  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.
