期刊
COMPUTER PHYSICS COMMUNICATIONS
卷 267, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.cpc.2021.108075
关键词
Quantum Monte Carlo; Dynamical mean field theory; Anderson impurity model; Strongly-correlated materials; Quantum impurity solver
资金
- US Department of Energy, Office of Basic Energy Sciences as part of the Computational Material Science Program [DE-AC05-00OR22725]
ComCTQMC is a GPU-accelerated quantum impurity solver that efficiently measures various observables and can solve complex-valued impurity problems. It demonstrates significant acceleration in large Hilbert spaces but may offer less impressive results or even deceleration in simpler problems. The solver employs improved estimators and reduced density matrices to enhance observable measurements.
We present ComCTQMC, a GPU accelerated quantum impurity solver. It uses the continuous-time quantum Monte Carlo (CTQMC) algorithm wherein the partition function is expanded in terms of the hybridisation function (CT-HYB). ComCTQMC supports both partition and worm-space measurements, and it uses improved estimators and the reduced density matrix to improve observable measurements whenever possible. ComCTQMC efficiently measures all one and two-particle Green's functions, all static observables which commute with the local Hamiltonian, and the occupation of each impurity orbital. ComCTQMC can solve complex-valued impurities with crystal fields that are hybridized to both fermionic and bosonic baths. Most importantly, ComCTQMC utilizes graphical processing units (GPUs), if available, to dramatically accelerate the CTQMC algorithm when the Hilbert space is sufficiently large. We demonstrate acceleration by a factor of over 600 (100) in a simulation of delta-Pu at 600 K with (without) crystal fields. In easier problems, the GPU offers less impressive acceleration or even decelerates the CTQMC. Here we describe the theory, algorithms, and structure used by ComCTQMC in order to achieve this set of features and level of acceleration.
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