Benchmarking ORCA PT-1 Boson Sampler in Simulation

Researchers demonstrated a time-bin interferometer, simulating a boson sampling approach, successfully solved moderately sized dominating set problems (n<250) with performance comparable to established classical algorithms like linear programming and greedy methods. Simulations suggest the physical device may offer improved scaling characteristics over classical computation.

The potential of photonic quantum computing rests on the ability to perform calculations intractable for conventional computers. A recent approach, boson sampling, utilises the probabilistic nature of photons to explore computational spaces beyond the reach of classical algorithms. Researchers at the University of York, Jessica Park, Susan Stepney, and Irene D’Amico, investigate the performance of a specific boson sampling architecture – the ORCA time-bin interferometer – through simulation. Their work, detailed in “Benchmarking ORCA PT-1 Boson Sampler in Simulation”, assesses the device’s capacity to solve a practical optimisation problem – finding a dominating set with applications in surveillance – and compares its simulated performance against established classical algorithms. The study highlights the potential, and current limitations, of this emerging quantum paradigm.

Benchmarking a Time-Bin Interferometer for Computational Task

Recent advances in quantum computing are driving exploration of novel computational paradigms. Boson sampling, a non-universal model leveraging quantum interference, presents a potential alternative to classical computation. This study benchmarks the ORCA time-bin interferometer (TBI) – a platform for boson sampling – against established classical algorithms, focusing on moderately sized minimum dominating set problems. These problems have practical applications in areas such as surveillance network optimisation.

The investigation centres on the principle of boson sampling, where indistinguishable photons are processed through an interferometer. The ORCA PT-1, utilising a time-bin encoding scheme and loop-based architecture, served as the testbed. The minimum dominating set problem was selected as a benchmark due to its relevance and suitability for comparative analysis with both quantum and classical methods.

Researchers employed simulations to explore optimal performance, isolating the computational core from physical device limitations like noise and error. This controlled environment allowed for a focused assessment of the boson sampling approach.

Results indicate that, within the simulated environment, the ORCA PT-1 achieves comparable success rates to classical algorithms in solving moderately sized (n<250) dominating set problems. This validates the potential of boson sampling as a computational model. However, the computational scaling of the TBI simulator exhibited inferior performance compared to the classical algorithms tested. This discrepancy likely arises from the simulation’s reliance on calculating outputs, rather than directly measuring them as would occur on a physical device.

Future research must prioritise validating these simulated results on the physical ORCA PT-1 device. Investigating the impact of inherent noise and errors on the TBI’s performance is crucial, alongside developing strategies for mitigation. Expanding the scope of benchmark problems to include other computationally challenging tasks, such as the maximum cut problem (Marcus & Minc, 1965), will further assess the TBI’s versatility.

Researchers are actively exploring algorithms and techniques to improve TBI performance, including the application of machine learning to optimise quantum interference. They are also developing methods for characterising and mitigating noise and errors, and investigating error correction codes to protect quantum information.

The study adheres to the principles of open science, with data and code publicly available to the research community. This commitment to collaboration and knowledge sharing aims to accelerate the development of quantum computing. The work builds upon decades of research in quantum optics and computer science, representing a step forward in the development of boson sampling.