Zobrazeno 1 - 10
of 23 401
pro vyhledávání: '"Cueto, A."'
Orthogonal arrays play a fundamental role in many applications. However, constructing orthogonal arrays with the required parameters for an application usually is extremely difficult and, sometimes, even impossible. Hence there is an increasing need
Externí odkaz:
http://arxiv.org/abs/2406.19516
Autor:
Majumder, Apratim, Meem, Monjurul, del Cueto, Fernando Gonzalez, Guevara-Vasquez, Fernando, Qadri, Syed N., Santiago, Freddie, Menon, Rajesh
We present a novel high-definition (HD) snapshot diffractive spectral imaging system utilizing a diffractive filter array (DFA) to capture a single image that encodes both spatial and spectral information. This single diffractogram can be computation
Externí odkaz:
http://arxiv.org/abs/2406.17302
Autor:
Gregory, Wilson G., Tonelli-Cueto, Josué, Marshall, Nicholas F., Lee, Andrew S., Villar, Soledad
This work characterizes equivariant polynomial functions from tuples of tensor inputs to tensor outputs. Loosely motivated by physics, we focus on equivariant functions with respect to the diagonal action of the orthogonal group on tensors. We show h
Externí odkaz:
http://arxiv.org/abs/2406.01552
Autor:
Andersen, J., Assi, B., Asteriadis, K., Azzurri, P., Barone, G., Behring, A., Benecke, A., Bhattacharya, S., Bothmann, E., Caletti, S., Chen, X., Chiesa, M., Cooper-Sarkar, A., Cridge, T., Gomez, A. Cueto, Datta, S., Dhani, P. K., Donega, M., Engel, T., Ravasio, S. Ferrario, Forte, S., Francavilla, P., Garzelli, M. V., Ghira, A., Ghosh, A., Giuli, F., Gouskos, L., Gras, P., Gütschow, C., Haddad, Y., Harland-Lang, L., Hekhorn, F., Helenius, I., Hinzmann, A., Höche, S., Holguin, J., Huss, A., Huston, J., Ježo, T., Jones, S., Kiebacher, S., Knobbe, M., Kogler, R., Köneke, K., Kunz, L., LeBlanc, M., Loch, P., Centeno, G. Loeschcke, Löschner, M., Maas, A., Magni, G., Maier, A., Marcoli, M., Marzani, S., McFayden, J., Meinzinger, P., Mikuni, V., Moch, S., Nadolsky, P., Napoletano, D., Pellen, M., Plätzer, S., Poncelet, R., Preuss, C., Qu, H., Rabbertz, K., Reichelt, D., Rescia, A., Roloff, J., Röntsch, R., Cruz, S. Sanchez, Sarkar, T., Scyboz, L., Sforza, F., Siódmok, A., Stagnitto, G., Tarek, A., Thorne, R. S., Valassi, A., Whitehead, J., Winter, J., Delaunay, C., Herrmann, B., Re, E.
This report presents a short summary of the activities of the "Standard Model" working group for the "Physics at TeV Colliders" workshop (Les Houches, France, 12-30 June, 2023).
Comment: Proceedings of the Standard Model Working Group of the 202
Comment: Proceedings of the Standard Model Working Group of the 202
Externí odkaz:
http://arxiv.org/abs/2406.00708
We prove that local stable/unstable sets of homeomorphisms of an infinite compact metric space satisfying the gluing-orbit property always contain compact and perfect subsets of the space. As a consequence, we prove that if a positively countably exp
Externí odkaz:
http://arxiv.org/abs/2405.17574
Thermodynamics-informed neural networks employ inductive biases for the enforcement of the first and second principles of thermodynamics. To construct these biases, a metriplectic evolution of the system is assumed. This provides excellent results, w
Externí odkaz:
http://arxiv.org/abs/2405.13093
This work revolves around the rigorous asymptotic analysis of models in nonlocal hyperelasticity. The corresponding variational problems involve integral functionals depending on nonlocal gradients with a finite interaction range $\delta$, called the
Externí odkaz:
http://arxiv.org/abs/2404.18509
The development of inductive biases has been shown to be a very effective way to increase the accuracy and robustness of neural networks, particularly when they are used to predict physical phenomena. These biases significantly increase the certainty
Externí odkaz:
http://arxiv.org/abs/2404.01060
We present a method to increase the resolution of measurements of a physical system and subsequently predict its time evolution using thermodynamics-aware neural networks. Our method uses adversarial autoencoders, which reduce the dimensionality of t
Externí odkaz:
http://arxiv.org/abs/2402.17506
Autor:
La Valle, Chris, Tonelli-Cueto, Josué
Separation bounds are a fundamental measure of the complexity of solving a zero-dimensional system as it measures how difficult it is to separate its zeroes. In the positive dimensional case, the notion of reach takes its place. In this paper, we pro
Externí odkaz:
http://arxiv.org/abs/2402.15649