4,098 research outputs found

    VI Workshop on Computational Data Analysis and Numerical Methods: Book of Abstracts

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    The VI Workshop on Computational Data Analysis and Numerical Methods (WCDANM) is going to be held on June 27-29, 2019, in the Department of Mathematics of the University of Beira Interior (UBI), Covilhã, Portugal and it is a unique opportunity to disseminate scientific research related to the areas of Mathematics in general, with particular relevance to the areas of Computational Data Analysis and Numerical Methods in theoretical and/or practical field, using new techniques, giving especial emphasis to applications in Medicine, Biology, Biotechnology, Engineering, Industry, Environmental Sciences, Finance, Insurance, Management and Administration. The meeting will provide a forum for discussion and debate of ideas with interest to the scientific community in general. With this meeting new scientific collaborations among colleagues, namely new collaborations in Masters and PhD projects are expected. The event is open to the entire scientific community (with or without communication/poster)

    Nash embedding and equilibrium in pure quantum states

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    With respect to probabilistic mixtures of the strategies in non-cooperative games, quantum game theory provides guarantee of fixed-point stability, the so-called Nash equilibrium. This permits players to choose mixed quantum strategies that prepare mixed quantum states optimally under constraints. In this letter, we show that fixed-point stability of Nash equilibrium can also be guaranteed for pure quantum strategies via an application of the Nash embedding theorem, permitting players to prepare pure quantum states optimally under constraints.Comment: 7 pages, 1 figure. arXiv admin note: text overlap with arXiv:1609.0836

    Learning Convex Partitions and Computing Game-theoretic Equilibria from Best Response Queries

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    Suppose that an mm-simplex is partitioned into nn convex regions having disjoint interiors and distinct labels, and we may learn the label of any point by querying it. The learning objective is to know, for any point in the simplex, a label that occurs within some distance ϵ\epsilon from that point. We present two algorithms for this task: Constant-Dimension Generalised Binary Search (CD-GBS), which for constant mm uses poly(n,log(1ϵ))poly(n, \log \left( \frac{1}{\epsilon} \right)) queries, and Constant-Region Generalised Binary Search (CR-GBS), which uses CD-GBS as a subroutine and for constant nn uses poly(m,log(1ϵ))poly(m, \log \left( \frac{1}{\epsilon} \right)) queries. We show via Kakutani's fixed-point theorem that these algorithms provide bounds on the best-response query complexity of computing approximate well-supported equilibria of bimatrix games in which one of the players has a constant number of pure strategies. We also partially extend our results to games with multiple players, establishing further query complexity bounds for computing approximate well-supported equilibria in this setting.Comment: 38 pages, 7 figures, second version strengthens lower bound in Theorem 6, adds footnotes with additional comments and fixes typo

    Noise in Quantum and Classical Computation & Non-locality

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    Quantum computers seem to have capabilities which go beyond those of classical computers. A particular example which is important for cryptography is that quantum computers are able to factor numbers much faster than what seems possible on classical machines. In order to actually build quantum computers it is necessary to build sufficiently accurate hardware, which is a big challenge. In part 1 of this thesis we prove lower bounds on the accuracy of the hardware needed to do quantum computation. We also present a similar result for classical computers. One resource that quantum computers have but classical computers do not have is entanglement. In Part 2 of this thesis we study certain general aspects of entanglement in terms of quantum XOR games and non-locality
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