A Statistical Benchmark for BosonSampling
Mattia Walschaers, Jack Kuipers, Juan-Diego Urbina, Klaus Mayer, Malte, C. Tichy, Klaus Richter, Andreas Buchleitner

TL;DR
This paper introduces a statistical benchmark for BosonSampling experiments, enabling verification that experimental data genuinely reflects many-boson interference rather than other particle types or noise, thus supporting quantum advantage claims.
Contribution
It proposes a new, classically computable statistical signature to certify BosonSampling experiments as genuine many-boson interference.
Findings
The benchmark distinguishes bosons from fermions and distinguishable particles.
It provides a practical method for experimental validation of BosonSampling.
The approach enhances confidence in quantum computational supremacy demonstrations.
Abstract
Computing the state of a quantum mechanical many-body system composed of indistinguishable particles distributed over a multitude of modes is one of the paradigmatic test cases of computational complexity theory: Beyond well-understood quantum statistical effects, the coherent superposition of many-particle amplitudes rapidly overburdens classical computing devices - essentially by creating extremely complicated interference patterns, which also challenge experimental resolution. With the advent of controlled many-particle interference experiments, optical set-ups that can efficiently probe many-boson wave functions - baptised BosonSamplers - have therefore been proposed as efficient quantum simulators which outperform any classical computing device, and thereby challenge the extended Church-Turing thesis, one of the fundamental dogmas of computer science. However, as in all…
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