The Complexity of Approximately Counting Tree Homomorphisms
Leslie Ann Goldberg, Mark Jerrum

TL;DR
This paper classifies the computational complexity of counting homomorphisms and weighted homomorphisms from graphs to trees, revealing rich structures and connections to problems like #BIS, #SAT, and the Potts model.
Contribution
It provides a complete complexity classification (trichotomy) for #WHomsTo(H) and #HomsTo(H) when H is a tree, including new links to the Potts model and disproving previous conjectures.
Findings
#WHomsTo(H) is in FP if H is a star.
#WHomsTo(H) is #BIS-hard or #SAT-hard depending on H's structure.
Certain trees H make #HomsTo(H) #SAT-equivalent.
Abstract
We study two computational problems, parameterised by a fixed tree H. #HomsTo(H) is the problem of counting homomorphisms from an input graph G to H. #WHomsTo(H) is the problem of counting weighted homomorphisms to H, given an input graph G and a weight function for each vertex v of G. Even though H is a tree, these problems turn out to be sufficiently rich to capture all of the known approximation behaviour in #P. We give a complete trichotomy for #WHomsTo(H). If H is a star then #WHomsTo(H) is in FP. If H is not a star but it does not contain a certain induced subgraph J_3 then #WHomsTo(H) is equivalent under approximation-preserving (AP) reductions to #BIS, the problem of counting independent sets in a bipartite graph. This problem is complete for the class #RHPi_1 under AP-reductions. Finally, if H contains an induced J_3 then #WHomsTo(H) is equivalent under AP-reductions to #SAT,…
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