3 papers
nlin.AO2025
Optimizing disorder with machine learning to harness synchronization
Jun-Yin Huang, Zheng-Meng Zhai, Vassilios Kovanis +1
Disorder is often considered detrimental to coherence. However, under specific conditions, it can enhance synchronization. We develop a machine-learning framework to design optimal…
quant-ph2025
Floquet quantum many-body scars in the tilted Fermi-Hubbard chain
Jun-Yin Huang, Li-Li Ye, Ying-Cheng Lai
The one-dimensional tilted, periodically driven Fermi-Hubbard chain is a paradigm in the study of quantum many-body physics, particularly for solid-state systems. We uncover the em…
cs.LG2024
Reconstructing dynamics from sparse observations with no training on target system
Zheng-Meng Zhai, Jun-Yin Huang, Benjamin D. Stern +1
In applications, an anticipated situation is where the system of interest has never been encountered before and sparse observations can be made only once. Can the dynamics be faith…