Research paper · 2012-12-06
Algorithms for the Markov Entropy Decomposition
Andrew J. Ferris, David Poulin
Abstract
The Markov entropy decomposition (MED) is a recently-proposed, cluster-based simulation method for finite temperature quantum systems with arbitrary geometry. In this paper, we detail numerical algorithms for performing the required steps of the MED, principally solving a minimization problem with a preconditioned Newton's algorithm, as well as how to extract global susceptibilities and thermal responses. We demonstrate the power of the method with the spin-1/2 XXZ model on the 2D square lattice, including the extraction of critical points and details of each phase. Although the method shares some qualitative similarities with exact-diagonalization, we show the MED is both more accurate and significantly more flexible.
Details
- arXiv identifier
- 1212.1442
- Published
- 2012-12-06
- Authors
- Andrew J. Ferris, David Poulin
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