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Gingrich, Todd R.

Publications and source records attributed to Gingrich, Todd R..

Near-optimal protocols in complex nonequilibrium transformations

Significance Classical thermodynamics was developed to help design the best protocols for operating heat engines that remain close to equilibrium at all times. Modern experimental techniques for manipulating microscopic and mesoscopic systems routinely access far-from-equilibrium states, demanding new theoretical tools to describe the optimal protocols in this more complicated regime. Prior studies have sought, in simple models, the protocol that minimizes dissipation. We use computational tools to investigate the diversity of low-dissipation protocols. We show that optimal protocols can be accompanied by a vast set of near-optimal protocols, which still offer the substantive benefits of the optimal protocol. Although solving for the optimal protocol is typically difficult, computationally identifying a near-optimal protocol can be comparatively easy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Preserving correlations between trajectories for efficient path sampling

Importance sampling of trajectories has proved a uniquely successful strategy for exploring rare dynamical behaviors of complex systems in an unbiased way. Carrying out this sampling, however, requires an ability to propose changes to dynamical pathways that are substantial, yet sufficiently modest to obtain reasonable acceptance rates. Satisfying this requirement becomes very challenging in the case of long trajectories, due to the characteristic divergences of chaotic dynamics. Here, we examine schemes for addressing this problem, which engineer correlation between a trial trajectory and its reference path, for instance using artificial forces. Our analysis is facilitated by a modern perspective on Markov chain Monte Carlo sampling, inspired by non-equilibrium statistical mechanics, which clarifies the types of sampling strategies that can scale to long trajectories. Viewed in this light, the most promising such strategy guides a trial trajectory by manipulating the sequence of random numbers that advance its stochastic time evolution, as done in a handful of existing methods. In cases where this “noise guidance” synchronizes trajectories effectively, as the Glauber dynamics of a two-dimensional Ising model, we show that efficient path sampling can be achieved for even very long trajectories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗