Adaptive Finite State Projection with Quantile-Based Pruning for Solving the Chemical Master Equation
Computational Engineering, Finance, and Science
2025-04-07 v1
Abstract
We present an adaptive Finite State Projection (FSP) method for efficiently solving the Chemical Master Equation (CME) with rigorous error control. Our approach integrates time-stepping with dynamic state-space truncation, balancing accuracy and computational cost. Krylov subspace methods approximate the matrix exponential, while quantile-based pruning controls state-space growth by removing low-probability states. Theoretical error bounds ensure that the truncation error remains bounded by the pruned mass at each step, which is user-controlled, and does not propagate forward in time. Numerical experiments on biochemical systems, including the Lotka-Volterra and Michaelis-Menten and bi-stable toggle switch models.
Keywords
Cite
@article{arxiv.2504.03070,
title = {Adaptive Finite State Projection with Quantile-Based Pruning for Solving the Chemical Master Equation},
author = {Aditya Dendukuri and Linda Petzold},
journal= {arXiv preprint arXiv:2504.03070},
year = {2025}
}