First Searches for Dark Matter with the KM3NeT Neutrino Telescopes

Autor: KM3NeT Collaboration, Aiello, S., Albert, A., Alhebsi, A. R., Alshamsi, M., Garre, S. Alves, Ambrosone, A., Ameli, F., Andre, M., Aphecetche, L., Ardid, M., Ardid, S., Aublin, J., Badaracco, F., Bailly-Salins, L., Bardačová, Z., Baret, B., Bariego-Quintana, A., Becherini, Y., Bendahman, M., Benfenati, F., Benhassi, M., Bennani, M., Benoit, D. M., Berbee, E., Bertin, V., Biagi, S., Boettcher, M., Bonanno, D., Bouasla, A. B., Boumaaza, J., Bouta, M., Bouwhuis, M., Bozza, C., Bozza, R. M., Brânzăş, H., Bretaudeau, F., Breuhaus, M., Bruijn, R., Brunner, J., Bruno, R., Buis, E., Buompane, R., Busto, J., Caiffi, B., Calvo, D., Capone, A., Carenini, F., Carretero, V., Cartraud, T., Castaldi, P., Cecchini, V., Celli, S., Cerisy, L., Chabab, M., Chen, A., Cherubini, S., Chiarusi, T., Circella, M., Clark, R., Cocimano, R., Coelho, J. A. B., Coleiro, A., Condorelli, A., Coniglione, R., Coyle, P., Creusot, A., Cuttone, G., Dallier, R., De Benedittis, A., De Martino, B., De Wasseige, G., Decoene, V., Del Rosso, I., Di Mauro, L. S., Di Palma, I., Díaz, A. F., Diego-Tortosa, D., Distefano, C., Domi, A., Donzaud, C., Dornic, D., Drakopoulou, E., Drouhin, D., Ducoin, J. -G., Dvornický, R., Eberl, T., Eckerová, E., Eddymaoui, A., van Eeden, T., Eff, M., van Eijk, D., Bojaddaini, I. El, Hedri, S. El, Ellajosyula, V., Enzenhöfer, A., Ferrara, G., Filipović, M. D., Filippini, F., Franciotti, D., Fusco, L. A., Gagliardini, S., Gal, T., Méndez, J. García, Soto, A. Garcia, Oliver, C. Gatius, Geißelbrecht, N., Genton, E., Ghaddari, H., Gialanella, L., Gibson, B. K., Giorgio, E., Goos, I., Goswami, P., Gozzini, S. R., Gracia, R., Guidi, C., Guillon, B., Gutiérrez, M., Haack, C., van Haren, H., Heijboer, A., Hennig, L., Hernández-Rey, J. J., Ibnsalih, W. Idrissi, Illuminati, G., Joly, D., de Jong, M., de Jong, P., Jung, B. J., Kistauri, G., Kopper, C., Kouchner, A., Kovalev, Y. Y., Kueviakoe, V., Kulikovskiy, V., Kvatadze, R., Labalme, M., Lahmann, R., Lamoureux, M., Larosa, G., Lastoria, C., Lazar, J., Lazo, A., Stum, S. Le, Lehaut, G., Lemaître, V., Leonora, E., Lessing, N., Levi, G., Clark, M. Lindsey, Longhitano, F., Magnani, F., Majumdar, J., Malerba, L., Mamedov, F., Manfreda, A., Marconi, M., Margiotta, A., Marinelli, A., Markou, C., Martin, L., Mastrodicasa, M., Mastroianni, S., Mauro, J., Miele, G., Migliozzi, P., Migneco, E., Mitsou, M. L., Mollo, C. M., Morales-Gallegos, L., Moussa, A., Mateo, I. Mozun, Muller, R., Musone, M. R., Musumeci, M., Navas, S., Nayerhoda, A., Nicolau, C. A., Nkosi, B., Fearraigh, B. Ó, Oliviero, V., Orlando, A., Oukacha, E., Paesani, D., González, J. Palacios, Papalashvili, G., Parisi, V., Gómez, E. J. Pastor, Pastore, C., Păun, A. M., Păvălaş, G. E., Martínez, S. Peña, Perrin-Terrin, M., Pestel, V., Pestes, R., Piattelli, P., Plavin, A., Poiré, C., Popa, V., Pradier, T., Prado, J., Pulvirenti, S., Quiroz-Rangel, C. A., Randazzo, N., Razzaque, S., Rea, I. C., Real, D., Riccobene, G., Romanov, A., Ros, E., Šaina, A., Greus, F. Salesa, Samtleben, D. F. E., Losa, A. Sánchez, Sanfilippo, S., Sanguineti, M., Santonocito, D., Sapienza, P., Schnabel, J., Schumann, J., Schutte, H. M., Seneca, J., Sennan, N., Sevle, P., Sgura, I., Shanidze, R., Sharma, A., Shitov, Y., Šimkovic, F., Simonelli, A., Sinopoulou, A., Spisso, B., Spurio, M., Stavropoulos, D., Štekl, I., Taiuti, M., Takadze, G., Tayalati, Y., Thiersen, H., Thoudam, S., Melo, I. Tosta e, Trocmé, B., Tsourapis, V., Tudorache, A., Tzamariudaki, E., Ukleja, A., Vacheret, A., Valsecchi, V., Van Elewyck, V., Vannoye, G., Vasileiadis, G., de Sola, F. Vazquez, Veutro, A., Viola, S., Vivolo, D., van Vliet, A., de Wolf, E., Lhenry-Yvon, I., Zavatarelli, S., Zegarelli, A., Zito, D., Zornoza, J. D., Zúñiga, J., Zywucka, N.

Indirect dark matter detection methods are used to observe the products of dark matter annihilations or decays originating from astrophysical objects where large amounts of dark matter are thought to accumulate. With neutrino telescopes, an excess of

Externí odkaz: http://arxiv.org/abs/2411.10092

Code-mixed LLM: Improve Large Language Models' Capability to Handle Code-Mixing through Reinforcement Learning from AI Feedback

Autor: Zhang, Wenbo, Majumdar, Aditya, Yadav, Amulya

Code-mixing(CM) or code-switching(CSW) refers to the juxtaposition of linguistic units from two or more languages during the conversation or sometimes even a single utterance. Code-mixing introduces unique challenges in daily life, such as syntactic

Externí odkaz: http://arxiv.org/abs/2411.09073

Opportunities and Challenges of Solid-State Quantum Nonlinear Optics

Autor: Kala, Abhinav, Sharp, David, Choi, Minho, Manna, Arnab, Deshmukh, Prathmesh, Veetil, Vijin Kizhake, Menon, Vinod, Pelton, Matthew, Waks, Edo, Majumdar, Arka

Nonlinear interactions between single quantum particles are at the heart of any quantum information system, including analog quantum simulation and fault-tolerant quantum computing. This remains a particularly difficult problem for photonic qubits, a

Externí odkaz: http://arxiv.org/abs/2411.06630

Enhancement of an Unruh-DeWitt battery performance through quadratic environmental coupling

Autor: Mukherjee, Arnab, Gangopadhyay, Sunandan, Majumdar, A. S.

We investigate relativistic effects on the performance of a quantum battery in an open quantum framework. We consider an Unruh-DeWitt detector driven by a coherent classical pulse as a quantum battery that is interacting with a massless scalar field

Externí odkaz: http://arxiv.org/abs/2411.02849

The drag length is key to quantifying tree canopy drag

Autor: Majumdar, Dipanjan, Vita, Giulio, Ramponi, Rubina, Glover, Nina, van Reeuwijk, Maarten

The effects of trees on urban flows are often determined using computational fluid dynamics approaches which typically use a quadratic drag formulation based on the leaf-area density $a$ and a volumetric drag coefficient $C_{d}^V$ to model vegetation

Externí odkaz: http://arxiv.org/abs/2411.01570