Measurement of the double-differential cross section of muon-neutrino charged-current interactions with low hadronic energy in the NOvA Near Detector

Autor: Acero, M. A., Acharya, B., Adamson, P., Aliaga, L., Anfimov, N., Antoshkin, A., Arrieta-Diaz, E., Asquith, L., Aurisano, A., Back, A., Balashov, N., Baldi, P., Bambah, B. A., Bannister, E., Barros, A., Bashar, S., Bat, A., Bays, K., Bernstein, R., Bezerra, T. J. C., Bhatnagar, V., Bhattarai, D., Bhuyan, B., Bian, J., Booth, A. C., Bowles, R., Brahma, B., Bromberg, C., Buchanan, N., Butkevich, A., Calvez, S., Carroll, T. J., Catano-Mur, E., Cesar, J. P., Chatla, A., Chirco, R., Choudhary, B. C., Christensen, A., Cicala, M. F., Coan, T. E., Cooleybeck, A., Cortes-Parra, C., Coveyou, D., Cremonesi, L., Davies, G. S., Derwent, P. F., Ding, P., Djurcic, Z., Dobbs, K., Dolce, M., Doyle, D., Tonguino, D. Dueñas, Dukes, E. C., Dye, A., Ehrlich, R., Ewart, E., Filip, P., Frank, M. J., Gallagher, H. R., Gao, F., Giri, A., Gomes, R. A., Goodman, M. C., Groh, M., Group, R., Habig, A., Hakl, F., Hartnell, J., Hatcher, R., He, M., Heller, K., Hewes, V, Himmel, A., Horoho, T., Ivaneev, Y., Ivanova, A., Jargowsky, B., Jarosz, J., Johnson, C., Judah, M., Kakorin, I., Kaplan, D. M., Kalitkina, A., Kirezli-Ozdemir, B., Kleykamp, J., Klimov, O., Koerner, L. W., Kolupaeva, L., Kralik, R., Kumar, A., Kus, V., Lackey, T., Lang, K., Lesmeister, J., Lister, A., Liu, J., Lock, J. A., Lokajicek, M., MacMahon, M., Magill, S., Mann, W. A., Manoharan, M. T., Plata, M. Manrique, Marshak, M. L., Martinez-Casales, M., Matveev, V., Mehta, B., Messier, M. D., Meyer, H., Miao, T., Miller, W. H., Mishra, S., Mishra, S. R., Mislivec, A., Mohanta, R., Moren, A., Morozova, A., Mu, W., Mualem, L., Muether, M., Mulder, K., Myers, D., Naples, D., Nath, A., Nelleri, S., Nelson, J. K., Nichol, R., Niner, E., Norman, A., Norrick, A., Nosek, T., Oh, H., Olshevskiy, A., Olson, T., Ozkaynak, M., Pal, A., Paley, J., Panda, L., Patterson, R. B., Pawloski, G., Petti, R., Porter, J. C. C., Prais, L. R., Rabelhofer, M., Rafique, A., Raj, V., Rajaoalisoa, M., Ramson, B., Rebel, B., Roy, P., Samoylov, O., Sanchez, M. C., Falero, S. Sanchez, Shanahan, P., Sharma, P., Sheshukov, A., Shivam, Shmakov, A., Shorrock, W., Shukla, S., Singha, D. K., Singh, I., Singh, P., Singh, V., Smith, E., Smolik, J., Snopok, P., Solomey, N., Sousa, A., Soustruznik, K., Strait, M., Suter, L., Sutton, A., Sutton, K., Swain, S., Sweeney, C., Sztuc, A., Talukdar, N., Oregui, B. Tapia, Tas, P., Thakore, T., Thomas, J., Tiras, E., Titus, M., Torun, Y., Tran, D., Trokan-Tenorio, J., Urheim, J., Vahle, P., Vallari, Z., Villamil, J. D., Vockerodt, K. J., Wallbank, M., Weber, C., Wetstein, M., Whittington, D., Wickremasinghe, D. A., Wieber, T., Wolcott, J., Wrobel, M., Wu, S., Wu, W., Xiao, Y., Yaeggy, B., Yahaya, A., Yankelevich, A., Yonehara, K., Yu, Y., Zadorozhnyy, S., Zalesak, J., Zwaska, R.

The NOvA collaboration reports cross-section measurements for $\nu_{\mu}$ charged-current interactions with low hadronic energy (maximum kinetic energy of 250 MeV for protons and 175 MeV for pions) in the NOvA Near Detector. The results are presented

Externí odkaz: http://arxiv.org/abs/2410.10222

The Landscape of Unfolding with Machine Learning

Autor: Huetsch, Nathan, Villadamigo, Javier Mariño, Shmakov, Alexander, Diefenbacher, Sascha, Mikuni, Vinicius, Heimel, Theo, Fenton, Michael, Greif, Kevin, Nachman, Benjamin, Whiteson, Daniel, Butter, Anja, Plehn, Tilman

Recent innovations from machine learning allow for data unfolding, without binning and including correlations across many dimensions. We describe a set of known, upgraded, and new methods for ML-based unfolding. The performance of these approaches ar

Externí odkaz: http://arxiv.org/abs/2404.18807

Function Approximation for Reinforcement Learning Controller for Energy from Spread Waves

Autor: Sarkar, Soumyendu, Gundecha, Vineet, Ghorbanpour, Sahand, Shmakov, Alexander, Babu, Ashwin Ramesh, Naug, Avisek, Pichard, Alexandre, Cocho, Mathieu

Publikováno v: IJCAI 2023, Proceedings of the Thirty-Second International Joint Conference on Artificial IntelligenceAugust 2023, Article No 688, Pages 6201 to 6209

The industrial multi-generator Wave Energy Converters (WEC) must handle multiple simultaneous waves coming from different directions called spread waves. These complex devices in challenging circumstances need controllers with multiple objectives of

Externí odkaz: http://arxiv.org/abs/2404.10991

AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning

Autor: Tavakoli, Mohammadamin, Chiu, Yin Ting T., Shmakov, Alexander, Carlton, Ann Marie, Van Vranken, David, Baldi, Pierre

Deep learning-based reaction predictors have undergone significant architectural evolution. However, their reliance on reactions from the US Patent Office results in a lack of interpretable predictions and limited generalization capability to other c

Externí odkaz: http://arxiv.org/abs/2311.01118

Cohomological Arithmetic Statistics for Principally Polarized Abelian Varieties over Finite Fields

Autor: Shmakov, Aleksander

There is a natural probability measure on the set of isomorphism classes of principally polarized Abelian varieties of dimension $g$ over $\mathbb{F}_q$, weighted by the number of automorphisms. The distributions of the number of $\mathbb{F}_q$-ratio

Externí odkaz: http://arxiv.org/abs/2309.13806