近日，法国初创公司Quandela的Giacomo Franceschetto及其研究团队取得一项新进展。经过不懈努力，他们在单光子量子计算机上实现了量子投影模拟的演示。相关研究成果已于2024年12月17日在国际知名学术期刊《物理评论A》上发表。

在这项工作中，研究人员在Quandela公司基于单光子的量子计算机Ascella上实现了该算法。研究人员重点演示了一个测试任务，以凸显量子智能体相对于经典智能体的潜力。

据悉，变分量子算法在有效运行于含噪中等规模量子器件上展现出潜力。近期，一种结合线性光学干涉仪和经典学习模型（即投影模拟，PS）的强化学习变分方法被提出。投影模拟是强化学习中的一种决策工具，其经典表示形式为在描述智能体记忆的图上进行随机游走。在该方法的光量子版本中，利用单光子在由可调分束器和相移器构成的网格上进行量子游走来选择动作。

附：英文原文

Title: Demonstration of quantum projective simulation on a single-photon-based quantum computer

Author: Giacomo Franceschetto, Arno Ricou

Issue&Volume: 2024/12/17

Abstract: Variational quantum algorithms show potential in effectively operating on noisy intermediate-scale quantum devices. A variational approach to reinforcement learning has been recently proposed, incorporating linear-optical interferometers and a classical learning model known as projective simulation (PS). PS is a decision-making tool for reinforcement learning and can be classically represented as a random walk on a graph that describes the agent's memory. In its optical quantum version, this approach utilizes quantum walks of single photons on a mesh of tunable beamsplitters and phase shifters to select actions. In this work, we present the implementation of this algorithm on Ascella, a single-photon-based quantum computer from Quandela. The focus is drawn on solving a test bed task to showcase the potential of the quantum agent with respect to the classical agent.

DOI: 10.1103/PhysRevA.110.062613

Source: https://journals.aps.org/pra/abstract/10.1103/PhysRevA.110.062613