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We present a generic reweighting method for nonequilibrium Markov processes.With nonequilibrium Monte Carlo simulations at a single temperature, onecalculates the time evolution of physical quantities at different temperatures,which greatly saves the computational time. Using the dynamical finite-sizescaling analysis for the nonequilibrium relaxation, one can study the dynamicalproperties of phase transitions together with the equilibrium ones. Wedemonstrate the procedure for the Ising model with the Metropolis algorithm,but the present formalism is general and can be applied to a variety of systemsas well as with different Monte Carlo update schemes.Comment: accepted for publication in Phys. Rev. E (Rapid Communications

Reweighting for nonequilibrium Markov processes using sequential importance sampling methods