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Applications of Near-Term Photonic Quantum Computers: Software and Algorithms
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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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Exact simulation of Gaussian Boson Sampling in polynomial space and exponential time
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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