Mean-field inclusion processes with a slow phase converge to a modulated Poisson-Dirichlet diffusion, a new two-component limit process with deterministic control.
Variational convergence for an irreversible exchange-driven stochastic particle system
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abstract
We show the variational convergence of an irreversible Markov jump process describing a finite stochastic particle system to the solution of a countable infinite system of deterministic time-inhomogeneous quadratic differential equations known as the exchange-driven growth model, which has two conserved quantities. As a bounded perturbation of the reversible kernel, the variational formulation is a generalization of the gradient flow formulation of the reversible process and can be interpreted as the large deviation functional of the Markov jump process. As a consequence of the variational convergence result, we show the propagation of chaos of the Markov processes to the limiting equation and the $\Gamma$-convergence of the energy functional. The latter convergence is consistent with related results for reversible coagulation-fragmentation equations and reveals the connection of stochastic processes to the long-time condensation phenomena in the limit equation.
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Modulated Poisson-Dirichlet diffusions arising from inclusion processes with a slow phase
Mean-field inclusion processes with a slow phase converge to a modulated Poisson-Dirichlet diffusion, a new two-component limit process with deterministic control.