cond-mat.dis-nn · 2026-06-15 · No. 24

Disordered Systems and Neural Networks, 2026-06-15.

1 new papers in cond-mat.dis-nn. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

1 entries
  1. 01

    Direct/adaptive-mixture phase-gradient learning for neural-network quantum states with complex phase structure

    Yi-Ran Xue, Rui Wang, Baigeng Wang, Chenan Wei

    cond-mat.dis-nn · cond-mat.str-el · cs.LG · physics.comp-ph · quant-ph

    Neural-network quantum states (NQS) are a leading variational tool for quantum many-body physics, yet their optimization is fragile whenever the ground state carries a non-trivial sign or complex phase structure, a situation generic to gauge fields, broken time-reversal symmetry, and fermionic statistics. We trace this fragility to the stochastic estimator of the phase gradient rather than to network expressiveness. The phase sector of the...

    arxiv.org/abs/2606.13912 · PDF

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