3 papers
cs.LG2026
One More Time: Revisiting Neural Quantum States from a Reinforcement Learning Perspective
Juan Agustín Duque, Sergio García Heredia, Vinicius Hernandes +4
Neural quantum states (NQS) provide a flexible and scalable framework for approximating quantum many-body wavefunctions. Among NQS parameterizations, autoregressive models are espe…
cond-mat.dis-nn2025
Double descent: When do neural quantum states generalize?
M. Schuyler Moss, Alev Orfi, Christopher Roth +5
Neural quantum states (NQS) provide flexible and compact wavefunction parameterizations for numerical studies of quantum many-body physics. In particular, NQS aim to circumvent the…
quant-ph2024
Speak so a physicist can understand you! TetrisCNN for detecting phase transitions and order parameters
Kacper Cybiński, James Enouen, Antoine Georges +1
Recently, neural networks (NNs) have become a powerful tool for detecting quantum phases of matter. Unfortunately, NNs are black boxes and only identify phases without elucidating…