Mathematics > Numerical Analysis
arXiv:2606.23980 (math)
[Submitted on 22 Jun 2026]
Abstract:The Fokker-Planck equation is fundamental to statistical mechanics, yet in settings with multiple state variables, anisotropic (cross-) diffusion, and jumps, conventional discretizations frequently produce non-physical negative probability densities. Building on the operator approach of "A. Itkin, Pricing derivatives under Levy models. Modern finite difference and pseudo-differential operators approach, Springer, 2017, ISBN 978-1-4939-6792-6", we introduce a family of "Diagonal Frog" discretizations whose spatial operators are eventually M-matrices (EM-matrices). Although these operators lack a local M-matrix structure, positivity of the directional sub-operators emerges in the spirit of Zeno's paradox: the matrix exponential, assembled as the limit of infinitely many ever-smaller substeps, is provably nonnegative after a short transient even though no single substep is. For the mixed-derivative block, whose generator is not eventually nonnegative, positivity instead rests on a factorized resolvent solver and holds conditionally, on an explicit step-size window; discrete mass is conserved exactly by the splitting for every step size. The resulting schemes are second-order accurate in time and space and require O(m 2 N + m 3) operations per time step, where m is the dimension of the Krylov subspace used to apply the exponential. As stress tests, we solve a two-dimensional anisotropic Fokker-Planck equation in the strong cross-diffusion regime against an exact Gaussian reference, a Kramers escape problem in a double-well potential, and an advection-dominated problem, and observe that the schemes remain stable, nonnegative, and mass-conservative for a wide range of Pécklet numbers (so, don't need any flux limiter). Finally, we extend the construction to multidimensional processes and to the backward Kolmogorov equation with jumps.
| Comments: | 64 pages, 8 figures, 10 tables |
| Subjects: | Numerical Analysis (math.NA); Biological Physics (physics.bio-ph); Computational Physics (physics.comp-ph); Computational Finance (q-fin.CP); Pricing of Securities (q-fin.PR) |
| Cite as: | arXiv:2606.23980 [math.NA] |
| (or arXiv:2606.23980v1 [math.NA] for this version) | |
| https://doi.org/10.48550/arXiv.2606.23980 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Andrey Itkin [view email]
[v1]
Mon, 22 Jun 2026 22:13:55 UTC (187 KB)
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