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Nature Photonics

A versatile single-photon-based quantum computing platform

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

Published Mar 26, 2024• 254 citations
PDF (CC BY)Publisher

Abstract

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

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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.
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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. To date, quantum computing demonstrations with light have implemented specific tasks with specialized hardware, notably Gaussian Boson Sampling which permitted quantum computational advantage to be reached. Here we report a first user-ready general-purpose quantum computing prototype based on single photons.
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Abstract A quantum computer attains computational advantage when outperforming the best classical computers running the best-known algorithms on well-defined tasks. No photonic machine offering programmability over all its quantum gates has demonstrated quantum computational advantage: previous machines 1,2 were largely restricted to static gate sequences. Earlier photonic demonstrations were also vulnerable to spoofing 3 , in which classical heuristics produce samples, without direct simulation, lying closer to the ideal distribution than do samples from the quantum hardware. Here we report quantum computational advantage using Borealis, a photonic processor offering dynamic programmability on all gates implemented. We carry out Gaussian boson sampling 4 (GBS) on 216 squeezed modes entangled with three-dimensional connectivity 5 , using a time-multiplexed and photon-number-resolving architecture. On average, it would take more than 9,000 years for the best available algorithms and supercomputers to produce, using exact methods, a single sample from the programmed distribution, whereas Borealis requires only 36 μs. This runtime advantage is over 50 million times as extreme as that reported from earlier photonic machines. Ours constitutes a very large GBS experiment, registering events with up to 219 photons and a mean photon number of 125. This work is a critical milestone on the path to a practical quantum computer, validating key technological features of photonics as a platform for this goal.
Quantum computing has changed the paradigm of computer science, where quantum technologies have promised to outperform classical ones. Such an advantage was only demonstrated for tasks with no application or out of reach for the state-of-the-art quantum technologies. In this context, a promising strategy to find practical use of quantum computers exploits hybrid models, where a quantum device estimates a hard-to-compute quantity, while a classical optimizer trains the parameters. In this work, we demonstrate that single photons and linear optical networks are sufficient for implementing variational quantum algorithms, when the problem specification (ansatz) is tailored to this specific platform. We show this by a proof-of-principle demonstration to tackle an instance of a factorization task, whose solution is encoded in the ground state of a suitable Hamiltonian. This work, which combines Variational Quantum Algorithms with hardware efficient ansätze for linear optics, showcases a promising pathway toward practical applications for photonic quantum platforms.
Photonic quantum technologies require the integration of high-quality quantum light sources with programmable photonic circuitry to enable on-chip quantum information processing. Semiconductor quantum dots have emerged as a leading platform for quantum light generation, yet their monolithic integration with cryogenic-compatible, programmable photonic circuitry remains challenging. Here we demonstrate a programmable quantum photonic platform that enables simultaneous control of highly coherent quantum dot-based single photon emitters and reconfigurable optical elements at cryogenic temperatures. System-level integration enables individual electrical and optical addressing of active components on a single chip, allowing their concurrent operation while preserving coherent non-classical light emission. We demonstrate multiple quantum-photonic functionalities, including pure single-photon generation, two-photon interference, and resonant transmission and reflection measurements of integrated emitters. These results mark a step from isolated quantum-optical devices towards programmable quantum-photonic hardware platforms capable of combining coherent quantum emitters with large-scale photonic functionality.