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Volume 34, Issue 1
Random Walk Approximation for Irreversible Drift-Diffusion Process on Manifold: Ergodicity, Unconditional Stability and Convergence

Yuan Gao & Jian-Guo Liu

Commun. Comput. Phys., 34 (2023), pp. 132-172.

Published online: 2023-08

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  • Abstract

Irreversible drift-diffusion processes are very common in biochemical reactions. They have a non-equilibrium stationary state (invariant measure) which does not satisfy detailed balance. For the corresponding Fokker-Planck equation on a closed manifold, using Voronoi tessellation, we propose two upwind finite volume schemes with or without the information of the invariant measure. Both schemes possess stochastic $Q$-matrix structures and can be decomposed as a gradient flow part and a Hamiltonian flow part, enabling us to prove unconditional stability, ergodicity and error estimates. Based on the two upwind schemes, several numerical examples – including sampling accelerated by a mixture flow, image transformations and simulations for stochastic model of chaotic system – are conducted. These two structure-preserving schemes also give a natural random walk approximation for a generic irreversible drift-diffusion process on a manifold. This makes them suitable for adapting to manifold-related computations that arise from high-dimensional molecular dynamics simulations.

  • AMS Subject Headings

60H30, 60H35, 65M75, 65M12

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COPYRIGHT: © Global Science Press

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@Article{CiCP-34-132, author = {Gao , Yuan and Liu , Jian-Guo}, title = {Random Walk Approximation for Irreversible Drift-Diffusion Process on Manifold: Ergodicity, Unconditional Stability and Convergence}, journal = {Communications in Computational Physics}, year = {2023}, volume = {34}, number = {1}, pages = {132--172}, abstract = {

Irreversible drift-diffusion processes are very common in biochemical reactions. They have a non-equilibrium stationary state (invariant measure) which does not satisfy detailed balance. For the corresponding Fokker-Planck equation on a closed manifold, using Voronoi tessellation, we propose two upwind finite volume schemes with or without the information of the invariant measure. Both schemes possess stochastic $Q$-matrix structures and can be decomposed as a gradient flow part and a Hamiltonian flow part, enabling us to prove unconditional stability, ergodicity and error estimates. Based on the two upwind schemes, several numerical examples – including sampling accelerated by a mixture flow, image transformations and simulations for stochastic model of chaotic system – are conducted. These two structure-preserving schemes also give a natural random walk approximation for a generic irreversible drift-diffusion process on a manifold. This makes them suitable for adapting to manifold-related computations that arise from high-dimensional molecular dynamics simulations.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.OA-2023-0021}, url = {http://global-sci.org/intro/article_detail/cicp/21883.html} }
TY - JOUR T1 - Random Walk Approximation for Irreversible Drift-Diffusion Process on Manifold: Ergodicity, Unconditional Stability and Convergence AU - Gao , Yuan AU - Liu , Jian-Guo JO - Communications in Computational Physics VL - 1 SP - 132 EP - 172 PY - 2023 DA - 2023/08 SN - 34 DO - http://doi.org/10.4208/cicp.OA-2023-0021 UR - https://global-sci.org/intro/article_detail/cicp/21883.html KW - Symmetric decomposition, non-equilibrium thermodynamics, enhancement by mixture, exponential ergodicity, structure-preserving numerical scheme. AB -

Irreversible drift-diffusion processes are very common in biochemical reactions. They have a non-equilibrium stationary state (invariant measure) which does not satisfy detailed balance. For the corresponding Fokker-Planck equation on a closed manifold, using Voronoi tessellation, we propose two upwind finite volume schemes with or without the information of the invariant measure. Both schemes possess stochastic $Q$-matrix structures and can be decomposed as a gradient flow part and a Hamiltonian flow part, enabling us to prove unconditional stability, ergodicity and error estimates. Based on the two upwind schemes, several numerical examples – including sampling accelerated by a mixture flow, image transformations and simulations for stochastic model of chaotic system – are conducted. These two structure-preserving schemes also give a natural random walk approximation for a generic irreversible drift-diffusion process on a manifold. This makes them suitable for adapting to manifold-related computations that arise from high-dimensional molecular dynamics simulations.

Yuan Gao & Jian-Guo Liu. (2023). Random Walk Approximation for Irreversible Drift-Diffusion Process on Manifold: Ergodicity, Unconditional Stability and Convergence. Communications in Computational Physics. 34 (1). 132-172. doi:10.4208/cicp.OA-2023-0021
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