sekiguchi, T., Sekiya, H., Seo, J. W., Sgalaberna, D., Shaikhiev, A., Shi, W., Shiba, H., Shibayama, R., Shigeta, N., Shima, S., Shimamura, R., Shimizu, K., Shinoki, M., Shiozawa, M., Shiraishi, Y., Shvartsman, A., Skrobova, N., Skwarczynski, K., Smy, M. B., Smyczek, D., Sobczyk, J. T., Sobel, H. W., Soler, F. J. P., Sonoda, Y., Speers, A. J., Spina, R., Stroke, Y., Suslov, I. A., Suvorov, S., Suzuki, S., Suzuki, A., Suzuki, S. Y., Suzuki, Y., Sánchez, F., Tada, T., Tada, M., Tairafune, S., Takagi, Y., Takeda, A., Takemoto, Y., Takeuchi, Y., Takhistov, V., Takifuji, K., Tanaka, H., Tanaka, H. K., Tanigawa, H., Taniuchi, N., Tano, T., Tarrant, A., Tashiro, T., Teklu, A., Terada, K., Tereshchenko, V. V., Thamm, N., Thiesse, M. D., Thompson, L. F., Toki, W., Tomiya, T., Touramanis, C., Tsui, K. M., Tsukamoto, T., Tzanov, M., Uchida, Y., Vagins, M. R., Vargas, D., Varghese, M., Vasseur, G., Villa, E., Vinning, W. G. S., Virginet, U., Vladisavljevic, T., Wachala, T., Wakabayashi, D., Wallace, H. T., Walsh, J. G., Walter, C. W., Wan, L., Wang, X., Wang, Y., Wark, D., Wascko, M. O., Watanabe, E., Weber, A., Wendell, R. A., Wester, T., Wilking, M. J., Wilkinson, C., Wilson, S. T., Wilson, J. R., Wood, K., Wret, C., Wu, Y., Xia, J., Xie, Z., Xu, B. D., Xu, Y. -H., Yamamoto, K., Yamamoto, T., Yamauchi, K., Yanagisawa, C., Yang, G., Yang, B. S., Yang, J. Y., Yankelevich, A., Yano, T., Yasutome, K., Yershov, N., Yevarouskaya, U., Yokoyama, M., Yoo, J., Yoshida, T., Yoshida, S., Yoshimoto, Y., Yoshimura, N., Yoshioka, Y., Yu, M., Yu, I., Zaki, R., Zaldivar, B., Zalewska, A., Zalipska, J., Zaremba, K., Zarnecki, G., Zhang, J., Zhang, A. Q., Zhang, B., Zhao, X. Y., Zhong, H., Zhu, T., Ziembicki, M., Zimmerman, E. D., Zito, M., and Zsoldos, S.

Subjects
High Energy Physics - Experiment
Abstract

The Super-Kamiokande and T2K collaborations present a joint measurement of neutrino oscillation parameters from their atmospheric and beam neutrino data. It uses a common interaction model for events overlapping in neutrino energy and correlated detector systematic uncertainties between the two datasets, which are found to be compatible. Using 3244.4 days of atmospheric data and a beam exposure of $19.7(16.3) \times 10^{20}$ protons on target in (anti)neutrino mode, the analysis finds a 1.9$\sigma$ exclusion of CP-conservation (defined as $J_{CP}=0$) and a preference for the normal mass ordering., Comment: 12 pages, 4 figures

Published
2024

195. A Relativistic Formula for the Multiple Scattering of Photons

Author

Takahashi, Rohta, Umemura, Masayuki, Ohsuga, Ken, Asahina, Yuta, Takeda, Rintaro, Takahashi, Mikiya M., Kawanaka, Norita, Konno, Kohkichi, and Nagasawa, Tomoaki

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Condensed Matter - Statistical Mechanics, General Relativity and Quantum Cosmology, High Energy Physics - Theory, Mathematical Physics
Abstract

We have discovered analytical expressions for the probability density function (PDF) of photons that are multiply scattered in relativistic flows, under the assumption of isotropic and inelastic scattering. These expressions characterize the collective dynamics of these photons, ranging from free-streaming to diffusion regions. The PDF, defined within the light cone to ensure the preservation of causality, is expressed in a three-dimensional space at a constant time surface. This expression is achieved by summing the PDFs of photons that have been scattered $n$ times within four-dimensional spacetime. We have confirmed that this formulation accurately reproduces the results of relativistic Monte Carlo simulations.We found that the PDF in three-dimensional space at a constant time surface can be represented in a separable variable form. We demonstrate the behavior of the PDF in the laboratory frame across a wide range of Lorentz factors for the relativistic flow. When the Lorentz factor of the fluid is low, the behavior of scattered photons evolves sequentially from free propagation to diffusion, and then to dynamic diffusion, where the mean effective velocity of the photons equates to that of the fluid. On the other hand, when the Lorentz factor is large, the behavior evolves from anisotropic ballistic motion, characterized by a mean effective velocity approaching the speed of light, to dynamic diffusion., Comment: The version accepted by ApJ Letters

Published
2024
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196. Evaluation of the X-ray SOI pixel detector with the on-chip ADC

Author

Matsuhashi, Hiroumi, Hagino, Kouichi, Bamba, Aya, Takeda, Ayaki, Yukumoto, Masataka, Mori, Koji, Nishioka, Yusuke, Tsuru, Takeshi Go, Uenomachi, Mizuki, Ikeda, Tomonori, Matsuda, Masamune, Narita, Takuto, Suzuki, Hiromasa, Tanaka, Takaaki, Kurachi, Ikuo, Kohmura, Takayoshi, Uchida, Yusuke, Arai, Yasuo, and Kawahito, Shoji

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

XRPIX is the monolithic X-ray SOI (silicon-on-insulator) pixel detector, which has a time resolution better than 10 $\rm{\mu}$s as well as a high detection efficiency for X-rays above 10 keV. XRPIX is planned to be installed on future X-ray satellites. To mount on satellites, it is essential that the ADC (analog-to-digital converter) be implemented on the detector because such peripheral circuits must be as compact as possible to achieve a large imaging area in the limited space in satellites. Thus, we developed a new XRPIX device with the on-chip ADC, and evaluated its performances. As the results, the integral non-linearity was evaluated to be 6 LSB (least significant bit), equivalent to 36 eV. The differential non-linearity was less than 0.7 LSB, and input noise from the on-chip ADC was 5~$\rm{e^{-}}$. Also, we evaluated end-to-end performance including the sensor part as well as the on-chip ADC. As the results, energy resolution at 5.9 keV was 294 $\rm{\pm}$ 4 eV in full-width at half maximum for the best pixel., Comment: 17 pages, 9 figures, NIMA, accepted

Published
2024

197. Zero-shot Degree of Ill-posedness Estimation for Active Small Object Change Detection

Author

Takeda, Koji, Tanaka, Kanji, Nakamura, Yoshimasa, and Kanezaki, Asako

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In everyday indoor navigation, robots often needto detect non-distinctive small-change objects (e.g., stationery,lost items, and junk, etc.) to maintain domain knowledge. Thisis most relevant to ground-view change detection (GVCD), a recently emerging research area in the field of computer vision.However, these existing techniques rely on high-quality class-specific object priors to regularize a change detector modelthat cannot be applied to semantically nondistinctive smallobjects. To address ill-posedness, in this study, we explorethe concept of degree-of-ill-posedness (DoI) from the newperspective of GVCD, aiming to improve both passive and activevision. This novel DoI problem is highly domain-dependent,and manually collecting fine-grained annotated training datais expensive. To regularize this problem, we apply the conceptof self-supervised learning to achieve efficient DoI estimationscheme and investigate its generalization to diverse datasets.Specifically, we tackle the challenging issue of obtaining self-supervision cues for semantically non-distinctive unseen smallobjects and show that novel "oversegmentation cues" from openvocabulary semantic segmentation can be effectively exploited.When applied to diverse real datasets, the proposed DoI modelcan boost state-of-the-art change detection models, and it showsstable and consistent improvements when evaluated on real-world datasets., Comment: 7 pages, 7 figures

Published
2024

198. Continuous-variable quantum kernel method on a programmable photonic quantum processor

Author

Anai, Keitaro, Ikehara, Shion, Yano, Yoshichika, Okuno, Daichi, and Takeda, Shuntaro

Subjects
Quantum Physics
Abstract

Among various quantum machine learning (QML) algorithms, the quantum kernel method has especially attracted attention due to its compatibility with noisy intermediate-scale quantum devices and its potential to achieve quantum advantage. This method performs classification and regression by nonlinearly mapping data into quantum states in a higher dimensional Hilbert space. Thus far, the quantum kernel method has been implemented only on qubit-based systems, but continuous-variable (CV) systems can potentially offer superior computational power by utilizing its infinite-dimensional Hilbert space. Here, we demonstrate the implementation of the classification task with the CV quantum kernel method on a programmable photonic quantum processor. We experimentally prove that the CV quantum kernel method successfully classifies several datasets robustly even under the experimental imperfections, with high accuracies comparable to the classical kernel. This demonstration sheds light on the utility of CV quantum systems for QML and should stimulate further study in other CV QML algorithms., Comment: 8 pages and 4 figures

Published
2024
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