3 papers
cond-mat.str-el2026
Scaling universal Fermi network toward ground states: A diffusion-Monte-Carlo assessment
Yu-Sheng Li, Saskia Poldmaa, Tzen Ong +4
In this work, we show that Fermi Sets---a provably universal neural network architecture for fermionic wavefunctions---can be systematically scaled up to find interacting ground st…
cond-mat.supr-con2026
Attention is all you need to solve chiral superconductivity
Chun-Tse Li, Tzen Ong, Max Geier +2
Recent advances on neural quantum states have shown that correlations between quantum particles can be efficiently captured by attention -- a foundation of modern neural architectu…
quant-ph2026
Quantum Algorithm for Low Energy Effective Hamiltonian and Quasi-Degenerate Eigenvalue Problem
Chun-Tse Li, Tzen Ong, Chih-Yun Lin +3
Quasi-degenerate eigenvalue problems are central to quantum chemistry and condensed-matter physics, where low-energy spectra often form manifolds of nearly degenerate states that d…