67 research outputs found

    Two Results about Quantum Messages

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    We show two results about the relationship between quantum and classical messages. Our first contribution is to show how to replace a quantum message in a one-way communication protocol by a deterministic message, establishing that for all partial Boolean functions f:{0,1}n×{0,1}m{0,1}f:\{0,1\}^n\times\{0,1\}^m\to\{0,1\} we have DAB(f)O(QAB,(f)m)D^{A\to B}(f)\leq O(Q^{A\to B,*}(f)\cdot m). This bound was previously known for total functions, while for partial functions this improves on results by Aaronson, in which either a log-factor on the right hand is present, or the left hand side is RAB(f)R^{A\to B}(f), and in which also no entanglement is allowed. In our second contribution we investigate the power of quantum proofs over classical proofs. We give the first example of a scenario, where quantum proofs lead to exponential savings in computing a Boolean function. The previously only known separation between the power of quantum and classical proofs is in a setting where the input is also quantum. We exhibit a partial Boolean function ff, such that there is a one-way quantum communication protocol receiving a quantum proof (i.e., a protocol of type QMA) that has cost O(logn)O(\log n) for ff, whereas every one-way quantum protocol for ff receiving a classical proof (protocol of type QCMA) requires communication Ω(n/logn)\Omega(\sqrt n/\log n)

    The Partition Bound for Classical Communication Complexity and Query Complexity

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    We describe new lower bounds for randomized communication complexity and query complexity which we call the partition bounds. They are expressed as the optimum value of linear programs. For communication complexity we show that the partition bound is stronger than both the rectangle/corruption bound and the \gamma_2/generalized discrepancy bounds. In the model of query complexity we show that the partition bound is stronger than the approximate polynomial degree and classical adversary bounds. We also exhibit an example where the partition bound is quadratically larger than polynomial degree and classical adversary bounds.Comment: 28 pages, ver. 2, added conten

    New Bounds for the Garden-Hose Model

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    We show new results about the garden-hose model. Our main results include improved lower bounds based on non-deterministic communication complexity (leading to the previously unknown Θ(n)\Theta(n) bounds for Inner Product mod 2 and Disjointness), as well as an O(nlog3n)O(n\cdot \log^3 n) upper bound for the Distributed Majority function (previously conjectured to have quadratic complexity). We show an efficient simulation of formulae made of AND, OR, XOR gates in the garden-hose model, which implies that lower bounds on the garden-hose complexity GH(f)GH(f) of the order Ω(n2+ϵ)\Omega(n^{2+\epsilon}) will be hard to obtain for explicit functions. Furthermore we study a time-bounded variant of the model, in which even modest savings in time can lead to exponential lower bounds on the size of garden-hose protocols.Comment: In FSTTCS 201

    The Complexity of Quantum Disjointness

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    We introduce the communication problem QNDISJ, short for Quantum (Unique) Non-Disjointness, and study its complexity under different modes of communication complexity. The main motivation for the problem is that it is a candidate for the separation of the quantum communication complexity classes QMA and QCMA. The problem generalizes the Vector-in-Subspace and Non-Disjointness problems. We give tight bounds for the QMA, quantum, randomized communication complexities of the problem. We show polynomially related upper and lower bounds for the MA complexity. We also show an upper bound for QCMA protocols, and show that the bound is tight for a natural class of QCMA protocols for the problem. The latter lower bound is based on a geometric lemma, that states that every subset of the n-dimensional sphere of measure 2^-p must contain an ortho-normal set of points of size Omega(n/p). We also study a "small-spaces" version of the problem, and give upper and lower bounds for its randomized complexity that show that the QNDISJ problem is harder than Non-disjointness for randomized protocols. Interestingly, for quantum modes the complexity depends only on the dimension of the smaller space, whereas for classical modes the dimension of the larger space matters

    Correlation in Hard Distributions in Communication Complexity

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    We study the effect that the amount of correlation in a bipartite distribution has on the communication complexity of a problem under that distribution. We introduce a new family of complexity measures that interpolates between the two previously studied extreme cases: the (standard) randomised communication complexity and the case of distributional complexity under product distributions. We give a tight characterisation of the randomised complexity of Disjointness under distributions with mutual information kk, showing that it is Θ(n(k+1))\Theta(\sqrt{n(k+1)}) for all 0kn0\leq k\leq n. This smoothly interpolates between the lower bounds of Babai, Frankl and Simon for the product distribution case (k=0k=0), and the bound of Razborov for the randomised case. The upper bounds improve and generalise what was known for product distributions, and imply that any tight bound for Disjointness needs Ω(n)\Omega(n) bits of mutual information in the corresponding distribution. We study the same question in the distributional quantum setting, and show a lower bound of Ω((n(k+1))1/4)\Omega((n(k+1))^{1/4}), and an upper bound, matching up to a logarithmic factor. We show that there are total Boolean functions fdf_d on 2n2n inputs that have distributional communication complexity O(logn)O(\log n) under all distributions of information up to o(n)o(n), while the (interactive) distributional complexity maximised over all distributions is Θ(logd)\Theta(\log d) for 6nd2n/1006n\leq d\leq 2^{n/100}. We show that in the setting of one-way communication under product distributions, the dependence of communication cost on the allowed error ϵ\epsilon is multiplicative in log(1/ϵ)\log(1/\epsilon) -- the previous upper bounds had the dependence of more than 1/ϵ1/\epsilon
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