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20212026
most citedTowards the ground state of molecules via diffusion Monte Carlo on neural networks

63 citations · 114 across the 20 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

physics.chem-ph2025★ 1 cited

Spin-Adapted Neural Network Wavefunctions in Real Space

Ruichen Li, Yuzhi Liu, Du Jiang +7

Spin plays a fundamental role in understanding electronic structure, yet many real-space wavefunction methods fail to adequately consider it. We introduce the Spin-Adapted Antisymm…

physics.chem-ph2025

A particle view of many-body electronic structure with neural network wavefunction

Zichen Wang, Weizhong Fu, Zhe Li +2

In the study of electronic structure, the wavefunction view dominates the current research landscape and forms the theoretical foundation of modern quantum mechanics. In contrast,…

physics.chem-ph2025

Neural Scaling Laws Surpass Chemical Accuracy for the Many-Electron Schrödinger Equation

Du Jiang, Xuelan Wen, Yixiao Chen +8

We demonstrate, for the first time, that neural scaling laws can deliver near-exact solutions to the many-electron Schrödinger equation across a broad range of realistic molecules.…

physics.chem-ph2025

Empowering Neural Network-based Quantum Monte Carlo with Local Pseudopotentials

Weizhong Fu, Ryunosuke Fujimaru, Ruichen Li +9

Neural Network-based Quantum Monte Carlo (NNQMC), an emerging method for solving many-body quantum systems with high accuracy, has been mainly applied to small systems due to deman…

cond-mat.str-el2025★ 1 cited

Deep Learning Sheds Light on Integer and Fractional Topological Insulators

Xiang Li, Yixiao Chen, Bohao Li +4

Electronic topological phases of matter, characterized by robust boundary states derived from topologically nontrivial bulk states, are pivotal for next-generation electronic devic…