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Status: Unchecked ×Keyword: spin-1/2 Heisenberg model ×Clear all

2 claims from 1 paper

1. Physics and Astronomy › Quantum many-body systems

   Two-dimensional frustrated J1−J2 model studied with neural network quantum states

   Choo, Neupert and Carleo · Physical review. B./Physical review. B · 2019

   The authors use a convolutional neural network as a variational wavefunction for the frustrated spin-1/2 J1-J2 Heisenberg model on the square lattice and compare it with existing state-of-the-art methods.

   Unchecked2 claims
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   1. UncheckedA convolutional neural-network wavefunction gives ground-state energies and properties for a frustrated magnet model that match, and often beat, leading existing methods.“We demonstrate that the resulting predictions for both ground-state energies and properties are competitive with, and often improve upon, existing state-of-the-art methods.”
   2. UncheckedIn a small region of maximal frustration, the neural-network ansatz performs comparatively well but not best among methods compared.“In a relatively small region in the parameter space, corresponding to the maximally frustrated regime, our ansatz exhibits comparatively good but not best performance.”