8,852 research outputs found

    Computing Bounds for Counter Automata

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    Qualitative formal verification, that seeks Boolean answers about the behavior of a system, is often insufficient for practical purposes. Observing quantitative information is of greater interest, e.g. for the calibration of a battery or a real-time scheduler. Historically, the focus has been on quantities in continuous domain, but recent years showed a renewed interest for discrete quantitative domains. Counter Automata (CA) is a quantitative extension of classical omega-automata. Recently a nice theory has been developed for them that extends the qualitative setting, with counterparts in terms of logics, automata and algebraic structure. We propose an adaptation, with plenty of practical applications,  of this formalism to express properties over discrete quantitative domains. The behavior of a Counter Automaton defines a function from infinite words to integers. Finding the bounds of such a function over a given set of words can be seen as an extension of qualitative universal and existential model-checking. Although the problem of determining whether such bounds are finite have already been addressed, efficient algorithms to compute their exact values still lack. We propose an non-naive method for the computation of the exact values of these bounds. It relies on a generalization of the emptiness problem of omega-automata. To solve this generalized emptiness problem, we propose an algorithm that extends emptiness check algorithms based on SCC enumeration.

    Quantum computation with devices whose contents are never read

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    In classical computation, a "write-only memory" (WOM) is little more than an oxymoron, and the addition of WOM to a (deterministic or probabilistic) classical computer brings no advantage. We prove that quantum computers that are augmented with WOM can solve problems that neither a classical computer with WOM nor a quantum computer without WOM can solve, when all other resource bounds are equal. We focus on realtime quantum finite automata, and examine the increase in their power effected by the addition of WOMs with different access modes and capacities. Some problems that are unsolvable by two-way probabilistic Turing machines using sublogarithmic amounts of read/write memory are shown to be solvable by these enhanced automata.Comment: 32 pages, a preliminary version of this work was presented in the 9th International Conference on Unconventional Computation (UC2010

    Beyond Language Equivalence on Visibly Pushdown Automata

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    We study (bi)simulation-like preorder/equivalence checking on the class of visibly pushdown automata and its natural subclasses visibly BPA (Basic Process Algebra) and visibly one-counter automata. We describe generic methods for proving complexity upper and lower bounds for a number of studied preorders and equivalences like simulation, completed simulation, ready simulation, 2-nested simulation preorders/equivalences and bisimulation equivalence. Our main results are that all the mentioned equivalences and preorders are EXPTIME-complete on visibly pushdown automata, PSPACE-complete on visibly one-counter automata and P-complete on visibly BPA. Our PSPACE lower bound for visibly one-counter automata improves also the previously known DP-hardness results for ordinary one-counter automata and one-counter nets. Finally, we study regularity checking problems for visibly pushdown automata and show that they can be decided in polynomial time.Comment: Final version of paper, accepted by LMC

    Deterministic parallel algorithms for bilinear objective functions

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    Many randomized algorithms can be derandomized efficiently using either the method of conditional expectations or probability spaces with low independence. A series of papers, beginning with work by Luby (1988), showed that in many cases these techniques can be combined to give deterministic parallel (NC) algorithms for a variety of combinatorial optimization problems, with low time- and processor-complexity. We extend and generalize a technique of Luby for efficiently handling bilinear objective functions. One noteworthy application is an NC algorithm for maximal independent set. On a graph GG with mm edges and nn vertices, this takes O~(log2n)\tilde O(\log^2 n) time and (m+n)no(1)(m + n) n^{o(1)} processors, nearly matching the best randomized parallel algorithms. Other applications include reduced processor counts for algorithms of Berger (1997) for maximum acyclic subgraph and Gale-Berlekamp switching games. This bilinear factorization also gives better algorithms for problems involving discrepancy. An important application of this is to automata-fooling probability spaces, which are the basis of a notable derandomization technique of Sivakumar (2002). Our method leads to large reduction in processor complexity for a number of derandomization algorithms based on automata-fooling, including set discrepancy and the Johnson-Lindenstrauss Lemma
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