High performance Boson sampling simulation via data-flow engines

Abstract

Boson sampling (BS) is viewed to be an accessible quantum computing paradigm to demonstrate computational advantage compared to classical computers. In this context, the evolution of permanent calculation algorithms attracts a significant attention as the simulation of BS experiments involves the evaluation of vast number of permanents. For this reason, we generalize the Balasubramanian–Bax–Franklin–Glynn permanent formula, aiming to efficiently integrate it into the BS strategy of Clifford and Clifford (2020 Faster classical boson sampling). A reduction in simulation complexity originating from multiplicities in photon occupation was achieved through the incorporation of a n-ary Gray code ordering of the addends during the permanent evaluation. Implementing the devised algorithm on FPGA-based data-flow engines, we leverage the resulting tool to accelerate boson sampling simulations for up to 40 photons. Drawing samples from a 60-mode interferometer, the achieved rate averages around 80 s per sample, employing 4 FPGA chips. The developed design facilitates the simulation of both ideal and lossy boson sampling experiments.