Benchmarking ORCA PT-1 Boson Sampler in Simulation

TL;DR

This paper benchmarks the ORCA PT-1 Boson Sampler's time-bin interferometer in simulation, demonstrating its potential to solve moderately sized combinatorial problems with performance comparable to classical algorithms, despite current scaling limitations.

Contribution

It introduces a simulation-based benchmarking of the ORCA TBI boson sampling device on a dominating set problem, highlighting its capabilities and limitations.

Findings

ORCA TBI can solve problems with n<250 nodes.

Performance is comparable to classical linear programming and greedy algorithms.

Scaling is worse than classical methods in simulation, but may improve in physical devices.

Abstract

Boson Sampling, a non-universal computing paradigm, has resulted in impressive claims of quantum supremacy. ORCA Computing have developed a time-bin interferometer (TBI) that claims to use the principles of boson sampling to solve a number of computational problems including optimisation and generative adversarial networks. We solve a dominating set problem with a surveillance use case on the ORCA TBI simulator to benchmark the use of these devices against classical algorithms. Simulation has been used to consider the optimal performance of the computing paradigm without having to factor in noise, errors and scaling limitations. We show that the ORCA TBI is capable of solving moderately sized (n<250) dominating set problems with comparable success to linear programming and greedy methods. Wall clock timing shows that the simulator has worse scaling than the classical methods, but this is unlikely to carry over to the physical device where the outputs are measured rather than calculated.