1,172 research outputs found

    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

    Weighted counting of solutions to sparse systems of equations

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    Given complex numbers w1,,wnw_1, \ldots, w_n, we define the weight w(X)w(X) of a set XX of 0-1 vectors as the sum of w1x1wnxnw_1^{x_1} \cdots w_n^{x_n} over all vectors (x1,,xn)(x_1, \ldots, x_n) in XX. We present an algorithm, which for a set XX defined by a system of homogeneous linear equations with at most rr variables per equation and at most cc equations per variable, computes w(X)w(X) within relative error ϵ>0\epsilon >0 in (rc)O(lnnlnϵ)(rc)^{O(\ln n-\ln \epsilon)} time provided wjβ(rc)1|w_j| \leq \beta (r \sqrt{c})^{-1} for an absolute constant β>0\beta >0 and all j=1,,nj=1, \ldots, n. A similar algorithm is constructed for computing the weight of a linear code over Fp{\Bbb F}_p. Applications include counting weighted perfect matchings in hypergraphs, counting weighted graph homomorphisms, computing weight enumerators of linear codes with sparse code generating matrices, and computing the partition functions of the ferromagnetic Potts model at low temperatures and of the hard-core model at high fugacity on biregular bipartite graphs.Comment: The exposition is improved, a couple of inaccuracies correcte

    Sparse random graphs with clustering

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    In 2007 we introduced a general model of sparse random graphs with independence between the edges. The aim of this paper is to present an extension of this model in which the edges are far from independent, and to prove several results about this extension. The basic idea is to construct the random graph by adding not only edges but also other small graphs. In other words, we first construct an inhomogeneous random hypergraph with independent hyperedges, and then replace each hyperedge by a (perhaps complete) graph. Although flexible enough to produce graphs with significant dependence between edges, this model is nonetheless mathematically tractable. Indeed, we find the critical point where a giant component emerges in full generality, in terms of the norm of a certain integral operator, and relate the size of the giant component to the survival probability of a certain (non-Poisson) multi-type branching process. While our main focus is the phase transition, we also study the degree distribution and the numbers of small subgraphs. We illustrate the model with a simple special case that produces graphs with power-law degree sequences with a wide range of degree exponents and clustering coefficients.Comment: 62 pages; minor revisio

    The step Sidorenko property and non-norming edge-transitive graphs

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    Sidorenko's Conjecture asserts that every bipartite graph H has the Sidorenko property, i.e., a quasirandom graph minimizes the density of H among all graphs with the same edge density. We study a stronger property, which requires that a quasirandom multipartite graph minimizes the density of H among all graphs with the same edge densities between its parts; this property is called the step Sidorenko property. We show that many bipartite graphs fail to have the step Sidorenko property and use our results to show the existence of a bipartite edge-transitive graph that is not weakly norming; this answers a question of Hatami [Israel J. Math. 175 (2010), 125-150].Comment: Minor correction on page

    09441 Abstracts Collection -- The Constraint Satisfaction Problem: Complexity and Approximability

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    From 25th to 30th October 2009, the Dagstuhl Seminar 09441 ``The Constraint Satisfaction Problem: Complexity and Approximability\u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

    Spectral preorder and perturbations of discrete weighted graphs

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    In this article, we introduce a geometric and a spectral preorder relation on the class of weighted graphs with a magnetic potential. The first preorder is expressed through the existence of a graph homomorphism respecting the magnetic potential and fulfilling certain inequalities for the weights. The second preorder refers to the spectrum of the associated Laplacian of the magnetic weighted graph. These relations give a quantitative control of the effect of elementary and composite perturbations of the graph (deleting edges, contracting vertices, etc.) on the spectrum of the corresponding Laplacians, generalising interlacing of eigenvalues. We give several applications of the preorders: we show how to classify graphs according to these preorders and we prove the stability of certain eigenvalues in graphs with a maximal d-clique. Moreover, we show the monotonicity of the eigenvalues when passing to spanning subgraphs and the monotonicity of magnetic Cheeger constants with respect to the geometric preorder. Finally, we prove a refined procedure to detect spectral gaps in the spectrum of an infinite covering graph.Comment: 26 pages; 8 figure

    The Complexity of Approximately Counting Retractions

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    Let GG be a graph that contains an induced subgraph HH. A retraction from GG to HH is a homomorphism from GG to HH that is the identity function on HH. Retractions are very well-studied: Given HH, the complexity of deciding whether there is a retraction from an input graph GG to HH is completely classified, in the sense that it is known for which HH this problem is tractable (assuming PNP\mathrm{P}\neq \mathrm{NP}). Similarly, the complexity of (exactly) counting retractions from GG to HH is classified (assuming FP#P\mathrm{FP}\neq \#\mathrm{P}). However, almost nothing is known about approximately counting retractions. Our first contribution is to give a complete trichotomy for approximately counting retractions to graphs of girth at least 55. Our second contribution is to locate the retraction counting problem for each HH in the complexity landscape of related approximate counting problems. Interestingly, our results are in contrast to the situation in the exact counting context. We show that the problem of approximately counting retractions is separated both from the problem of approximately counting homomorphisms and from the problem of approximately counting list homomorphisms --- whereas for exact counting all three of these problems are interreducible. We also show that the number of retractions is at least as hard to approximate as both the number of surjective homomorphisms and the number of compactions. In contrast, exactly counting compactions is the hardest of all of these exact counting problems
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