160 research outputs found

    The MSO+U theory of (N, <) is undecidable

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    We consider the logic MSO+U, which is monadic second-order logic extended with the unbounding quantifier. The unbounding quantifier is used to say that a property of finite sets holds for sets of arbitrarily large size. We prove that the logic is undecidable on infinite words, i.e. the MSO+U theory of (N,<) is undecidable. This settles an open problem about the logic, and improves a previous undecidability result, which used infinite trees and additional axioms from set theory.Comment: 9 pages, with 2 figure

    Covering Vectors by Spaces: Regular Matroids

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    We consider the problem of covering a set of vectors of a given finite dimensional linear space (vector space) by a subspace generated by a set of vectors of minimum size. Specifically, we study the Space Cover problem, where we are given a matrix M and a subset of its columns T; the task is to find a minimum set F of columns of M disjoint with T such that that the linear span of F contains all vectors of T. This is a fundamental problem arising in different domains, such as coding theory, machine learning, and graph algorithms. We give a parameterized algorithm with running time 2^{O(k)}||M|| ^{O(1)} solving this problem in the case when M is a totally unimodular matrix over rationals, where k is the size of F. In other words, we show that the problem is fixed-parameter tractable parameterized by the rank of the covering subspace. The algorithm is "asymptotically optimal" for the following reasons. Choice of matrices: Vector matroids corresponding to totally unimodular matrices over rationals are exactly the regular matroids. It is known that for matrices corresponding to a more general class of matroids, namely, binary matroids, the problem becomes W[1]-hard being parameterized by k. Choice of the parameter: The problem is NP-hard even if |T|=3 on matrix-representations of a subclass of regular matroids, namely cographic matroids. Thus for a stronger parameterization, like by the size of T, the problem becomes intractable. Running Time: The exponential dependence in the running time of our algorithm cannot be asymptotically improved unless Exponential Time Hypothesis (ETH) fails. Our algorithm exploits the classical decomposition theorem of Seymour for regular matroids

    Unambiguous Separators for Tropical Tree Automata

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    In this paper we show that given a max-plus automaton (over trees, and with real weights) computing a function f and a min-plus automaton (similar) computing a function g such that f ? g, there exists effectively an unambiguous tropical automaton computing h such that f ? h ? g. This generalizes a result of Lombardy and Mairesse of 2006 stating that series which are both max-plus and min-plus rational are unambiguous. This generalization goes in two directions: trees are considered instead of words, and separation is established instead of characterization (separation implies characterization). The techniques in the two proofs are very different

    Distributed Strong Diameter Network Decomposition

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    For a pair of positive parameters D,χD,\chi, a partition P{\cal P} of the vertex set VV of an nn-vertex graph G=(V,E)G = (V,E) into disjoint clusters of diameter at most DD each is called a (D,χ)(D,\chi) network decomposition, if the supergraph G(P){\cal G}({\cal P}), obtained by contracting each of the clusters of P{\cal P}, can be properly χ\chi-colored. The decomposition P{\cal P} is said to be strong (resp., weak) if each of the clusters has strong (resp., weak) diameter at most DD, i.e., if for every cluster CPC \in {\cal P} and every two vertices u,vCu,v \in C, the distance between them in the induced graph G(C)G(C) of CC (resp., in GG) is at most DD. Network decomposition is a powerful construct, very useful in distributed computing and beyond. It was shown by Awerbuch \etal \cite{AGLP89} and Panconesi and Srinivasan \cite{PS92}, that strong (2O(logn),2O(logn))(2^{O(\sqrt{\log n})},2^{O(\sqrt{\log n})}) network decompositions can be computed in 2O(logn)2^{O(\sqrt{\log n})} distributed time. Linial and Saks \cite{LS93} devised an ingenious randomized algorithm that constructs {\em weak} (O(logn),O(logn))(O(\log n),O(\log n)) network decompositions in O(log2n)O(\log^2 n) time. It was however open till now if {\em strong} network decompositions with both parameters 2o(logn)2^{o(\sqrt{\log n})} can be constructed in distributed 2o(logn)2^{o(\sqrt{\log n})} time. In this paper we answer this long-standing open question in the affirmative, and show that strong (O(logn),O(logn))(O(\log n),O(\log n)) network decompositions can be computed in O(log2n)O(\log^2 n) time. We also present a tradeoff between parameters of our network decomposition. Our work is inspired by and relies on the "shifted shortest path approach", due to Blelloch \etal \cite{BGKMPT11}, and Miller \etal \cite{MPX13}. These authors developed this approach for PRAM algorithms for padded partitions. We adapt their approach to network decompositions in the distributed model of computation

    An Upper Bound on the Complexity of Recognizable Tree Languages

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    The third author noticed in his 1992 PhD Thesis [Sim92] that every regular tree language of infinite trees is in a class (D_n(Σ0_2))\Game (D\_n({\bf\Sigma}^0\_2)) for some natural number n1n\geq 1, where \Game is the game quantifier. We first give a detailed exposition of this result. Next, using an embedding of the Wadge hierarchy of non self-dual Borel subsets of the Cantor space 2ω2^\omega into the class Δ1_2{\bf\Delta}^1\_2, and the notions of Wadge degree and Veblen function, we argue that this upper bound on the topological complexity of regular tree languages is much better than the usual Δ1_2{\bf\Delta}^1\_2

    The complexity of verifying loop-free programs as differentially private

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    We study the problem of verifying differential privacy for loop-free programs with probabilistic choice. Programs in this class can be seen as randomized Boolean circuits, which we will use as a formal model to answer two different questions: first, deciding whether a program satisfies a prescribed level of privacy; second, approximating the privacy parameters a program realizes. We show that the problem of deciding whether a program satisfies ε-differential privacy is coNP#P-complete. In fact, this is the case when either the input domain or the output range of the program is large. Further, we show that deciding whether a program is (ε,δ)-differentially private is coNP#P-hard, and in coNP#P for small output domains, but always in coNP#P#P. Finally, we show that the problem of approximating the level of differential privacy is both NP-hard and coNP-hard. These results complement previous results by Murtagh and Vadhan showing that deciding the optimal composition of differentially private components is #P-complete, and that approximating the optimal composition of differentially private components is in P

    An Optimal Dual Fault Tolerant Reachability Oracle

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    Let G=(V,E) be an n-vertices m-edges directed graph. Let s inV be any designated source vertex. We address the problem of reporting the reachability information from s under two vertex failures. We show that it is possible to compute in polynomial time an O(n) size data structure that for any query vertex v, and any pair of failed vertices f_1, f_2, answers in O(1) time whether or not there exists a path from s to v in G{f_1,f_2}. For the simpler case of single vertex failure such a data structure can be obtained using the dominator-tree from the celebrated work of Lengauer and Tarjan [TOPLAS 1979, Vol. 1]. However, no efficient data structure was known in the past for handling more than one failures. We, in addition, also present a labeling scheme with O(log^3(n))-bit size labels such that for any f_1, f_2, v in Vit is possible to determine in poly-logarithmic time if v is reachable from s in G{f_1,f_2} using only the labels of f1, f_2 and v. Our data structure can also be seen as an efficient mechanism for verifying double-dominators. For any given x, y, v in V we can determine in O(1) time if the pair (x,y) is a double-dominator of v. Earlier the best known method for this problem was using dominator chain from which verification of double-dominators of only a single vertex was possible
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