Complexity of the Graph Homomorphism Problem w.r.t. Degeneracy

2026-07-10Computational Complexity

Computational Complexity
AI summary

The authors study a problem called graph homomorphism (HOM), which asks if one graph can be mapped into another while keeping connections intact. They focus on how a property called degeneracy of the target graph affects how hard this problem is to solve. They find that degeneracy creates a complexity barrier: even graphs with low degeneracy make HOM very hard to solve quickly, and this hardness cannot be easily improved by known techniques. The authors also explain why certain lower bound proofs for related problems don't give the strongest possible results under common complexity assumptions.

graph homomorphismdegeneracyexponential time hypothesis (ETH)algorithmic complexitytreewidthchromatic numbersparse 2-CSPgraph parameterscomputational hardness
Authors
Grigorii Braulov, Nikolai Chukhin, Alexander S. Kulikov, Ivan Mihajlin
Abstract
The graph homomorphism problem HOM is: given an $n$-vertex source graph $G$ and an $h$-vertex target graph $H$, is there a mapping from $V(G)$ to $V(H)$ that preserves edges? A straightforward brute-force algorithm for HOM has running time $O(2^{n \log h})$ and it is known that, under ETH, there are no $2^{o(n \log h)}$ algorithms. In recent years, less restrictive graph parameters $p$ have been identified that allow one to solve HOM in time $p(H)^{O(n)}$. Examples include treewidth, maximum degree, and track number. On the other hand, it is known that the chromatic number parameter is too small: under ETH, HOM cannot be solved in time $χ(H)^{O(n)}$. We study the complexity of HOM in terms of the degeneracy of $H$. This is perhaps the most natural unresolved graph parameter between the known algorithmic and hardness regimes: on the one hand, each of bounded treewidth, bounded maximum degree, and bounded track number implies bounded degeneracy; on the other hand, bounded degeneracy implies bounded chromatic number. Our results show that, at the same time, the influence of degeneracy of $H$ on the complexity of HOM differs significantly from that of the previously studied parameters. We show that, under ETH, there is no $2^{o(degen(H) n)}$ algorithm for any value of $degen(H)$ as a function of $n$. We also show that bounded degeneracy alone does not make target size benign: even targets with $degen(H)$ at most $2$ and quasi-polynomial size force $n^{Ω(n)}$-scale hardness. Finally, we introduce a no-compression barrier that explains why the known fine-grained lower bounds for sparse $2$-CSP are not tight under ETH. Moreover, it shows that substantially stronger lower bounds for polynomial-target degeneracy are unlikely to follow from standard reductions from sparse $3$-SAT.