papers

Publications (5)

cond-mat.quant-gas2026

Uncovering Exotic Paired States in the 2D Spin-Imbalanced Fermi Gas with Neural Wave Functions

Wan Tong Lou, Gino Cassella, Andres Perez Fadon +5

We study the zero-temperature phase diagram of the 2D spin-imbalanced Fermi gas with short-ranged attractive interactions using the recently developed neural network variational Mo…

physics.comp-ph2024

Accurate Computation of Quantum Excited States with Neural Networks

David Pfau, Simon Axelrod, Halvard Sutterud +2

We present a variational Monte Carlo algorithm for estimating the lowest excited states of a quantum system which is a natural generalization of the estimation of ground states. Th…

cond-mat.str-el2024

Interaction-Induced Symmetry Breaking in Circular Quantum Dots

Andres Perez Fadon, Gino Cassella, Halvard Sutterud +1

This paper investigates interaction-induced symmetry breaking in circular quantum dots. We explain that the anisotropic static Wigner molecule ground states frequently observed in…

cond-mat.quant-gas2024

Neural Wave Functions for Superfluids

Wan Tong Lou, Halvard Sutterud, Gino Cassella +4

Understanding superfluidity remains a major goal of condensed matter physics. Here we tackle this challenge utilizing the recently developed Fermionic neural network (FermiNet) wav…

physics.comp-ph2024

Transferable Neural Wavefunctions for Solids

Leon Gerard, Michael Scherbela, Halvard Sutterud +2

Deep-Learning-based Variational Monte Carlo (DL-VMC) has recently emerged as a highly accurate approach for finding approximate solutions to the many-electron Schrödinger equation…