Zobrazeno 1 - 10
of 9 060
pro vyhledávání: '"JAN, T."'
Autor:
Schneider, Jan T., Ueda, Atsushi, Liu, Yifan, Läuchli, Andreas M., Oshikawa, Masaki, Tagliacozzo, Luca
We set up an effective field theory formulation for the renormalization flow of matrix product states (MPS) with finite bond dimension, focusing on systems exhibiting finite-entanglement scaling close to a conformally invariant critical fixed point.
Externí odkaz:
http://arxiv.org/abs/2411.03954
Autor:
Bou-Comas, Aleix, Marimón, Carlos Ramos, Schneider, Jan T., Carignano, Stefano, Tagliacozzo, Luca
We introduce a novel experimental approach to probe many-body quantum systems by developing a protocol to measure generalized temporal entropies. We demonstrate that the recently proposed generalized temporal entropies [Phys. Rev. Research 6, 033021]
Externí odkaz:
http://arxiv.org/abs/2409.05517
Autor:
Graczyk, Krzysztof M., Kowal, Beata E., Ankowski, Artur M., Banerjee, Rwik Dharmapal, Bonilla, Jose Luis, Prasad, Hemant, Sobczyk, Jan T.
Transfer learning (TL) allows a deep neural network (DNN) trained on one type of data to be adapted for new problems with limited information. We propose to use the TL technique in physics. The DNN learns the physics of one process, and after fine-tu
Externí odkaz:
http://arxiv.org/abs/2408.09936
Autor:
Kowal, Beata E., Graczyk, Krzysztof M., Ankowski, Artur M., Banerjee, Rwik Dharmapal, Prasad, Hemant, Sobczyk, Jan T.
Employing the neural network framework, we obtain empirical fits to the electron-scattering cross sections for carbon over a broad kinematic region, extending from the quasielastic peak through resonance excitation to the onset of deep-inelastic scat
Externí odkaz:
http://arxiv.org/abs/2312.17298
Autor:
Banerjee, Rwik Dharmapal, Ankowski, Artur M., Graczyk, Krzysztof M., Kowal, Beata E., Prasad, Hemant, Sobczyk, Jan T.
Publikováno v:
Phys. Rev. D 109, 073004 (2024)
The Short-Baseline Neutrino program in Fermilab aims to resolve the nature of the low-energy excess events observed in LSND and MiniBooNE, and analyze with unprecedented precision neutrino interactions with argon. These studies require reliable estim
Externí odkaz:
http://arxiv.org/abs/2312.13369
As particle accelerators increase their collision rates, and deep learning solutions prove their viability, there is a growing need for lightweight and fast neural network architectures for low-latency tasks such as triggering. We examine the potenti
Externí odkaz:
http://arxiv.org/abs/2310.16121
Publikováno v:
Case Reports in Nephrology and Dialysis, Vol 14, Iss 1, Pp 171-177 (2024)
Introduction: The Seraph® 100 Microbind® Affinity Filter is a biomimetic adsorbent device that can remove pathogens from the blood. Case Presentation: Here, we report the successful use of the Seraph® 100 to treat both a SARS-CoV-2 reinfection lea
Externí odkaz:
https://doaj.org/article/b144b43b78d2415496a0488b92db5d4d
Autor:
Hu, Qingzhi, Daza, Daniel, Swinkels, Laurens, Ūsaitė, Kristina, Hoen, Robbert-Jan 't, Groth, Paul
The Sustainable Development Goals (SDGs) were introduced by the United Nations in order to encourage policies and activities that help guarantee human prosperity and sustainability. SDG frameworks produced in the finance industry are designed to prov
Externí odkaz:
http://arxiv.org/abs/2308.02622
Publikováno v:
J. High Energ. Phys. 2024, 113 (2024)
PELICAN is a novel permutation equivariant and Lorentz invariant or covariant aggregator network designed to overcome common limitations found in architectures applied to particle physics problems. Compared to many approaches that use non-specialized
Externí odkaz:
http://arxiv.org/abs/2307.16506