Parallelized Traveling Cluster Approximation to Study Numerically Spin-Fermion Models on Large Lattices
Anamitra Mukherjee, Niravkumar D. Patel, Chris Bishop, and Elbio, Dagotto

TL;DR
This paper introduces a parallelized version of the Traveling Cluster Approximation, enabling the simulation of large-scale spin-fermion models on lattices with up to 10^5 sites, significantly advancing computational capabilities.
Contribution
A novel parallelization of the Traveling Cluster Approximation that allows efficient simulation of large lattice spin-fermion models up to 10^5 sites.
Findings
Enables simulation of larger lattices than previous methods
Achieves record lattice sizes for spin-fermion models
Improves computational efficiency through parallelization
Abstract
Lattice spin-fermion models are important to study correlated systems where quantum dynamics allows for a separation between slow and fast degrees of freedom. The fast degrees of freedom are treated quantum mechanically while the slow variables, generically refereed to as the "spins", are treated classically. At present, exact diagonalization coupled with classical Monte Carlo (ED+MC) is extensively used to solve numerically a general class of lattice spin-fermion problems. In this common setup, the classical variables (spins) are treated via the standard MC method while the fermion problem is solved by exact diagonalization. The "Traveling Cluster Approximation" (TCA) is a real space variant of the ED+MC method that allows to solve spin-fermion problems on lattice sizes with up to sites. In this publication, we present a novel reorganization of the TCA algorithm in a manner that…
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