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Applications of Near-Term Photonic Quantum Computers: Software and Algorithms

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arxiv 1912.07634 v1 pith:SE3G263D submitted 2019-12-16 quant-ph physics.comp-ph

classification quant-phphysics.comp-ph
keywords algorithmsapplicationsquantumphotonicsoftwarecodecomputingimplement
verification ladder T0 review T1 audit T2 compute T3 formal

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Gaussian Boson Sampling (GBS) is a near-term platform for photonic quantum computing. Recent efforts have led to the discovery of GBS algorithms with applications to graph-based problems, point processes, and molecular vibronic spectra in chemistry. The development of dedicated quantum software is a key enabler in permitting users to program devices and implement algorithms. In this work, we introduce a new applications layer for the Strawberry Fields photonic quantum computing library. The applications layer provides users with the necessary tools to design and implement algorithms using GBS with only a few lines of code. This paper serves a dual role as an introduction to the software, supported with example code, and also a review of the current state of the art in GBS algorithms.

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  1. Exact simulation of Gaussian Boson Sampling in polynomial space and exponential time

    quant-ph 2019-08 conditional novelty 7.0 of 10

    A chain-rule algorithm samples each mode of a Gaussian Boson Sampler sequentially, giving exact simulation in polynomial space and time exponential in the detected photon number.

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