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

Publication ,  Journal Article
Gao, Y; Liu, JG
Published in: Communications in Computational Physics
January 1, 2023

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.

Duke Scholars

Published In

Communications in Computational Physics

DOI

EISSN

1991-7120

ISSN

1815-2406

Publication Date

January 1, 2023

Volume

34

Issue

1

Start / End Page

132 / 172

Related Subject Headings

  • Applied Mathematics
  • 4601 Applied computing
 

Citation

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Gao, Y., & Liu, J. G. (2023). Random Walk Approximation for Irreversible Drift-Diffusion Process on Manifold: Ergodicity, Unconditional Stability and Convergence. Communications in Computational Physics, 34(1), 132–172. https://doi.org/10.4208/cicp.OA-2023-0021
Gao, Y., and J. G. Liu. “Random Walk Approximation for Irreversible Drift-Diffusion Process on Manifold: Ergodicity, Unconditional Stability and Convergence.” Communications in Computational Physics 34, no. 1 (January 1, 2023): 132–72. https://doi.org/10.4208/cicp.OA-2023-0021.
Gao, Y., and J. G. Liu. “Random Walk Approximation for Irreversible Drift-Diffusion Process on Manifold: Ergodicity, Unconditional Stability and Convergence.” Communications in Computational Physics, vol. 34, no. 1, Jan. 2023, pp. 132–72. Scopus, doi:10.4208/cicp.OA-2023-0021.
Journal cover image

Published In

Communications in Computational Physics

DOI

EISSN

1991-7120

ISSN

1815-2406

Publication Date

January 1, 2023

Volume

34

Issue

1

Start / End Page

132 / 172

Related Subject Headings

  • Applied Mathematics
  • 4601 Applied computing