Abstraction-Based Segmental Simulation of Chemical Reaction Networks

TL;DR

This paper introduces a segmentation-based simulation method for chemical reaction networks that accelerates computations by reusing precomputed segments, while maintaining accuracy through system abstraction.

Contribution

It presents a novel approach combining segmentation and abstraction to efficiently simulate chemical networks with preserved dynamics and properties.

Findings

Significant speedups in simulation times.

Runs closely match true system distributions.

Efficient abstraction-based simulation scheme.

Abstract

Simulating chemical reaction networks is often computationally demanding, in particular due to stiffness. We propose a novel simulation scheme where long runs are not simulated as a whole but assembled from shorter precomputed segments of simulation runs. On the one hand, this speeds up the simulation process to obtain multiple runs since we can reuse the segments. On the other hand, questions on diversity and genuineness of our runs arise. However, we ensure that we generate runs close to their true distribution by generating an appropriate abstraction of the original system and utilizing it in the simulation process. Interestingly, as a by-product, we also obtain a yet more efficient simulation scheme, yielding runs over the system's abstraction. These provide a very faithful approximation of concrete runs on the desired level of granularity, at a low cost. Our experiments demonstrate the speedups in the simulations while preserving key dynamical as well as quantitative properties.