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…
quant-ph2025
Quantum Algorithm for Low-Energy Effective Hamiltonians and Subspace Eigenvalue Problem
Chun-Tse Li, Tzen Ong, Chih-Yun Lin +3
Subspace eigenvalue problems arise ubiquitously in quantum chemistry and condensed-matter physics, where the relevant object is often a low-energy manifold rather than a single gro…
cond-mat.supr-con2025
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…