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Showing 51644 results for "deep learning" in Physics
Physics Preprint PDF DOI

Effective Noise Mitigation via Quantum Circuit Learning in Quantum Simulation of Integrable Spin Chains

Wenlong Zhao, Yimeng Zhang, Yan Guo, Yufan Cui, Zhuohang Wang, Rui-Dong Zhu · 2026

We propose a noise-mitigation quantum simulation strategy for near-term quantum devices based on Quantum Circuit Learning (QCL), which is in particular effective for integrable quantum spin chains. Th…

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Physics Preprint PDF DOI

An Extended Evaluation Split for DeepSpaceYoloDataset

Olivier Parisot · 2026

Recent technological advances in astronomy, particularly the growing popularity of smart telescopes for the general public, make it possible to develop highly effective detection solutions that are ac…

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Physics Preprint PDF DOI

Ultrafast Sliding Ferroelectric Switching in Bilayer Hexagonal Boron Nitride Revealed by Deep Learning Molecular Dynamics

Yinan Wang, Poyen Chen, Teruyasu Mizoguchi · 2026

Sliding ferroelectricity in bilayer hexagonal boron nitride (h-BN) offers compelling prospects for next-generation non-volatile memory, yet the atomistic dynamics of electric-field-driven polarization…

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Physics Preprint PDF DOI

DeepPropNet: an operator learning-based predictor for thermal plasma properties

Zuo Wang, Linlin Zhong · 2026

Thermal plasma properties play a critical role in plasma simulations and plasma-related applications. However, their strong nonlinear dependence on temperature, pressure, and gas composition makes acc…

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Physics Preprint PDF DOI

Training of particle-turbulence sub-grid-scale closures with just particle data

G. Saltar Rivera, L. Villafane, J. B. Freund · 2026

If sufficient training data are available, neural networks are attractive for representing missing physics in simulations, such as sub-grid scales in the coarse-mesh particle-turbulence system we cons…

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Physics Preprint PDF DOI

Structure-Aware Transformers for Learning Near-Optimal Trotter Orderings with System-Size Generalization in 1D Heisenberg Hamiltonians

Shamminuj Aktar, Reuben Tate, Stephan Eidenbenz · 2026

Trotterization is a standard approach for simulating quantum time evolution on quantum computers, where the Hamiltonian is split into local terms and each term is applied in sequence. The order of the…

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Physics Preprint PDF DOI

The major cluster merger in Abell 2034 as seen by XRISM: Strong turbulence and spectral anomalies?

Annie Heinrich, Irina Zhuravleva, Eugene Churazov, Congyao Zhang, Daniele Rogantini, Hannah McCall, Reinout J. van Weeren, William R. Forman · 2026

XRISM observations to date have shown that gas kinetic pressures in the intracluster medium (ICM) tend towards the low end of predictions from cosmological simulations. Here, we present a XRISM observ…

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Physics Preprint PDF DOI

Nonlocal nonstabilizerness in free fermion models

Mario Collura, Benjamin Beri, Emanuele Tirrito · 2026

Nonlocal magic quantifies the irreducible nonstabilizerness of a bipartite quantum state after optimizing over local basis changes. We study nonlocal magic for pure fermionic Gaussian states, and deri…

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Physics Preprint PDF DOI

Momentum-Space Entanglement Signatures and Spinon Breakdown in the $J_1$-$J_2$ Zig-Zag Heisenberg Chain

Tom Oeffner, Ludwig Bordfeldt, Andreas Feuerpfeil, Lukas Elter, Tobias Helbig, Tobias Hofmann, Martin Greiter, Ronny Thomale · 2026

We investigate the resilience of spinon quasiparticles in the $J_1$-$J_2$ zig-zag spin chain ($J_2>0$) from the viewpoint of momentum-space entanglement. For small $J_2$, we show that deconfined spino…

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Physics Preprint PDF DOI

Outer-Crust Equations of State for Neutron Stars

P.S. Koliogiannis, N. Paar · 2026

We construct and systematically assess four outer-crust equations of state based on relativistic nuclear mass models and a machine-learning mass table. Our aim is to quantify the sensitivity of the eq…

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Physics Preprint PDF DOI

Fluctuations of path-dependent thermodynamic quantities in open quantum systems via two-point system-only measurements

Alessandra Colla, Andrea Smirne, Heinz-Peter Breuer, Bassano Vacchini · 2026

We propose a method to evaluate general thermodynamic fluctuations in open quantum systems, based on performing a two-point measurement scheme on the system using dynamics-dependent thermodynamic obse…

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Physics Preprint PDF DOI

Quantum Feature Selection with Higher-Order Binary Optimization on Trapped-Ion Hardware

Carlos Flores-Garrigos, Anton Simen, Qi Zhang, Enrique Solano, Narendra N. Hegade, Sayonee Ray, Claudio Girotto, Jason Iaconis, Martin Roetteler · 2026

We present a quantum feature-selection framework based on a higher-order unconstrained binary optimization (HUBO) formulation that explicitly incorporates multivariate dependencies beyond standard qua…

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Physics Preprint PDF DOI

Continuum contribution to charged-current absorption of low-energy $\nu_e$ on $^{40}$Ar

Steven Gardiner, Pablo Barham Alzas, Alexis Nikolakopoulos, Luca H. Abu El-Haj, Natalie Jachowicz, Vishvas Pandey · 2026

Accurate modeling of the absorption of tens-of-MeV $\nu_e$ on $^{40}$Ar is needed to enable measurements of astrophysical neutrinos using large liquid argon time projection chamber (LArTPC) detectors,…

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Physics Preprint PDF DOI

Status of the KM3NeT real-time analysis framework

Martina Marconi (on behalf of the KM3NeT Collaboration) · 2026

Multi-messenger astronomy requires real-time systems capable of rapidly responding to external alerts and sharing significant detections with partner observatories. KM3NeT, a deep-sea Cherenkov neutri…

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Physics Preprint PDF DOI

SRGA J115215.0$-$510656: an unusual long-period eclipsing dwarf nova with disc wind signatures

Nikita Rawat, David A. H. Buckley, John R. Thorstensen, Christian Knigge, Yusuke Tampo, Stephen B. Potter, Anupam Bhardwaj, Simone Scaringi, Ilya A. Mereminskiy, Jeewan C. Pandey, Srinivas M Rao, Alexander A. Lutovinov · 2026

We present the first detailed optical study of the cataclysmic variable SRGA J115215.0$-$510656, based on new time-resolved photometric and spectroscopic observations complemented by long-baseline Tra…

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Physics Preprint PDF DOI

Euclid preparation. Refining input galaxy shape distributions for shear calibration simulations

Euclid Collaboration: H. Jansen, N. Martinet, S. Grandis, H. Hoekstra, S.-S. Li, T. Schrabback, G. Congedo, B. Csizi, F. Kleinebreil, G. Mankar, N. Zimmermann, B. Altieri, S. Andreon, N. Auricchio, C. Baccigalupi, M. Baldi, S. Bardelli, P. Battaglia, A. Biviano, E. Branchini, M. Brescia, S. Camera, V. Capobianco, C. Carbone, V. F. Cardone, J. Carretero, S. Casas, F. J. Castander, M. Castellano, G. Castignani, S. Cavuoti, A. Cimatti, C. Colodro-Conde, L. Conversi, Y. Copin, F. Courbin, H. M. Courtois, M. Cropper, H. Degaudenzi, G. De Lucia, H. Dole, F. Dubath, X. Dupac, S. Escoffier, M. Farina, R. Farinelli, S. Farrens, S. Ferriol, P. Fosalba, S. Fotopoulou, N. Fourmanoit, M. Frailis, E. Franceschi, M. Fumana, S. Galeotta, K. George, B. Gillis, C. Giocoli, J. Gracia-Carpio, A. Grazian, F. Grupp, S. V. H. Haugan, W. Holmes, I. M. Hook, F. Hormuth, A. Hornstrup, K. Jahnke, M. Jhabvala, B. Joachimi, S. Kermiche, A. Kiessling, B. Kubik, K. Kuijken, M. Kummel, M. Kunz, H. Kurki-Suonio, A. M. C. Le Brun, S. Ligori, P. B. Lilje, V. Lindholm, I. Lloro, G. Mainetti, O. Mansutti, O. Marggraf, M. Martinelli, F. Marulli, R. J. Massey, E. Medinaceli, M. Meneghetti, E. Merlin, G. Meylan, A. Mora, M. Moresco, B. Morin, L. Moscardini, R. Nakajima, C. Neissner, S.-M. Niemi, J. W. Nightingale, C. Padilla, S. Paltani, F. Pasian, K. Pedersen, W. J. Percival, V. Pettorino, S. Pires, G. Polenta, L. A. Popa, F. Raison, A. Renzi, J. Rhodes, G. Riccio, M. Roncarelli, R. Saglia, Z. Sakr, D. Sapone, P. Schneider, A. Secroun, E. Sihvola, P. Simon, C. Sirignano, G. Sirri, L. Stanco, P. Tallada-Crespi, A. N. Taylor, I. Tereno, N. Tessore, S. Toft, R. Toledo-Moreo, F. Torradeflot, I. Tutusaus, J. Valiviita, T. Vassallo, G. Verdoes Kleijn, Y. Wang, J. Weller, G. Zamorani, F. M. Zerbi, E. Zucca, M. Ballardini, A. Boucaud, E. Bozzo, C. Burigana, R. Cabanac, M. Calabrese, A. Cappi, T. Castro, J. A. Escartin Vigo, J. Garcia-Bellido, S. Hemmati, E. Jullo, J. Macias-Perez, R. Maoli, J. Martin-Fleitas, N. Mauri, R. B. Metcalf, P. Monaco, A. Pezzotta, M. Pontinen, I. Risso, V. Scottez, M. Sereno, M. Tenti, M. Tucci, M. Viel, M. Wiesmann, Y. Akrami, I. T. Andika, G. Angora, S. Anselmi, M. Archidiacono, F. Atrio-Barandela, L. Baumont, L. Bazzanini, D. Bertacca, M. Bethermin, F. Beutler, A. Blanchard, L. Blot, M. Bonici, S. Borgani, M. L. Brown, S. Bruton, A. Calabro, B. Camacho Quevedo, F. Caro, C. S. Carvalho, F. Cogato, A. R. Cooray, O. Cucciati, J. E. Davies, T. de Boer, G. Desprez, A. Diaz-Sanchez, S. Di Domizio, J. M. Diego, V. Duret, M. Y. Elkhashab, Y. Fang, A. Finoguenov, A. Franco, K. Ganga, R. Gavazzi, E. Gaztanaga, F. Giacomini, F. Gianotti, G. Gozaliasl, A. Gruppuso, M. Guidi, C. M. Gutierrez, A. Hall, C. Hernandez-Monteagudo, H. Hildebrandt, J. J. E. Kajava, Y. Kang, V. Kansal, D. Karagiannis, K. Kiiveri, J. Kim, C. C. Kirkpatrick, K. Koyama, S. Kruk, M. C. Lam, M. Lattanzi, L. Legrand, M. Lembo, F. Lepori, G. Leroy, G. F. Lesci, J. Lesgourgues, T. I. Liaudat, S. J. Liu, M. Magliocchetti, F. Mannucci, C. J. A. P. Martins, L. Maurin, M. Miluzio, C. Moretti, G. Morgante, S. Nadathur, K. Naidoo, A. Navarro-Alsina, S. Nesseris, F. Pace, D. Paoletti, F. Passalacqua, K. Paterson, L. Patrizii, C. Pattison, A. Pisani, D. Potter, G. W. Pratt, S. Quai, M. Radovich, K. Rojas, W. Roster, S. Sacquegna, M. Sahlen, D. B. Sanders, E. Sarpa, A. Schneider, D. Sciotti, D. Scognamiglio, E. Sellentin, L. C. Smith, E. Soubrie, I. Szapudi, K. Tanidis, F. Tarsitano, G. Testera, M. Tewes, R. Teyssier, S. Tosi, A. Troja, C. Uhlemann, C. Valieri, A. Venhola, D. Vergani, G. Verza, E. Vilenius, S. Vinciguerra, M. von Wietersheim-Kramsta, N. A. Walton, A. H. Wright · 2026

The Euclid Wide Survey (EWS) will cover the majority of the extragalactic sky with a resolution similar to the Hubble Space Telescope. This unprecedented data set will introduce a new era of precision…

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Physics Preprint PDF DOI

Inverse Design of Cellular Composites for Targeted Nonlinear Mechanical Response via Multi-Fidelity Bayesian Optimisation

Hirak Kansara, Leo Guo, Wei Tan · 2026

The rise of machine learning and additive manufacturing has enabled the design of architected materials with tailored properties that surpass those of natural materials. Inverse design offers a data-e…

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Physics Preprint PDF DOI

Possible explanation of Hoehler's clustering: effective partial-wave mixing induced by truncation

A. Svarc · 2026

Hoehler noted that resonance poles obtained from different partial waves in $\pi N$ scattering appear to bunch together near a small set of common complex energies, and suggested that this could indic…

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Physics Preprint PDF DOI

Large-eddy simulation nets (LESnets) based on physics-informed neural operator for wall-bounded turbulence

Sunan Zhao, Yunpeng Wang, Huiyu Yang, Zhihong Guo, Jianchun Wang · 2026

Accurate and efficient prediction of three-dimensional (3D) wall-bounded turbulent flows poses a significant challenge for machine learning methods, particularly in scenarios where flow field data are…

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Physics Preprint PDF DOI

Normalizing flows for density estimation in multi-detector gravitational-wave searches

Sam Insley, Michael J. Williams, Rahul Dhurkunde, Ian Harry · 2026

Identifying compact binary coalescences buried within the non-Gaussian and non-stationary data taken by gravitational-wave interferometers requires sophisticated search pipelines, such as the PyCBC an…

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