Simulating and assessing boson sampling experiments with phase-space representations.

The search for new, application-specific quantum computers designed to outperform any classical computer is driven by the ending of Moore's law and the quantum advantages potentially obtainable. Photonic networks are promising examples, with experimental demonstrations and potential for obtaining a quantum computer to solve problems believed classically impossible. This introduces a challenge: how does one design or understand such photonic networks? One must be able to calculate observables using general methods capable of treating arbitrary inputs, dissipation and noise. We develop novel complex phase-space software for simulating these photonic networks, and apply this to boson sampling experiments. Our techniques give sampling errors orders of magnitude lower than experimental correlation measurements for the same number of samples. We show that these techniques remove systematic errors in previous algorithms for estimating correlations, with large improvements in errors in some cases. In addition, we obtain a scalable channel-combination strategy for assessment of boson sampling devices.