Quantum circuits with many photons on a programmable nanophotonic chip
Juan Miguel Arrazola, Ville Bergholm, Kamil Brádler, Thomas R. Bromley, Matthew J. Collins, Ish Dhand, Andrea Fumagalli, Thomas Gerrits, Arseni Goussev, L. G. Helt, J. Hundal, Theodor Isacsson, Robert B. Israel, Josh Izaac, Soran Jahangiri, R. Janik, Nathan Killoran, Shreya P. Kumar, Jonathan Lavoie, Adriana E. Lita, Dylan H. Mahler, M. Menotti, Blair Morrison, Sae Woo Nam, Leonhard Neuhaus, Haoyu Qi, Nicolás Quesada, A. Repingon, Krishna Kumar Sabapathy, Maria Schuld, Daiqin Su, Swinarton Jeremy, Antal Száva, K. Tan, P. Tan, Varun Vaidya, Z. Vernon, Zabaneh Zeid, Yanbing Young Zhang
Abstract Growing interest in quantum computing for practical applications has led to a surge in the availability of programmable machines for executing quantum algorithms1, 2. Present-day photonic quantum computers3–7 have been limited either to non-deterministic operation, low photon numbers and rates, or fixed random gate sequences. Here we introduce a full-stack hardware−software system for executing many-photon quantum circuit operations using integrated nanophotonics: a programmable chip, operating at room temperature and interfaced with a fully automated control system. The system enables remote users to execute quantum algorithms that require up to eight modes of strongly squeezed vacuum initialized as two-mode squeezed states in single temporal modes, a fully general and programmable four-mode interferometer, and photon number-resolving readout on all outputs. Detection of multi-photon events with photon numbers and rates exceeding any previous programmable quantum optical demonstration is made possible by strong squeezing and high sampling rates. We verify the non-classicality of the device output, and use the platform to carry out proof-of-principle demonstrations of three quantum algorithms: Gaussian boson sampling, molecular vibronic spectra and graph similarity8. These demonstrations validate the platform as a launchpad for scaling photonic technologies for quantum information processing.
Abstract Growing interest in quantum computing for practical applications has led to a surge in the availability of programmable machines for executing quantum algorithms1, 2. Present-day photonic quantum computers3–7 have been limited either to non-deterministic operation, low photon numbers and rates, or fixed random gate sequences. Here we introduce a full-stack hardware−software system for executing many-photon quantum circuit operations using integrated nanophotonics: a programmable chip, operating at room temperature and interfaced with a fully automated control system. The system enables remote users to execute quantum algorithms that require up to eight modes of strongly squeezed vacuum initialized as two-mode squeezed states in single temporal modes, a fully general and programmable four-mode interferometer, and photon number-resolving readout on all outputs. Detection of multi-photon events with photon numbers and rates exceeding any previous programmable quantum optical demonstration is made possible by strong squeezing and high sampling rates. We verify the non-classicality of the device output, and use the platform to carry out proof-of-principle demonstrations of three quantum algorithms: Gaussian boson sampling, molecular vibronic spectra and graph similarity8. These demonstrations validate the platform as a launchpad for scaling photonic technologies for quantum information processing.
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.
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. 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 high accuracy. For photon native computation, we implement a classifier algorithm using a 3-photon-based quantum neural network and report a first 6-photon Boson Sampling demonstration on a universal reconfigurable integrated circuit. Finally, we report on a first heralded 3-photon entanglement generation, a key milestone toward measurement-based quantum computing.
Light-matter interaction at the quantum level provides a versatile interface driving photonic quantum technologies toward practical applications. We demonstrate multi-mode photonic circuits that enable precise programming of linear and nonlinear phase configurations at the single-photon level. The nonlinearity operation is realized using a solid-state quantum emitter, a self-assembled quantum dot, integrated into a nanophotonic device. The quantum dot interfaces with a temporal linear optical interferometer, creating a programmable nonlinear photonic platform that is necessary for implementing quantum protocols that require strong nonlinearities, such as the quantum simulation of anharmonic molecular dynamics.
Integrated quantum photonics has emerged as one of the leading platforms for scaling quantum information processing, offering compact, stable, and low-loss hardware with precise phase and mode control. Advances in integrated photonics architectures and active programmability now enable complex, high-dimensional transformations essential for quantum advantage tasks. We introduce an integrated, reconfigurable 3D photonic device with 128 modes for manipulation of single-photon quantum states (Qolossus 3D). Leveraging a continuously coupled architecture and thermo-optic programmability, the platform implements reconfigurable unitary transformations at unprecedented scale for integrated quantum optics. Exploiting indistinguishable single photons demultiplexed from a quantum dot source, we perform Boson Sampling across the large-dimensional chip and analyse the resulting output distributions for up to 4 photons. We then exploit it to demonstrate randomness generation via Boson Sampling. Agreement with theoretical predictions validates both the device's reconfigurable operation and the generation of random numbers. Our results highlight the scalability, stability, and precise control of integrated photonics for quantum information processing.
Abstract Quantum information science offers inherently more powerful methods for communication, computation, and precision measurement that take advantage of quantum superposition and entanglement. In recent years, theoretical and experimental advances in quantum computing and simulation with photons have spurred great interest in developing large photonic entangled states that challenge today’s classical computers. As experiments have increased in complexity, there has been an increasing need to transition bulk optics experiments to integrated photonics platforms to control more spatial modes with higher fidelity and phase stability. The silicon‐on‐insulator (SOI) nanophotonics platform offers new possibilities for quantum optics, including the integration of bright, nonclassical light sources, based on the large third‐order nonlinearity (χ (3) ) of silicon, alongside quantum state manipulation circuits with thousands of optical elements, all on a single phase‐stable chip. How large do these photonic systems need to be? Recent theoretical work on Boson Sampling suggests that even the problem of sampling from e30 identical photons, having passed through an interferometer of hundreds of modes, becomes challenging for classical computers. While experiments of this size are still challenging, the SOI platform has the required component density to enable low‐loss and programmable interferometers for manipulating hundreds of spatial modes. Here, we discuss the SOI nanophotonics platform for quantum photonic circuits with hundreds‐to‐thousands of optical elements and the associated challenges. We compare SOI to competing technologies in terms of requirements for quantum optical systems. We review recent results on large‐scale quantum state evolution circuits and strategies for realizing high‐fidelity heralded gates with imperfect, practical systems. Next, we review recent results on silicon photonics‐based photon‐pair sources and device architectures, and we discuss a path towards large‐scale source integration. Finally, we review monolithic integration strategies for single‐photon detectors and their essential role in on‐chip feed forward operations.
This dissertation explores the use of single photons in integrated photonic circuits as a platform for quantum computation and quantum simulation. In the noisy intermediate-scale quantum (NISQ) era, photonic implementations of boson sampling provide one of the most promising routes to demonstrating quantum advantage, while also enabling insight-driven experiments that probe many-body interference and computational complexity. The first part of the thesis is devoted to the hardware development and characterization of programmable silicon nitride photonic processors. We demonstrate large-scale multi-photon interference in a 20-mode universal processor, establishing the potential of integrated photonics for scaling up boson sampling experiments. In parallel, we introduce a validation protocol based on detector binning, implemented on a 12-mode predecessor of the device. Together, these studies advance the photonic platform itself, focusing on scalability, versatility, and benchmarking, rather than direct applications. The second part turns to quantum simulation. We first present a photonic simulation of a spin-foam amplitude from loop quantum gravity, illustrating how multi-photon interference can provide a testbed for problems in fundamental physics. We then implement a particle-number-difference Maxwell demon using conditional operations on photon subsets in a multi-mode interferometer. This experiment probes the link between thermodynamics and information theory, showing how a photonic platform with single-photon resolution and quantum interference can be used to explore information-driven control of physical systems. The final part addresses quantum computation, where we demonstrate a boson-sampling-accelerated Monte Carlo integrator. This hybrid quantum–classical algorithm represents one of the few proposals to extend boson sampling toward practical applications while plausibly retaining its computational hardness. We validate the method in a proof-of-principle experiment reproducing perturbative corrections in a model inspired by Efimov physics. Altogether, the results presented in this thesis position integrated photonics as both a scalable hardware platform for multi-photon experiments and a versatile tool for advancing quantum simulation and computation.