743 research outputs found

    Boson Sampling as Canonical Transformation: A semiclassical approach in Fock space

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    We show that a theory of complex scattering between many-body (Fock) states can be constructed such that its classical limit is a canonical transformation thus encoding quantum interference in the semiclassical form of the associated unitary operator. Based on this idea, we study the different coherent effects expected under different choices of the many-body states and provide different representations of the associated transition probabilities. In this way, we derive exact relations and representations of the scattering process that can be used to attack timely problems related with Boson Sampling.Comment: submitted to Ann. Phy

    The Classical Complexity of Boson Sampling

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    We study the classical complexity of the exact Boson Sampling problem where the objective is to produce provably correct random samples from a particular quantum mechanical distribution. The computational framework was proposed by Aaronson and Arkhipov in 2011 as an attainable demonstration of `quantum supremacy', that is a practical quantum computing experiment able to produce output at a speed beyond the reach of classical (that is non-quantum) computer hardware. Since its introduction Boson Sampling has been the subject of intense international research in the world of quantum computing. On the face of it, the problem is challenging for classical computation. Aaronson and Arkhipov show that exact Boson Sampling is not efficiently solvable by a classical computer unless P#P=BPPNPP^{\#P} = BPP^{NP} and the polynomial hierarchy collapses to the third level. The fastest known exact classical algorithm for the standard Boson Sampling problem takes O((m+n1n)n2n)O({m + n -1 \choose n} n 2^n ) time to produce samples for a system with input size nn and mm output modes, making it infeasible for anything but the smallest values of nn and mm. We give an algorithm that is much faster, running in O(n2n+poly(m,n))O(n 2^n + \operatorname{poly}(m,n)) time and O(m)O(m) additional space. The algorithm is simple to implement and has low constant factor overheads. As a consequence our classical algorithm is able to solve the exact Boson Sampling problem for system sizes far beyond current photonic quantum computing experimentation, thereby significantly reducing the likelihood of achieving near-term quantum supremacy in the context of Boson Sampling.Comment: 15 pages. To appear in SODA '1

    Approximating the Permanent with Fractional Belief Propagation

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    We discuss schemes for exact and approximate computations of permanents, and compare them with each other. Specifically, we analyze the Belief Propagation (BP) approach and its Fractional Belief Propagation (FBP) generalization for computing the permanent of a non-negative matrix. Known bounds and conjectures are verified in experiments, and some new theoretical relations, bounds and conjectures are proposed. The Fractional Free Energy (FFE) functional is parameterized by a scalar parameter γ[1;1]\gamma\in[-1;1], where γ=1\gamma=-1 corresponds to the BP limit and γ=1\gamma=1 corresponds to the exclusion principle (but ignoring perfect matching constraints) Mean-Field (MF) limit. FFE shows monotonicity and continuity with respect to γ\gamma. For every non-negative matrix, we define its special value γ[1;0]\gamma_*\in[-1;0] to be the γ\gamma for which the minimum of the γ\gamma-parameterized FFE functional is equal to the permanent of the matrix, where the lower and upper bounds of the γ\gamma-interval corresponds to respective bounds for the permanent. Our experimental analysis suggests that the distribution of γ\gamma_* varies for different ensembles but γ\gamma_* always lies within the [1;1/2][-1;-1/2] interval. Moreover, for all ensembles considered the behavior of γ\gamma_* is highly distinctive, offering an emprirical practical guidance for estimating permanents of non-negative matrices via the FFE approach.Comment: 42 pages, 14 figure

    Bounds on the permanent and some applications

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    We give new lower and upper bounds on the permanent of a doubly stochastic matrix. Combined with previous work, this improves on the deterministic approximation factor for the permanent. We also give a combinatorial application of the lower bound, proving S. Friedland's "Asymptotic Lower Matching Conjecture" for the monomer-dimer problem
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