Monte Carlo Algorithm for the Double Exchange Model Optimized for Parallel Computations

Abstract

A new algorithm for Monte Carlo calculation of the double exchange model is studied. The algorithm is commonly applicable to wide classes of strongly correlated electron systems which involve itinerant electrons coupled with thermodynamically fluctuating fields. Using moment expansions of the density of states with Chebyshev polynomials, the algorithm provides an efficient calculation on large size clusters, especially on parallel computers. Benchmark calculations are performed on Beowulf-type cluster systems with over 100 CPUs in parallel.

9 pages with 1 figure and 1 table. To be published in Computer Phys. Comm

References in corpus (1)

• Critical Phenomena of Ferromagnetic Transition in Double-Exchange Systems

Cited by in corpus (11)

• Phase Diagram of a Model for Diluted Magnetic Semiconductors Beyond Mean-Field Approximations
• Efficient Langevin Simulation of Coupled Classical Fields and Fermions
• Order N Monte Carlo Algorithm for Fermion Systems Coupled with Fluctuating Adiabatical Fields
• The Truncated Polynomial Expansion Monte Carlo Method for Fermion Systems Coupled to Classical Fields: A Model Independent Implementation
• Fragility of the A-type AF and CE Phases of Manganites: An Exotic Insulator-to-Metal Transition Induced by Quenched Disorder
• Study of the One- and Two-Band Models for Colossal Magnetoresistive Manganites Using the Truncated Polynomial Expansion Method
• Effective Ruderman-Kittel-Kasuya-Yosida-like interaction in diluted double-exchange model: self-learning Monte Carlo approach
• Calculation of Dynamical and Many-Body Observables with the Polynomial Expansion Method for Spin-Fermion Models
• Polynomial Expansion Monte Carlo Study of Frustrated Itinerant Electron Systems: Application to a Spin-ice type Kondo Lattice Model on a Pyrochlore Lattice
• Self-learning Monte Carlo with equivariant Transformer
• Sample generation for the spin-fermion model using neural networks