近日，法国Quandela公司的Niccolo Somaschi&Jean Senellart及其研究团队取得一项新进展。经过不懈努力，他们成功开发出一个多功能的单光子量子计算平台。相关研究成果已于2024年3月26日在国际知名学术期刊《自然—光子学》上发表。

该研究团队提出一个基于单光子的云可访问的通用量子计算原型。该设备包括一个高效的量子点单光子源，在可重构芯片上馈送通用线性光网络，硬件误差由机器学习的平移过程补偿。全面的软件栈设计使得用户能够远程控制设备，通过逻辑门或直接光子操作执行计算任务。在基于门的计算方面，研究人员对一、二和三量子比特门进行了基准测试，并达到了先进的保真度水平，分别为99.6±0.1%、93.8±0.6%和86±1.2%。

此外，他们还实现了一个变分量子特征求解器，并成功应用于氢分子能级的化学精度计算。在光子原生计算领域，他们利用基于三光子的量子神经网络实现了分类器算法，并展示了在通用可重构集成电路上的六光子玻色子采样演示。最后，他们还报道了预示三光子纠缠产生的成果，这标志着基于测量的量子计算领域取得了关键性进展。

据悉，量子计算旨在借助量子现象来有效地执行即使是最强大的经典超级计算机也无法实现的计算。光子量子计算具有显著优势，包括低退相干性、在适度低温下即可进行信息处理，以及能够与经典网络和量子网络进行本地集成。目前，光量子计算演示已利用专门硬件成功实现特定任务，尤其是高斯玻色子采样，这使得量子计算优势得以实现。

附：英文原文

Title: A versatile single-photon-based quantum computing platform

Author: Maring, Nicolas, Fyrillas, Andreas, Pont, Mathias, Ivanov, Edouard, Stepanov, Petr, Margaria, Nico, Hease, William, Pishchagin, Anton, Lematre, Aristide, Sagnes, Isabelle, Au, Thi Huong, Boissier, Sbastien, Bertasi, Eric, Baert, Aurlien, Valdivia, Mario, Billard, Marie, Acar, Ozan, Brieussel, Alexandre, Mezher, Rawad, Wein, Stephen C., Salavrakos, Alexia, Sinnott, Patrick, Fioretto, Dario A., Emeriau, Pierre-Emmanuel, Belabas, Nadia, Mansfield, Shane, Senellart, Pascale, Senellart, Jean, Somaschi, Niccolo

Issue&Volume: 2024-03-26

Abstract: Quantum computing aims at exploiting quantum phenomena to efficiently perform computations that are unfeasible even for the most powerful classical supercomputers. Among the promising technological approaches, photonic quantum computing offers the advantages of low decoherence, information processing with modest cryogenic requirements, and native integration with classical and quantum networks. So far, quantum computing demonstrations with light have implemented specific tasks with specialized hardware, notably Gaussian boson sampling, which permits the quantum computational advantage to be realized. Here we report a cloud-accessible versatile quantum computing prototype based on single photons. The device comprises a high-efficiency quantum-dot single-photon source feeding a universal linear optical network on a reconfigurable chip for which hardware errors are compensated by a machine-learned transpilation process. Our full software stack allows remote control of the device to perform computations via logic gates or direct photonic operations. For gate-based computation, we benchmark one-, two- and three-qubit gates with state-of-the art fidelities of 99.6±0.1%, 93.8±0.6% and 86±1.2%, respectively. We also implement a variational quantum eigensolver, which we use to calculate the energy levels of the hydrogen molecule with chemical accuracy. For photon native computation, we implement a classifier algorithm using a three-photon-based quantum neural network and report a six-photon boson sampling demonstration on a universal reconfigurable integrated circuit. Finally, we report on a heralded three-photon entanglement generation, a key milestone toward measurement-based quantum computing.

DOI: 10.1038/s41566-024-01403-4

Source: https://www.nature.com/articles/s41566-024-01403-4