3 papers
cond-mat.supr-con2024
Imaging Josephson Vortices on Curved Junctions
Yuita Fujisawa, Anjana Krishnadas, Barnaby R. M. Smith +5
Understanding the nature of vortices in type-II superconductors is crucial for comprehending exotic superconductors and advancing the application of superconducting materials in fu…
hep-lat2024
Gauge covariant neural network for quarks and gluons
Yuki Nagai, Akio Tomiya
We propose gauge-covariant neural networks along with a specialized training algorithm for lattice QCD, designed to handle realistic quarks and gluons in four-dimensional space-tim…
cond-mat.str-el2024
Self-learning Monte Carlo with equivariant Transformer
Yuki Nagai, Akio Tomiya
Machine learning and deep learning have revolutionized computational physics, particularly the simulation of complex systems. Equivariance is essential for simulating physical syst…