Explicitly antisymmetrized neural network layers for variational Monte Carlo simulation

DOI10.1016/j.jcp.2022.111765OpenAlexW4308924602MaRDI QIDQ2112448

Jeffmin Lin, Lin Lin, Gil Goldshlager

Publication date: 11 January 2023

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2112.03491

zbMATH Keywords

neural networksmachine learningelectronic structureantisymmetryvariational Monte Carlo

Mathematics Subject Classification ID

Artificial intelligence (68Txx) Quantum theory (81-XX) Applications of quantum theory to specific physical systems (81Vxx)

Related Items (1)

A Multilevel Method for Many-Electron Schrödinger Equations Based on the Atomic Cluster Expansion

Uses Software

• PySCF
• Adam
• JAX

Cites Work

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• Why does deep and cheap learning work so well?
• Solving many-electron Schrödinger equation using deep neural networks
• Quantum Monte Carlo Methods
• Energy Spectrum of the Excitations in Liquid Helium
• On the eigenfunctions of many-particle systems in quantum mechanics
• Solving the quantum many-body problem with artificial neural networks
• Deep Neural Network Approximation Theory
• Quantum Monte Carlo Approaches for Correlated Systems

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