Abstract
As the analog of the free energy for dynamical trajectories, the large deviation functionplays a central role in the statistical mechanics of systems far from equilibrium. Here, weidentify numerical issues that can arise when the model of interest evolves according to acontinuous-time dynamics. This analysis motivates the introduction of an algorithm inwhich a list of previously visited states is used to resample the distribution of interest. Wediscuss the convergence properties of our algorithm in detail and demonstrate itsapplication to the single-site zero-range process and the many-site totally asymmetricexclusion process.
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