Quality Assurance and Quality Control of the $26~\text{m}^2$ SiPM production for the DarkSide-20k dark matter experiment

Autor: Acerbi, F., Adhikari, P., Agnes, P., Ahmad, I., Albergo, S., Albuquerque, I. F., Alexander, T., Alton, A. K., Amaudruz, P., Aprile, M. Angiolilli. E., Corona, M. Atzori, Auty, D. J., Ave, M., Avetisov, I. C., Azzolini, O., Back, H. O., Balmforth, Z., Olmedo, A. Barrado, Barrillon, P., Batignani, G., Bhowmick, P., Bloem, M., Blua, S., Bocci, V., Bonivento, W., Bottino, B., Boulay, M. G., Buchowicz, A., Bussino, S., Busto, J., Cadeddu, M., Cadoni, M., Calabrese, R., Camillo, V., Caminata, A., Canci, N., Capra, A., Caravati, M., Cardenas-Montes, M., Cargioli, N., Carlini, M., Castello, P., Cavalcante, P., Cebrian, S., Ruiz, J. Cela, Chashin, S., Chepurnov, A., Cifarelli, L., Cintas, D., Cleveland, B., Coadou, Y., Cocco, V., Colaiuda, D., Vilda, E. Conde, Consiglio, L., Costa, B. S., Czubak, M., D'Auria, S., Rolo, M. D. Da Rocha, Darbo, G., Davini, S., de Asmundis, R., De Cecco, S., Dellacasa, G., Derbin, A. V., Di Capua, F., Di Noto, L., Di Stefano, P., Dias, L. K., Dionisi, C., Dolganov, G., Dordei, F., Dronik, V., Elersich, A., Ellingwood, E., Erjavec, T., Fearon, N., Diaz, M. Fernandez, Ficorella, A., Fiorillo, G., Franchini, P., Franco, D., Gatti, H. Frandini, Frolov, E., Gabriele, F., Gahan, D., Galbiati, C., Galiski, G., Gallina, G., Gallus, G., Garbini, M., Abia, P. Garcia, Gawdzik, A., Gendotti, A., Giovanetti, G. K., Casanueva, V. Goicoechea, Gola, A., Grandi, L., Grauso, G., di Cortona, G. Grilli, Grobov, A., Gromov, M., Gulino, M., Guo, C., Hackett, B. R., Hallin, A., Hamer, A., Haranczyk, M., Hessel, T., Horikawa, S., Hu, J., Hubaut, F., Hucker, J., Hugues, T., Hungerford, E. V., Ianni, A., Ippoliti, G., Ippolito, V., Jamil, A., Jillings, C., Keloth, R., Kemmerich, N., Kemp, A., Kester, Carlos E., Kimura, M., Kondo, K., Korga, G., Kotsiopoulou, L., Koulosousas, S., Kubankin, A., Kunze, P., Kuss, M., Kuźniak, M., Kuzwa, M., La Commara, M., Lai, M., LeGuirriec, E., Leason, E., Leoni, A., Lidey, L., Lissia, M., Luzzi, L., Lychagina, O., Macfadyen, O., Machulin, I. N., Manecki, S., Manthos, I., Marasciulli, A., Margutti, G., Mari, S. M., Mariani, C., Maricic, J., Martinez, M., Martoff, C. J., Matteucci, G., Mavrokoridis, K., Mazza, E., McDonald, A. B., Merzi, S., Messina, A., Milincic, R., Minutoli, S., Mitra, A., Monroe, J., Moretti, E., Morrocchi, M., Mroz, T., Muratova, V. N., Murphy, M., Murra, M., Muscas, C., Musico, P., Nania, R., Nessi, M., Nieradka, G., Nikolopoulos, K., Nikoloudaki, E., Nowak, J., Olchanski, K., Oleinik, A., Oleynikov, V., Organtini, P., de Solrzano, A. Ortiz, Pallavicini, M., Pandola, L., Pantic, E., Paoloni, E., Papi, D., Pastuszak, G., Paternoster, G., Pegoraro, P. A., Pelczar, K., Perez, R., Pesudo, V., Piacentini, S., Pino, N., Plante, G., Pocar, A., Poehlmann, M., Pordes, S., Pralavorio, P., Preosti, E., Price, D., Puglia, S., Bazetto, M. Queiroga, Ragusa, F., Ramachers, Y., Ramirez, A., Ravinthiran, S., Razeti, M., Renshaw, A. L., Rescigno, M., Resconi, S., Retiere, F., Rignanese, L. P., Rivetti, A., Roberts, A., Roberts, C., Rogers, G., Romero, L., Rossi, M., Rubbia, A., Rudik, D., Sabia, M., Salomone, P., Samoylov, O., Sanfilippo, S., Santone, D., Santorelli, R., Santos, E. Moura, Savarese, C., Scapparone, E., Schuckman II, F. G., Scioli, G., Semenov, D. A., Sheshukov, A., Simeone, M., Skensved, P., Skorokhvatov, M. D., Smirnov, O., Smirnova, T., Smith, B., Sotnikov, A., Spadoni, F., Spangenberg, M., Stefanizzi, R., Steri, A., Stornelli, V., Stracka, S., Sulis, S., Sung, A., Sunny, C., Suvorov, Y., Szelc, A. M., Taborda, O., Tartaglia, R., Taylor, A., Taylor, J., Testera, G., Thieme, K., Thompson, A., Torres-Lara, S., Tricomi, A., Unzhakov, E. V., Van Uffelen, M., Viant, T., Viel, S., Vishneva, A., Vogelaar, R. B., Vossebeld, J., Vyas, B., Wada, M., Walczak, M., Wang, Y., Wang, H., Westerdale, S., Williams, L., Wojaczyski, R., Wojcik, M. M., Wojcik, M., Wright, T., Xie, Y., Yang, C., Yin, J., Zabihi, A., Zakhary, P., Zani, A., Zhang, Y., Zhu, T., Zichichi, A., Zuzel, G., Zykova, M. P.

DarkSide-20k is a novel liquid argon dark matter detector currently under construction at the Laboratori Nazionali del Gran Sasso (LNGS) of the Istituto Nazionale di Fisica Nucleare (INFN) that will push the sensitivity for Weakly Interacting Massive

Externí odkaz: http://arxiv.org/abs/2412.18867

Multimodal Purcell enhancement and optical coherence of Eu$^{\text{3+}}$ ions in a single nanoparticle coupled to a microcavity

Autor: Eichhorn, Timon, Jobbitt, Nicholas, Bieling, Sören, Liu, Shuping, Krom, Tobias, Serrano, Diana, Huber, Robert, Lemmer, Ulrich, de Riedmatten, Hugues, Goldner, Philippe, Hunger, David

Europium-doped nanocrystals constitute a promising material for a scalable future quantum computing platform. Long-lived nuclear spin states could serve as qubits addressed via coherent optical transitions. In order to realize an efficient spin-photo

Externí odkaz: http://arxiv.org/abs/2412.06576

Shapes of direct cortical responses vs. short-range axono-cortical evoked potentials: The effects of direct electrical stimulation applied to the human brain

Autor: Turpin, Clotilde, Rossel, Olivier, Schlosser-Perrin, Félix, Ng, Sam, Matsumoto, Riki, Mandonnet, Emmanuel, Duffau, Hugues, Bonnetblanc, François

Objective: Direct cortical responses (DCR) and axono-cortical evoked potentials (ACEP) are generated by electrically stimulating the cortex either directly or indirectly through white matter pathways, potentially leading to different electrogenic pro

Externí odkaz: http://arxiv.org/abs/2411.16360

Modeling contact binaries, III. Properties of a population of close, massive binaries

Autor: Fabry, Matthias, Marchant, Pablo, Langer, Norbert, Sana, Hugues

Among massive stars, binary interaction is the rule rather than the exception. The closest binaries, those with periods of less than about 10 days, undergo mass transfer during core-hydrogen burning, with many of them experiencing a nuclear-timescale

Externí odkaz: http://arxiv.org/abs/2410.21394

DR-MPC: Deep Residual Model Predictive Control for Real-world Social Navigation

Autor: Han, James R., Thomas, Hugues, Zhang, Jian, Rhinehart, Nicholas, Barfoot, Timothy D.

How can a robot safely navigate around people exhibiting complex motion patterns? Reinforcement Learning (RL) or Deep RL (DRL) in simulation holds some promise, although much prior work relies on simulators that fail to precisely capture the nuances

Externí odkaz: http://arxiv.org/abs/2410.10646