
TL;DR
This paper classifies the query complexity of testing list $H$-homomorphisms for different graph classes, revealing a trichotomy based on the structure of $H$ and establishing when constant, sublinear, or linear queries are needed.
Contribution
It provides a complete classification of graphs $H$ for which list $H$-homomorphisms are testable with various query complexities, introducing a trichotomy theorem.
Findings
Constant query testability for reflexive complete or irreflexive complete bipartite graphs.
Sublinear query testability for bi-arc graphs.
Linear query complexity for non-bi-arc graphs.
Abstract
Let be an undirected graph. In the List -Homomorphism Problem, given an undirected graph with a list constraint for each variable , the objective is to find a list -homomorphism , that is, for every and whenever . We consider the following problem: given a map as an oracle access, the objective is to decide with high probability whether is a list -homomorphism or \textit{far} from any list -homomorphisms. The efficiency of an algorithm is measured by the number of accesses to . In this paper, we classify graphs with respect to the query complexity for testing list -homomorphisms and show the following trichotomy holds: (i) List -homomorphisms are testable with a constant number of queries if and only if is a…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Advanced Graph Theory Research · Machine Learning and Algorithms
