Finite-temperature properties of strongly correlated systems via variational Monte Carlo

Jahan Claes, Bryan K. Clark

Research output: Contribution to journalArticlepeer-review

Abstract

Variational methods are a common approach for computing properties of ground states but have not yet found analogous success in finite-temperature calculations. In this work, we develop a new variational finite-temperature algorithm (VAFT), which combines ideas from minimally entangled typical thermal states (METTS), variational Monte Carlo (VMC) optimization, and path integral Monte Carlo (PIMC). This allows us to define an implicit variational density matrix to estimate finite-temperature properties in two and three dimensions. We benchmark the algorithm on the bipartite Heisenberg model and compare to exact results.

Original languageEnglish (US)
Article number205109
JournalPhysical Review B
Volume95
Issue number20
DOIs
StatePublished - May 8 2017

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

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