Reverse-Robust Computation with Chemical Reaction Networks
Abstract
Chemical reaction networks, or CRNs, are known to stably compute semilinear Boolean-valued predicates and functions, provided that all reactions are irreversible. However, this property does not hold for wet-lab implementations, as all chemical reactions are reversible, even at very slow rates. We study the computational power of CRNs under the reverse-robust computation model, where reactions are permitted to occur either in forward or in reverse up to a cutoff point, after which they may only occur in forward. Our main results show that all semilinear predicates and all semilinear functions can be computed reverse-robustly, and in fact, that existing constructions continue to hold under the reverse-robust computational model. A key tool used to prove correctness under the reverse-robust computation model is invariants: linear (or linear modulo some ) combinations of the counts of the species that are preserved by all reactions.
Cite
@article{arxiv.2604.14355,
title = {Reverse-Robust Computation with Chemical Reaction Networks},
author = {Ravi Kini and David Doty},
journal= {arXiv preprint arXiv:2604.14355},
year = {2026}
}