@article{af43245f8b214f9b9187f38e9810bbcf,
title = "Finite-temperature properties of strongly correlated systems via variational Monte Carlo",
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.",
author = "Jahan Claes and Clark, {Bryan K.}",
note = "Funding Information: This research is part of the Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation (Awards No.OCI-0725070 and No.ACI-1238993) and the state of Illinois. Blue Waters is a joint effort of the University of Illinois at Urbana-Champaign and its National Center for Supercomputing Applications. This work was also supported by SciDAC-DOE Grant No.DE-FG02-12ER46875. We thank the Department of Energy's Institute for Nuclear Theory at the University of Washington for its hospitality where initial versions of this work were presented. Parts of this work were performed at the Aspen Center for Physics, which is supported by National Science Foundation Grant No.PHY-106629. Publisher Copyright: {\textcopyright} 2017 American Physical Society.",
year = "2017",
month = may,
day = "8",
doi = "10.1103/PhysRevB.95.205109",
language = "English (US)",
volume = "95",
journal = "Physical Review B",
issn = "2469-9950",
publisher = "American Physical Society",
number = "20",
}