Jump processes as generalized gradient flows

By Mark A. Peletier, Riccarda Rossi, Giuseppe Savar'e, Oliver Tse. Calculus of Variations and Partial Differential Equations, 2020

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We have created a functional framework for a class of non-metric gradient systems. The state space is a space of nonnegative measures, and the class of systems includes the Forward Kolmogorov equations for the laws of Markov jump processes on Polish spaces. This framework comprises a definition of a notion of solutions, a method to prove existence, and an archetype uniqueness result. We do this by using only the structure that is provided directly by the dissipation functional, which need not be homogeneous, and we do not appeal to any metric structure.

Subfields: Applied Mathematics, Mathematical Physics, Modeling and Simulation

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