Reweighting for Nonequilibrium Markov Processes Using Sequential Importance Sampling Methods

Abstract

We present a generic reweighting method for nonequilibrium Markov processes. With nonequilibrium Monte Carlo simulations at a single temperature, one calculates the time evolution of physical quantities at different temperatures, which greatly saves the computational time. Using the dynamical finite-size scaling analysis for the nonequilibrium relaxation, one can study the dynamical properties of phase transitions together with the equilibrium ones. We demonstrate the procedure for the Ising model with the Metropolis algorithm, but the present formalism is general and can be applied to a variety of systems as well as with different Monte Carlo update schemes.

accepted for publication in Phys. Rev. E (Rapid Communications)

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• Non-equilibrium relaxation and interface energy of the Ising model
• Dynamic Approach to the Fully Frustrated XY Model
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Cited by in corpus (8)

• Short-time domain-wall dynamics in the random-field Ising model with a driving field
• Capturing exponential variance using polynomial resources: applying tensor networks to non-equilibrium stochastic processes
• Nonequilibrium critical dynamics with domain wall and surface
• Dynamic effect of overhangs and islands at the depinning transition in two-dimensional magnets
• Short-time critical dynamics at perfect and non-perfect surface
• Nonequilibrium Reweighting on the Driven Diffusive Lattice Gas
• Multispin Coding Technique for Nonequilibrium Reweighting
• Critical domain-wall dynamics of model B