Generation and sampling of quantum states of light in a silicon chip (1812.03158v1)

Abstract: Implementing large instances of quantum algorithms requires the processing of many quantum information carriers in a hardware platform that supports the integration of different components. While established semiconductor fabrication processes can integrate many photonic components, the generation and algorithmic processing of many photons has been a bottleneck in integrated photonics. Here we report the on-chip generation and processing of quantum states of light with up to eight photons in quantum sampling algorithms. Switching between different optical pumping regimes, we implement the Scattershot, Gaussian and standard boson sampling protocols in the same silicon chip, which integrates linear and nonlinear photonic circuitry. We use these results to benchmark a quantum algorithm for calculating molecular vibronic spectra. Our techniques can be readily scaled for the on-chip implementation of specialised quantum algorithms with tens of photons, pointing the way to efficiency advantages over conventional computers.

Quantum State Generation and Sampling in Integrated Photonics

The paper focuses on the development of integrated quantum photonics techniques for generating and sampling quantum states of light, particularly boson sampling, a challenging problem for classical computation. The authors report generating and processing quantum states with up to eight photons on a silicon chip, using both Scattershot Boson Sampling (SBS) and Gaussian Boson Sampling (GBS) protocols.

Overview

Integrated quantum photonics leverages established semiconductor fabrication methods, providing a platform for integrating multiple photonic components necessary for practical quantum computing. Despite advances in component integration, generating and processing several photons has remained a bottleneck. This research addresses this issue using SBS and GBS protocols in a silicon photonic chip, which combines linear and nonlinear photonic circuitry.

Key Results

The paper highlights results from implementing SBS, GBS, and standard boson sampling in a single silicon chip containing four spontaneous four-wave mixing (SFWM) sources:

1. Scattershot Boson Sampling: By using a single wavelength pumping scheme, the authors achieve a mean fidelity of 92% with the theoretical distribution for six-photon (three-pair) events. The photon generation rate improved combinatorially, with an enhancement factor of approximately $\binom{4}{n}$ for 1 to 3 pairs compared to standard boson sampling.
2. Gaussian Boson Sampling: Implementing a dual-wavelength pumping scheme led to observing up to four signal photons at a rate of $1.1\,\text{Hz}$, achieving an 87% fidelity with theoretical predictions for four-photon events. The SBS protocol's output statistical distribution was validated to be distinct from that of distinguishable photons by Bayesian analysis.
3. Practical Applications: The results were leveraged to benchmark a quantum algorithm for calculating molecular vibronic spectra, suggesting the scalability of the technique to process results beyond the computational capability of classical computers.

Implications and Future Directions

The paper underscores the potential for integrated photonics to handle specialized quantum algorithms efficiently, suggesting silicon photonics as a viable pathway towards practical quantum advantage. Several implications emerge from this work:

• Scalability: The experimental results with integrated platforms hint at scalable designs that may outperform classical systems in calculating molecular transitions and simulating quantum dynamics.
• Photon Rate and Efficiency Enhancements: The report details combinatorial enhancements of photon generation rates through the SBS and GBS protocols, opening pathways to improve the efficiency of quantum algorithms.
• Beyond Conventional Computing: The integration of many photonic components presents a pathway to documents exhibiting computational advantages.

Future work might focus on integrating larger arrays of detectors, improving SFWM source performance, and minimizing loss in photonic circuits to push the boundaries of integrated quantum photonic experiments further. Developing techniques to harness increased photon rates and applying error-correction strategies will be crucial to scaling up these experiments.

Conclusion

This paper contributes significantly to the field of quantum photonics, demonstrating the feasibility of scalable integrated photonic platforms for performing complex quantum experiments. The methodology and results presented can help guide the development of photonic quantum computing systems capable of solving problems infeasible for classical computers.