Benchmarking the ORCA PT-2 Boson Sampler using Minimum Dominating Set Problems
This work provides an early benchmark for a specific photonic quantum computing device (ORCA PT-2) against classical algorithms for combinatorial optimization problems, indicating its current limitations.
This paper evaluates ORCA Computing's PT-2 boson sampler using a gradient-free variational algorithm to solve minimum dominating set problems. The boson sampler, tested in single- and double-loop configurations, was outperformed by classical methods under the experimental parameters, with the authors hypothesizing this is due to insufficient samples and iterations.
We use boson sampling as part of a gradient-free variational algorithm (the Binary Bosonic Solver) to solve a minimum dominating set problem and compare these results to a number of exact and heuristic classical algorithms. The boson sampling has been performed on the physical PT-2 time-bin interferometer from ORCA Computing. The PT-2 device has been tested here using both a single- and double-loop configuration and the results are compared based on the best found solution and the overall run time. With the parameters used in this experiment, the boson sampler is outperformed by the classical methods, but we hypothesise that this is due to insufficient samples and iterations. We classically simulate boson sampling in a single-loop configuration to break down the runtime for individual algorithmic components, allowing for estimates of when boson sampling may outperform classical methods. This study recommends a watching brief on boson sampling as the complexity of the interferometer is improved and the loss in the hardware is reduced allowing for better performance from the associated algorithms.