Event-chain algorithm for the Heisenberg model: Evidence for dynamic scaling
arXiv:1508.05661 · doi:10.1103/PhysRevE.92.063306
Abstract
We apply the event-chain Monte Carlo algorithm to the three-dimensional ferromagnetic Heisenberg model. The algorithm is rejection-free and also realizes an irreversible Markov chain that satisfies global balance. The autocorrelation functions of the magnetic susceptibility and the energy indicate a dynamical critical exponent at the critical temperature, while that of the magnetization does not measure the performance of the algorithm. This seems to be the first report that the event-chain Monte Carlo algorithm substantially reduces the dynamical critical exponent from the conventional value of .
arXiv comment4 pages, 5 figures
References in corpus (12)
- Exchange Monte Carlo Method and Application to Spin Glass Simulations
- Multicanonical Ensemble: A New Approach to Simulate First-order Phase Transitions
- Two-step melting in two dimensions: First-order liquid-hexatic transition
- 2D Melting: From Liquid-Hexatic Coexistence to Continuous Transitions
- Critical Exponents of the Classical 3D Heisenberg Model: A Single-Cluster Monte Carlo Study
- Event-chain Monte Carlo algorithms for hard-sphere systems
- Markov Chain Monte Carlo Method without Detailed Balance
- Generalized event-chain Monte Carlo: Constructing rejection-free global-balance algorithms from infinitesimal steps
- Rejection-free Monte-Carlo sampling for general potentials
- Irreversible Monte Carlo Algorithms for Efficient Sampling
- Hard-sphere melting and crystallization with event-chain Monte Carlo
- Event-chain Monte Carlo for classical continuous spin models
Cited by in corpus (30)
- Event-chain Monte Carlo: foundations, applications, and prospects
- Flow-based sampling for fermionic lattice field theories
- Piecewise Deterministic Markov Processes for Scalable Monte Carlo on Restricted Domains
- Irreversible local Markov chains with rapid convergence towards equilibrium
- Event-chain Monte Carlo algorithms for three- and many-particle interactions
- Cell-veto Monte Carlo algorithm for long-range systems
- Phase transitions and ordering structures of a model of chiral helimagnet in three dimensions
- Eigenvalue analysis of an irreversible random walk with skew detailed balance conditions
- All-atom computations with irreversible Markov chains
- Efficient Irreversible Monte Carlo samplers
- Clock Monte Carlo methods
- JeLLyFysh-Version1.0 -- a Python application for all-atom event-chain Monte Carlo
- Event-Chain Monte-Carlo Simulations of Dense Soft Matter Systems
- Event-chain Monte Carlo with factor fields
- Irreversible Markov chains in spin models: Topological excitations
- Lifted Worm Algorithm for the Ising Model
- Irreversible Markov chain Monte Carlo algorithm for self-avoiding walk
- PDMP characterisation of event-chain Monte Carlo algorithms for particle systems
- Hard-disk dipoles and non-reversible Markov chains
- Testing the event-chain algorithm in asymptotically free models
- Anomalous diffusion analysis of the lifting events in the event-chain Monte Carlo for the classical XY models
- Control of probability flow in Markov chain Monte Carlo -- Nonreversibility and lifting
- Irreversible swap algorithms for soft sphere glasses
- Simulated tempering with irreversible Gibbs sampling techniques
- Comparison of the clock, stochastic cutoff, and Tomita Monte Carlo methods in simulating the dipolar triangular lattice at criticality
- Bosonized one-dimensional quantum systems through enhanced event-chain Monte Carlo
- Phase Transitions for Cuboc Orders in Stacked Kagome Heisenberg Systems
- The generic Mott transition in the sine-Gordon model through an embedded worm algorithm
- Monte Carlo solver and renormalization of Migdal-Eliashberg spin chain
- Accelerating Multicanonical Sampling with Irreversibility