129 research outputs found

    Counting Subgraphs in Somewhere Dense Graphs

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    We study the problems of counting copies and induced copies of a small pattern graph H in a large host graph G. Recent work fully classified the complexity of those problems according to structural restrictions on the patterns H. In this work, we address the more challenging task of analysing the complexity for restricted patterns and restricted hosts. Specifically we ask which families of allowed patterns and hosts imply fixed-parameter tractability, i.e., the existence of an algorithm running in time f(H)?|G|^O(1) for some computable function f. Our main results present exhaustive and explicit complexity classifications for families that satisfy natural closure properties. Among others, we identify the problems of counting small matchings and independent sets in subgraph-closed graph classes ? as our central objects of study and establish the following crisp dichotomies as consequences of the Exponential Time Hypothesis: - Counting k-matchings in a graph G ? ? is fixed-parameter tractable if and only if ? is nowhere dense. - Counting k-independent sets in a graph G ? ? is fixed-parameter tractable if and only if ? is nowhere dense. Moreover, we obtain almost tight conditional lower bounds if ? is somewhere dense, i.e., not nowhere dense. These base cases of our classifications subsume a wide variety of previous results on the matching and independent set problem, such as counting k-matchings in bipartite graphs (Curticapean, Marx; FOCS 14), in F-colourable graphs (Roth, Wellnitz; SODA 20), and in degenerate graphs (Bressan, Roth; FOCS 21), as well as counting k-independent sets in bipartite graphs (Curticapean et al.; Algorithmica 19). At the same time our proofs are much simpler: using structural characterisations of somewhere dense graphs, we show that a colourful version of a recent breakthrough technique for analysing pattern counting problems (Curticapean, Dell, Marx; STOC 17) applies to any subgraph-closed somewhere dense class of graphs, yielding a unified view of our current understanding of the complexity of subgraph counting

    Parameterized (Modular) Counting and Cayley Graph Expanders

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    We study the problem #EdgeSub(?) of counting k-edge subgraphs satisfying a given graph property ? in a large host graph G. Building upon the breakthrough result of Curticapean, Dell and Marx (STOC 17), we express the number of such subgraphs as a finite linear combination of graph homomorphism counts and derive the complexity of computing this number by studying its coefficients. Our approach relies on novel constructions of low-degree Cayley graph expanders of p-groups, which might be of independent interest. The properties of those expanders allow us to analyse the coefficients in the aforementioned linear combinations over the field ?_p which gives us significantly more control over the cancellation behaviour of the coefficients. Our main result is an exhaustive and fine-grained complexity classification of #EdgeSub(?) for minor-closed properties ?, closing the missing gap in previous work by Roth, Schmitt and Wellnitz (ICALP 21). Additionally, we observe that our methods also apply to modular counting. Among others, we obtain novel intractability results for the problems of counting k-forests and matroid bases modulo a prime p. Furthermore, from an algorithmic point of view, we construct algorithms for the problems of counting k-paths and k-cycles modulo 2 that outperform the best known algorithms for their non-modular counterparts. In the course of our investigations we also provide an exhaustive parameterized complexity classification for the problem of counting graph homomorphisms modulo a prime p

    On the Complexity of Bounded Context Switching

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    Bounded context switching (BCS) is an under-approximate method for finding violations to safety properties in shared-memory concurrent programs. Technically, BCS is a reachability problem that is known to be NP-complete. Our contribution is a parameterized analysis of BCS. The first result is an algorithm that solves BCS when parameterized by the number of context switches (cs) and the size of the memory (m) in O*(m^(cs)2^(cs)). This is achieved by creating instances of the easier problem Shuff which we solve via fast subset convolution. We also present a lower bound for BCS of the form m^o(cs / log(cs)), based on the exponential time hypothesis. Interestingly, the gap is closely related to a conjecture that has been open since FOCS\u2707. Further, we prove that BCS admits no polynomial kernel. Next, we introduce a measure, called scheduling dimension, that captures the complexity of schedules. We study BCS parameterized by the scheduling dimension (sdim) and show that it can be solved in O*((2m)^(4sdim)4^t), where t is the number of threads. We consider variants of the problem for which we obtain (matching) upper and lower bounds

    Counting Problems in Parameterized Complexity

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    This survey is an invitation to parameterized counting problems for readers with a background in parameterized algorithms and complexity. After an introduction to the peculiarities of counting complexity, we survey the parameterized approach to counting problems, with a focus on two topics of recent interest: Counting small patterns in large graphs, and counting perfect matchings and Hamiltonian cycles in well-structured graphs. While this survey presupposes familiarity with parameterized algorithms and complexity, we aim at explaining all relevant notions from counting complexity in a self-contained way

    Fine-Grained Complexity of k-OPT in Bounded-Degree Graphs for Solving TSP

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    The Traveling Salesman Problem asks to find a minimum-weight Hamiltonian cycle in an edge-weighted complete graph. Local search is a widely-employed strategy for finding good solutions to TSP. A popular neighborhood operator for local search is k-opt, which turns a Hamiltonian cycle C into a new Hamiltonian cycle C\u27 by replacing k edges. We analyze the problem of determining whether the weight of a given cycle can be decreased by a k-opt move. Earlier work has shown that (i) assuming the Exponential Time Hypothesis, there is no algorithm that can detect whether or not a given Hamiltonian cycle C in an n-vertex input can be improved by a k-opt move in time f(k) n^o(k / log k) for any function f, while (ii) it is possible to improve on the brute-force running time of O(n^k) and save linear factors in the exponent. Modern TSP heuristics are very successful at identifying the most promising edges to be used in k-opt moves, and experiments show that very good global solutions can already be reached using only the top-O(1) most promising edges incident to each vertex. This leads to the following question: can improving k-opt moves be found efficiently in graphs of bounded degree? We answer this question in various regimes, presenting new algorithms and conditional lower bounds. We show that the aforementioned ETH lower bound also holds for graphs of maximum degree three, but that in bounded-degree graphs the best improving k-move can be found in time O(n^((23/135+epsilon_k)k)), where lim_{k -> infty} epsilon_k = 0. This improves upon the best-known bounds for general graphs. Due to its practical importance, we devote special attention to the range of k in which improving k-moves in bounded-degree graphs can be found in quasi-linear time. For k <= 7, we give quasi-linear time algorithms for general weights. For k=8 we obtain a quasi-linear time algorithm when the weights are bounded by O(polylog n). On the other hand, based on established fine-grained complexity hypotheses about the impossibility of detecting a triangle in edge-linear time, we prove that the k = 9 case does not admit quasi-linear time algorithms. Hence we fully characterize the values of k for which quasi-linear time algorithms exist for polylogarithmic weights on bounded-degree graphs

    The complexity of detecting taut angle structures on triangulations

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    There are many fundamental algorithmic problems on triangulated 3-manifolds whose complexities are unknown. Here we study the problem of finding a taut angle structure on a 3-manifold triangulation, whose existence has implications for both the geometry and combinatorics of the triangulation. We prove that detecting taut angle structures is NP-complete, but also fixed-parameter tractable in the treewidth of the face pairing graph of the triangulation. These results have deeper implications: the core techniques can serve as a launching point for approaching decision problems such as unknot recognition and prime decomposition of 3-manifolds.Comment: 22 pages, 10 figures, 3 tables; v2: minor updates. To appear in SODA 2013: Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithm

    Lower Bounds for the Graph Homomorphism Problem

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    The graph homomorphism problem (HOM) asks whether the vertices of a given nn-vertex graph GG can be mapped to the vertices of a given hh-vertex graph HH such that each edge of GG is mapped to an edge of HH. The problem generalizes the graph coloring problem and at the same time can be viewed as a special case of the 22-CSP problem. In this paper, we prove several lower bound for HOM under the Exponential Time Hypothesis (ETH) assumption. The main result is a lower bound 2Ω(nloghloglogh)2^{\Omega\left( \frac{n \log h}{\log \log h}\right)}. This rules out the existence of a single-exponential algorithm and shows that the trivial upper bound 2O(nlogh)2^{{\mathcal O}(n\log{h})} is almost asymptotically tight. We also investigate what properties of graphs GG and HH make it difficult to solve HOM(G,H)(G,H). An easy observation is that an O(hn){\mathcal O}(h^n) upper bound can be improved to O(hvc(G)){\mathcal O}(h^{\operatorname{vc}(G)}) where vc(G)\operatorname{vc}(G) is the minimum size of a vertex cover of GG. The second lower bound hΩ(vc(G))h^{\Omega(\operatorname{vc}(G))} shows that the upper bound is asymptotically tight. As to the properties of the "right-hand side" graph HH, it is known that HOM(G,H)(G,H) can be solved in time (f(Δ(H)))n(f(\Delta(H)))^n and (f(tw(H)))n(f(\operatorname{tw}(H)))^n where Δ(H)\Delta(H) is the maximum degree of HH and tw(H)\operatorname{tw}(H) is the treewidth of HH. This gives single-exponential algorithms for graphs of bounded maximum degree or bounded treewidth. Since the chromatic number χ(H)\chi(H) does not exceed tw(H)\operatorname{tw}(H) and Δ(H)+1\Delta(H)+1, it is natural to ask whether similar upper bounds with respect to χ(H)\chi(H) can be obtained. We provide a negative answer to this question by establishing a lower bound (f(χ(H)))n(f(\chi(H)))^n for any function ff. We also observe that similar lower bounds can be obtained for locally injective homomorphisms.Comment: 19 page
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