Neural ring homomorphism preserves mandatory sets required for open convexity
Neha Gupta, Suhith K N

TL;DR
This paper investigates how neural code properties related to convexity and local obstructions are affected by elementary code maps, highlighting the preservation of homological mandatory sets and exploring Stanley-Reisner ring relationships.
Contribution
It demonstrates that the homological mandatory set remains invariant under elementary code maps and explores the algebraic structure linking neural codes and simplicial complexes.
Findings
Homological mandatory sets are preserved under elementary code maps.
Relationships between Stanley-Reisner rings and neural codes are established.
Provides an alternative proof of the invariance of homological mandatory sets.
Abstract
It has been studied by Curto et al. (SIAM J. on App. Alg. and Geom., 1(1) : 222 238, 2017) that a neural code that has an open convex realization does not have any local obstruction relative to the neural code. Further, a neural code has no local obstructions if and only if it contains the set of mandatory codewords, which depends only on the simplicial complex . Thus if , then cannot be open convex. However, the problem of constructing for any given code is undecidable. There is yet another way to capture the local obstructions via the homological mandatory set, The significance of for a given code is that $…
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Taxonomy
TopicsTopological and Geometric Data Analysis · Computational Drug Discovery Methods · Cell Image Analysis Techniques
