Nature Communications (Mar 2020)

Generalization properties of neural network approximations to frustrated magnet ground states

  • Tom Westerhout,
  • Nikita Astrakhantsev,
  • Konstantin S. Tikhonov,
  • Mikhail I. Katsnelson,
  • Andrey A. Bagrov

DOI
https://doi.org/10.1038/s41467-020-15402-w
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 8

Abstract

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Neural network representations of quantum states are hoped to provide an efficient basis for numerical methods without the need for case-by-case trial wave functions. Here the authors show that limited generalization capacity of such representations is responsible for convergence problems for frustrated systems.