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Counting List Homomorphisms from Graphs of Bounded Treewidth: Tight Complexity Bounds
ACM Transactions on Algorithms ( IF 1.3 ) Pub Date : 2024-02-13 , DOI: 10.1145/3640814
Jacob Focke 1 , Dániel Marx 1 , Paweł Rzążewski 2
Affiliation  

The goal of this work is to give precise bounds on the counting complexity of a family of generalized coloring problems (list homomorphisms) on bounded-treewidth graphs. Given graphs G, H, and lists \(L(v)\subseteq V(H)\) for every \(v\in V(G)\), a list homomorphism is a function \(f:V(G)\rightarrow V(H)\) that preserves the edges (i.e., \(uv\in E(G)\) implies \(f(u)f(v)\in E(H)\)) and respects the lists (i.e., \(f(v)\in L(v))\). Standard techniques show that if G is given with a tree decomposition of width t, then the number of list homomorphisms can be counted in time \(|V(H)|^t\cdot n^{\mathcal {O}(1)}\). Our main result is determining, for every fixed graph H, how much the base \(|V(H)|\) in the running time can be improved. For a connected graph H, we define irr(H) in the following way: if H has a loop or is nonbipartite, then irr(H) is the maximum size of a set \(S\subseteq V(H)\) where any two vertices have different neighborhoods; if H is bipartite, then irr(H) is the maximum size of such a set that is fully in one of the bipartition classes. For disconnected H, we define irr(H) as the maximum of irr(C) over every connected component C of H. It follows from earlier results that if irr(H)=1, then the problem of counting list homomorphisms to H is polynomial-time solvable, and otherwise it is #P-hard. We show that, for every fixed graph H, the number of list homomorphisms from (G,L) to H

can be counted in time \(\operatorname{irr}(H)^t\cdot n^{\mathcal {O}(1)}\) if a tree decomposition of G having width at most t is given in the input, and,

given that \(\operatorname{irr}(H)\ge 2\), cannot be counted in time \((\operatorname{irr}(H)-\varepsilon)^t\cdot n^{\mathcal {O}(1)}\) for any \(\varepsilon \gt 0\), even if a tree decomposition of G having width at most t is given in the input, unless the Counting Strong Exponential-Time Hypothesis (#SETH) fails.

Thereby, we give a precise and complete complexity classification featuring matching upper and lower bounds for all target graphs with or without loops.



中文翻译:

从有界树宽图中计算列表同态:严格的复杂性界限

这项工作的目标是对有界树宽图上的一系列广义着色问题(列表同态)的计数复杂性给出精确的界限。给定图GH和对于每个vV ( G ) 的列表L ( v )⊆ V ( H ) ,列表同态是保留边的函数f : V ( G ) → V ( H ) (即, uv ε E ( G ) 意味着f ( u ) f ( v ) ε E ( H )) 并遵守列表(即f ( v ) ε L ( v ))。标准技术表明,如果G给出宽度为t 的树分解,则可以在时间 \(|V(H)|^t\cdot n^{\mathcal {O}(1) 内计算列表同态的数量} \)。我们的主要结果是确定对于每个固定图H,基数 | 是多少。VH)| 在运行时间上可以得到改善。对于连通图H,我们按以下方式定义 \(\operatorname{irr}(H) \):如果H有环或非二部,则 \(\operatorname{irr}(H) \) 是最大尺寸集合SV ( H ) 的任意两个顶点具有不同的邻域;如果H是二分的,则 \(\operatorname{irr}(H) \) 是完全属于二分类之一的集合的最大大小。对于断开的H ,我们将 \(\operatorname{irr}(H) \) 定义为H的每个连通分量C上 \(\operatorname{irr}(C) \) 的最大值。从之前的结果可以看出,如果 \(\operatorname{irr}(H)=1 \),那么计算H的列表同态的问题是多项式时间可解的,否则是#P-困难的。我们证明,对于每个固定图H ,从 ( G , L ) 到H的列表同态数

如果输入中给出宽度至多为 t 的 G 的树分解,可以时间计算 \(\operatorname{irr}(H)^t\cdot n^{\mathcal {O}(1)} \)和

鉴于 \(\operatorname{irr}(H)\ge 2 \) 无法计算时间 \((\operatorname{irr}(H)-\epsilon)^t\cdot n^{\mathcal {O} (1)} \) 对于任何 ϵ > 0,即使输入中给出了宽度至多为t的G树分解,除非计数强指数时间假设 (#SETH) 失败。

因此,我们给出了精确且完整的复杂性分类,其特征在于为所有带或不带循环的目标图匹配上限和下限。

更新日期:2024-02-14
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