mlsanityData to 7 Oct 2026

Phases of two-dimensional spinless lattice fermions with first-quantized deep neural-network quantum states

arXiv 2008.00118 ↗First posted 31 Jul 2020cond-mat.str-el cs.LG quant-phcited by 15

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Abstract (arXiv)

First-quantized deep neural network techniques are developed for analyzing strongly coupled fermionic systems on the lattice. Using a Slater-Jastrow inspired ansatz which exploits deep residual networks with convolutional residual blocks, we approximately determine the ground state of spinless fermions on a square lattice with nearest-neighbor interactions. The flexibility of the neural-network ansatz results in a high level of accuracy when compared to exact diagonalization results on small systems, both for energy and correlation functions. On large systems, we obtain accurate estimates of the boundaries between metallic and charge ordered phases as a function of the interaction strength and the particle density.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Jul 2020.

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Citing papers per year: 2021: 4; 2022: 5; 2023: 4; 2024: 1; 2025: 1.

15 papers.

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  1. 2021Gauge Invariant and Anyonic Symmetric Transformer and RNN Quantum States for Quantum Lattice Modelscited by 17
  2. 2021Ab-initio study of interacting fermions at finite temperature with neural canonical transformationcited by 16
  3. 2021Explicitly antisymmetrized neural network layers for variational Monte Carlo simulationcited by 14
  4. 2022Gauge Equivariant Neural Networks for 2+1D U(1) Gauge Theory Simulations in Hamiltonian Formulationcited by 11
  5. 2022Simulating 2+1D Lattice Quantum Electrodynamics at Finite Density with Neural Flow Wavefunctionscited by 10
  6. 2023Pairing-based graph neural network for simulating quantum materialscited by 9
  7. 2022Lattice Convolutional Networks for Learning Ground States of Quantum Many-Body Systemscited by 6
  8. 2025Physics-informed neural networks for high-dimensional solutions and snaking bifurcations in nonlinear latticescited by 3
  9. 2021Continuous-variable neural-network quantum states and the quantum rotor modelcited by 2
  10. 2023Convergence of variational Monte Carlo simulation and scale-invariant pre-trainingcited by 2
  11. 2023Anti-symmetric Barron functions and their approximation with sums of determinantscited by 2
  12. 2022O(N2) Universal Antisymmetry in Fermionic Neural Networkscited by 1
3 more
  1. 2023Artificial intelligence for artificial materials: moir'e atomcited by 1
  2. 2022Efficient anti-symmetrization of a neural network layer by taming the sign problemcited by 0
  3. 2024Uniform Ck Approximation of G-Invariant and Antisymmetric Functions, Embedding Dimensions, and Polynomial Representationscited by 0