Statistical properties of worm algorithms for two dimensional frustrated Ising models
arXiv:1812.11861 · doi:10.1103/PhysRevE.103.062101
Abstract
We study the distribution of lengths and other statistical properties of worms constructed by Monte Carlo worm algorithms in the power-law three-sublattice ordered phase of frustrated triangular and kagome lattice Ising antiferromagnets. Viewing each step of the worm construction as a position increment (step) of a random walker, we demonstrate that the persistence exponent and the dynamical exponent of this random walk depend only on the universal power-law exponents of the underlying critical phase, and not on the details of the worm algorithm or the microscopic Hamiltonian. Further, we argue that the detailed balance criterion obeyed by such worm algorithms and the power-law correlations of the underlying equilibrium system together give rise to two related properties of this random walk: First, the steps of the walk are expected to be power-law correlated in time. Second, the position distribution of the walker relative to its starting point is given by the equilibrium position distribution of a particle in an attractive logarithmic central potential of strength , where is the universal power-law exponent of the equilibrium defect-antidefect correlation function of the underlying spin system. We derive a scaling relation, , that allows us to express the dynamical exponent of this process in terms of its persistence exponent . Our measurements of and are consistent with this relation over a range of values of the universal equilibrium exponent , and yield subdiffusive () values of in the entire range. Thus we demonstrate that the worms represent a discrete-time realization of a fractional Brownian motion characterized by these properties.
arXiv commentSeveral figures moved to appendix in response to referee suggestions. Includes additional discussion on Markovian limit and connection to contour lines of Gaussian free field
References in corpus (24)
- Stochastic series expansion method with operator-loop update
- Worm algorithms for classical statistical models
- The Loop Algorithm
- The superconductor-insulator transition in 2D dirty boson systems
- Conformally Invariant Fractals and Potential Theory
- Monte Carlo simulation of ice models
- Classical dimers with aligning interactions on the square lattice
- Accessing the dynamics of large many-particle systems using Stochastic Series Expansion
- Random Walks in Logarithmic and Power-Law Potentials, Nonuniversal Persistence, and Vortex Dynamics in the Two-Dimensional XY Model
- Cluster Monte Carlo Algorithm for the Quantum Rotor Model
- Quantum criticality, lines of fixed points, and phase separation in doped two-dimensional quantum dimer models
- Magnetic charge and ordering in kagome spin ice
- Analysis of a fully packed loop model arising in a magnetic Coulomb phase
- Correlations and confinement in non-planar two-dimensional dimer models
- Transient ageing in fractional Brownian and Langevin equation motion
- Fractal Structure of Spin Clusters and Domain Walls in 2D Ising Model
- Directed geometrical worm algorithm applied to the quantum rotor model
- Fractional stochastic differential equations satisfying fluctuation-dissipation theorem
- Melting of three-sublattice order in easy-axis antiferromagnets on triangular and Kagome lattices
- Cluster algorithms for frustrated two dimensional Ising antiferromagnets via dual worm constructions
- Bilayer Coulomb phase of two dimensional dimer models: Absence of power-law columnar order
- Critical Loop Gases and the Worm Algorithm
- Cluster Analysis for Percolation on Two Dimensional Fully Frustrated System
- Dual Geometric Worm Algorithm for Two-Dimensional Discrete Classical Lattice Models