Stellar stripping efficiencies of satellites in numerical simulations: the effect of resolution, satellite properties and numerical disruption

Autor: Martin, G., Pearce, F. R., Hatch, N. A., Contreras-Santos, A., Knebe, A., Cui, W.

The stellar stripping of satellites in cluster haloes is understood to play an important role in the production of intracluster light. Increasingly, cosmological simulations have been utilised to investigate its origin and assembly. However, such sim

Externí odkaz: http://arxiv.org/abs/2410.19292

Resource-Efficient Sensor Fusion via System-Wide Dynamic Gated Neural Networks

Autor: Singhal, Chetna, Wu, Yashuo, Malandrino, Francesco, Contreras, Sharon Ladron de Guevara, Levorato, Marco, Chiasserini, Carla Fabiana

Publikováno v: IEEE SECON 2024

Mobile systems will have to support multiple AI-based applications, each leveraging heterogeneous data sources through DNN architectures collaboratively executed within the network. To minimize the cost of the AI inference task subject to requirement

Externí odkaz: http://arxiv.org/abs/2410.16723

A new method of reconstructing images of gamma-ray telescopes applied to the LST-1 of CTAO

Autor: Project, CTA-LST, Abe, K., Abe, S., Abhishek, A., Acero, F., Aguasca-Cabot, A., Agudo, I., Alispach, C., Crespo, N. Alvarez, Ambrosino, D., Antonelli, L. A., Aramo, C., Arbet-Engels, A., Arcaro, C., Asano, K., Aubert, P., Baktash, A., Balbo, M., Bamba, A., Larriva, A. Baquero, de Almeida, U. Barres, Barrio, J. A., Jiménez, L. Barrios, Batkovic, I., Baxter, J., González, J. Becerra, Bernardini, E., Medrano, J. Bernete, Berti, A., Bezshyiko, I., Bhattacharjee, P., Bigongiari, C., Bissaldi, E., Blanch, O., Bonnoli, G., Bordas, P., Borkowski, G., Brunelli, G., Bulgarelli, A., Burelli, I., Burmistrov, L., Buscemi, M., Cardillo, M., Caroff, S., Carosi, A., Carrasco, M. S., Cassol, F., Castrejón, N., Cauz, D., Cerasole, D., Ceribella, G., Chai, Y., Cheng, K., Chiavassa, A., Chikawa, M., Chon, G., Chytka, L., Cicciari, G. M., Cifuentes, A., Contreras, J. L., Cortina, J., Costantini, H., Da Vela, P., Dalchenko, M., Dazzi, F., De Angelis, A., de Lavergne, M. de Bony, De Lotto, B., de Menezes, R., Del Burgo, R., Del Peral, L., Delgado, C., Mengual, J. Delgado, della Volpe, D., Dellaiera, M., Di Piano, A., Di Pierro, F., Di Tria, R., Di Venere, L., Díaz, C., Dominik, R. M., Prester, D. Dominis, Donini, A., Dorner, D., Doro, M., Eisenberger, L., Elsässer, D., Emery, G., Escudero, J., Ramazani, V. Fallah, Ferrarotto, F., Fiasson, A., Foffano, L., Coromina, L. Freixas, Fröse, S., Fukazawa, Y., López, R. Garcia, Gasbarra, C., Gasparrini, D., Geyer, D., Paiva, J. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Godinovic, N., Grau, R., Green, D., Green, J., Gunji, S., Günther, P., Hackfeld, J., Hadasch, D., Hahn, A., Hassan, T., Hayashi, K., Heckmann, L., Heller, M., Llorente, J. Herrera, Hirotani, K., Hoffmann, D., Horns, D., Houles, J., Hrabovsky, M., Hrupec, D., Hui, D., Iarlori, M., Imazawa, R., Inada, T., Inome, Y., Inoue, S., Ioka, K., Iori, M., Iuliano, A., Martinez, I. Jimenez, Quiles, J. Jimenez, Jurysek, J., Kagaya, M., Kalashev, O., Karas, V., Katagiri, H., Kataoka, J., Kerszberg, D., Kobayashi, Y., Kohri, K., Kong, A., Kubo, H., Kushida, J., Lainez, M., Lamanna, G., Lamastra, A., Lemoigne, L., Linhoff, M., Longo, F., López-Coto, R., López-Oramas, A., Loporchio, S., Lorini, A., Bahilo, J. Lozano, Luciani, H., Luque-Escamilla, P. L., Majumdar, P., Makariev, M., Mallamaci, M., Mandat, D., Manganaro, M., Manicò, G., Mannheim, K., Marchesi, S., Mariotti, M., Marquez, P., Marsella, G., Martí, J., Martinez, O., Martínez, G., Martínez, M., Mas-Aguilar, A., Maurin, G., Mazin, D., Méndez-Gallego, J., Guillen, E. Mestre, Micanovic, S., Miceli, D., Miener, T., Miranda, J. M., Mirzoyan, R., Mizuno, T., Gonzalez, M. Molero, Molina, E., Montaruli, T., Moralejo, A., Morcuende, D., Morselli, A., Moya, V., Muraishi, H., Nagataki, S., Nakamori, T., Neronov, A., Nickel, L., Rosillo, M. Nievas, Nikolic, L., Nishijima, K., Noda, K., Nosek, D., Novotny, V., Nozaki, S., Ohishi, M., Ohtani, Y., Oka, T., Okumura, A., Orito, R., Otero-Santos, J., Ottanelli, P., Owen, E., Palatiello, M., Paneque, D., Pantaleo, F. R., Paoletti, R., Paredes, J. M., Pech, M., Pecimotika, M., Peresano, M., Pfeifle, F., Pietropaolo, E., Pihet, M., Pirola, G., Plard, C., Podobnik, F., Pons, E., Prandini, E., Priyadarshi, C., Prouza, M., Rainò, S., Rando, R., Rhode, W., Ribó, M., Righi, C., Rizi, V., Fernandez, G. Rodriguez, Frías, M. D. Rodríguez, Ruina, A., Ruiz-Velasco, E., Saito, T., Sakurai, S., Sanchez, D. A., Sano, H., Šarić, T., Sato, Y., Saturni, F. G., Savchenko, V., Schiavone, F., Schleicher, B., Schmuckermaier, F., Schubert, J. L., Schussler, F., Schweizer, T., Arroyo, M. Seglar, Siegert, T., Sitarek, J., Sliusar, V., Strišković, J., Strzys, M., Suda, Y., Tajima, H., Takahashi, H., Takahashi, M., Takata, J., Takeishi, R., Tam, P. H. T., Tanaka, S. J., Tateishi, D., Tavernier, T., Temnikov, P., Terada, Y., Terauchi, K., Terzic, T., Teshima, M., Tluczykont, M., Tokanai, F., Torres, D. F., Travnicek, P., Tutone, A., Vacula, M., Vallania, P., van Scherpenberg, J., Acosta, M. Vázquez, Ventura, S., Verna, G., Viale, I., Vigliano, A., Vigorito, C. F., Visentin, E., Vitale, V., Voitsekhovskyi, V., Voutsinas, G., Vovk, I., Vuillaume, T., Walter, R., Wan, L., Will, M., Wójtowicz, J., Yamamoto, T., Yamazaki, R., Yeung, P. K. H., Yoshida, T., Yoshikoshi, T., Zhang, W., Zywucka, N.

Imaging atmospheric Cherenkov telescopes (IACTs) are used to observe very high-energy photons from the ground. Gamma rays are indirectly detected through the Cherenkov light emitted by the air showers they induce. The new generation of experiments, i

Externí odkaz: http://arxiv.org/abs/2410.16042

Machine Learning approach to reconstruct Density Matrices from Quantum Marginals

Autor: Uzcategui-Contreras, Daniel, Guerra, Antonio, Niklitschek, Sebastian, Delgado, Aldo

In this work, we propose a machine learning approach to address one aspect of the quantum marginal problem: finding a global density matrix compatible with a given set of quantum marginals. Our method involves combining a quantum marginal imposition

Externí odkaz: http://arxiv.org/abs/2410.11145

Minimization and Hyperbolicity

Autor: Contreras, Gonzalo, Offin, Daniel

In this paper we study the relationship between the strict locally minimizing orbits for time dependent lagrangian systems and hyperbolicity properties of the corresponding lagrangian flow.

Externí odkaz: http://arxiv.org/abs/2410.08426