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Network Combination to Persistence of High-dimensional Delayed Complex Balanced Mass-action Systems

Authors :
Zhang, Xiaoyu
Gao, Chunhou
Dochain, Denis
Publication Year :
2023

Abstract

Complex balanced mass-action systems (CBMASs) are of great importance in the filed of biochemical reaction networks. However analyzing the persistence of these networks with high dimensions and time delays poses significant challenges. To tackle this, we propose a novel approach that combines 1-dimensional (1d) or 2d delayed CBMASs (DeCBMASs) and introduces inheritable combination methods based on the relationship between semilocking sets and intersecting species. These methods account for various scenarios, including cases where the set of intersecting species is empty, or there are no common species in non-trivial semilocking sets and the intersecting species set, or when special forms are present. By utilizing these combination methods, we derive sufficient conditions for the persistence of high-dimensional DeCBMASs. This significantly expands the known class of delayed chemical reaction network systems that exhibit persistence. The effectiveness of our proposed approach is also demonstrated through several examples, highlighting its practical applicability in real-world scenarios. This research contributes to advancing the understanding of high-dimensional DeCBMASs and offers insights into their persistent behavior.

Subjects

Subjects :
Mathematics - Dynamical Systems

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2307.10712
Document Type :
Working Paper