Deshpande Abhinav, Mehta Arthur, Vincent Trevor, Quesada Nicolás, Hinsche Marcel, Ioannou Marios, Madsen Lars, Lavoie Jonathan, Qi Haoyu, Eisert Jens, Hangleiter Dominik, Fefferman Bill, Dhand Ish
Joint Center for Quantum Information and Computer Science, NIST/University of Maryland, College Park, MD 20742, USA.
Joint Quantum Institute, NIST/University of Maryland, College Park, MD 20742, USA.
Sci Adv. 2022 Jan 7;8(1):eabi7894. doi: 10.1126/sciadv.abi7894. Epub 2022 Jan 5.
Photonics is a promising platform for demonstrating a quantum computational advantage (QCA) by outperforming the most powerful classical supercomputers on a well-defined computational task. Despite this promise, existing proposals and demonstrations face challenges. Experimentally, current implementations of Gaussian boson sampling (GBS) lack programmability or have prohibitive loss rates. Theoretically, there is a comparative lack of rigorous evidence for the classical hardness of GBS. In this work, we make progress in improving both the theoretical evidence and experimental prospects. We provide evidence for the hardness of GBS, comparable to the strongest theoretical proposals for QCA. We also propose a QCA architecture we call high-dimensional GBS, which is programmable and can be implemented with low loss using few optical components. We show that particular algorithms for simulating GBS are outperformed by high-dimensional GBS experiments at modest system sizes. This work thus opens the path to demonstrating QCA with programmable photonic processors.
光子学是一个很有前景的平台，通过在明确的计算任务上超越最强大的经典超级计算机来展示量子计算优势（QCA）。尽管有此前景，但现有方案和演示面临挑战。在实验方面，高斯玻色子采样（GBS）的当前实现缺乏可编程性，或者具有高得令人望而却步的损耗率。在理论方面，相对缺乏关于GBS经典难度的严格证据。在这项工作中，我们在改善理论证据和实验前景两方面都取得了进展。我们提供了与QCA最有力的理论方案相当的关于GBS难度的证据。我们还提出了一种称为高维GBS的QCA架构，它是可编程的，并且可以使用很少的光学组件以低损耗实现。我们表明，在适度的系统规模下，用于模拟GBS的特定算法在高维GBS实验面前表现不佳。因此，这项工作为用可编程光子处理器展示QCA开辟了道路。
