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  • Currently displaying 361 - 380 of 3293 publications
The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning
R Ohana, M McCabe, L Meyer, R Morel, FJ Agocs, M Beneitez, M Berger, B Burkhart, K Burns, SB Dalziel, DB Fielding, D Fortunato, JA Goldberg, K Hirashima, Y-F Jiang, RR Kerswell, S Maddu, J Miller, P Mukhopadhyay, SS Nixon, J Shen, R Watteaux, BR-S Blancard, F Rozet, LH Parker, M Cranmer, S Ho
(2024)
(link to publication)
Dispersion relations of relativistic radiation hydrodynamics
L Gavassino
(2024)
(link to publication)
Charged Rotating Hairy Black Holes in AdS$_5 \times S^5$: Unveiling their Secrets
OJC Dias, P Mitra, JE Santos
(2024)
(link to publication)
GPU-accelerated semicoherent hierarchical search for stellar-mass binary inspiral signals in LISA
D Bandopadhyay, CJ Moore
– Physical Review D
(2024)
110,
103026
(doi: 10.1103/PhysRevD.110.103026)
Non-Newtonian corrections to radiative viscosity: Israel-Stewart theory as a viscosity limiter
L Gavassino
(2024)
(link to publication)
Gapless nonhydrodynamic modes in relativistic kinetic theory
L Gavassino
– Physical Review Research
(2024)
6,
l042043
(doi: 10.1103/physrevresearch.6.l042043)
Smooth extremal horizons are the exception, not the rule
GT Horowitz, JE Santos
(2024)
(link to publication)
Spinning Black Binaries in de Sitter Space
ÓJC Dias, JE Santos, B Way
– Physical Review Letters
(2024)
133,
191401
(doi: 10.1103/PhysRevLett.133.191401)
Optimizing the Evolution of Perturbations in the $Λ$CDM Universe
S-F Chen, Z Vlah, M White
– Journal of Cosmology and Astroparticle Physics
(2024)
012
(doi: 10.1088/1475-7516/2024/11/012)
Convergence of the hydrodynamic gradient expansion in relativistic kinetic theory
L Gavassino
– Physical Review D
(2024)
110,
094012
(doi: 10.1103/PhysRevD.110.094012)
Accelerating Giant-impact Simulations with Machine Learning
C Lammers, M Cranmer, S Hadden, S Ho, N Murray, D Tamayo
– The Astrophysical Journal
(2024)
975,
228
(doi: 10.3847/1538-4357/ad7fe5)
Hair is complicated: Gravitational waves from stable and unstable boson-star mergers
B-X Ge, EA Lim, U Sperhake, T Evstafyeva, D Cors, ED Jong, R Croft, T Helfer
(2024)
(link to publication)
Perturbative unitarity bounds from momentum-space entanglement
CD Pueyo, H Goodhew, C McCulloch, E Pajer
(2024)
(link to publication)
Does it matter? A more careful treatment of density fluctuations in 21-cm simulations
J Flitter, S Libanore, ED Kovetz
(2024)
(link to publication)
The open effective field theory of inflation
SA Salcedo, T Colas, E Pajer
– Journal of High Energy Physics
(2024)
2024,
248
(doi: 10.1007/jhep10(2024)248)
Expected insights into Type Ia supernovae from LISA’s gravitational wave observations
V Korol, R Buscicchio, R Pakmor, J Morán-Fraile, CJ Moore, SE de Mink
– Astronomy & Astrophysics
(2024)
691,
A44
(doi: 10.1051/0004-6361/202451380)
Computational complexity of deep learning: fundamental limitations and empirical phenomena
B Barak, A Carrell, A Favero, W Li, L Stephan, A Zlokapa
– Journal of Statistical Mechanics: Theory and Experiment
(2024)
2024,
104008
(doi: 10.1088/1742-5468/ad3a5b)
The mass profiles of dwarf galaxies from Dark Energy Survey lensing
J Thornton, A Amon, RH Wechsler, S Adhikari, Y-Y Mao, J Myles, M Geha, N Kallivayalil, E Tollerud, B Weiner
– Monthly Notices of the Royal Astronomical Society
(2024)
535,
1
(doi: 10.1093/mnras/stae2040)
LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Merging
K Wang, N Dimitriadis, A Favero, G Ortiz-Jimenez, F Fleuret, P Frossard
(2024)
(link to publication)
What can be learnt with wide convolutional neural networks?*
F Cagnetta, A Favero, M Wyart
– Journal of Statistical Mechanics Theory and Experiment
(2024)
2024,
104020
(doi: 10.1088/1742-5468/ad65df)

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