Document Type
Article
Publication Date
11-2022
Abstract
The popularity of molecular computation has given rise to several models of abstraction, one of the more recent ones being Chemical Reaction Networks (CRNs). These are equivalent to other popular computational models, such as Vector Addition Systems and Petri-Nets, and restricted versions are equivalent to Population Protocols. This paper continues the work on core reachability questions related to Chemical Reaction Networks; given two configurations, can one reach the other according to the system's rules? With no restrictions, reachability was recently shown to be Ackermann-complete, this resolving a decades-old problem.
Here, we fully characterize monotone reachability problems based on various restrictions such as the rule size, the number of rules that may create a species (k-source) or consume a species (k-consuming), the volume, and whether the rules have an acyclic production order (feed-forward). We show PSPACE-completeness of reachability with only bimolecular reactions with two-source and two-consuming rules. This proves hardness of reachability in Population Protocols, which was unknown. Further, this shows reachability in CRNs is PSPACE-complete with size-2 rules, which was previously only known with size-5 rules. This is achieved using techniques within the motion planning framework.
We provide many important results for feed-forward CRNs where rules are single-source or single-consuming. We show that reachability is solvable in polynomial time if the system does not contain special void or autogenesis rules. We then fully characterize all systems of this type and show that if you allow void/autogenesis rules, or have more than one source and one consuming, the problems become NP-complete. Finally, we show several interesting special cases of CRNs based on these restrictions or slight relaxations and note future significant open questions related to this taxonomy.
Recommended Citation
Alaniz, Robert M., et al. "Reachability in Restricted Chemical Reaction Networks." arXiv preprint arXiv:2211.12603 (2022).
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