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Photonic quantum information processing: a concise review

Sergei Slussarenko, Geoff J. Pryde

arXiv:1907.06331v2quant-ph

TL;DR

Photonic quantum computing must overcome weak photon–photon interactions, loss, and resource overhead while supporting large-scale processing. This review surveys experimental and theoretical advances including improved detectors and sources, integrated photonics, and cluster-state computing. These developments support photonics as a promising platform for medium- and large-scale processing and quantum networking.

  • Problem

    Weak photon interactions, photon loss, and storage requirements create substantial resource overhead for scalable photonic quantum computing.

  • Method

    The review surveys selected experimental and theoretical advances in photonic quantum computing, including detectors, sources, integrated platforms, and cluster-state schemes.

  • Results

    The reviewed developments include reduced cluster-state resource requirements, high-performance photon sources and detectors, and increasingly complex integrated photonic circuits.

  • Takeaways & Limitations

    The review presents photonics as a promising route to medium- and large-scale quantum processing and as a leading platform for connecting distant processors.

  • Takeaways & Limitations

    The review only briefly covers error correction, optical quantum memories, algorithms, protocols, and several alternative encodings and technologies.

Abstract

from arXiv · show

Photons have been a flagship system for studying quantum mechanics, advancing quantum information science, and developing quantum technologies. Quantum entanglement, teleportation, quantum key distribution and early quantum computing demonstrations were pioneered in this technology because photons represent a naturally mobile and low-noise system with quantum-limited detection readily available. The quantum states of individual photons can be manipulated with very high precision using interferometry, an experimental staple that has been under continuous development since the 19th century. The complexity of photonic quantum computing device and protocol realizations has raced ahead as both underlying technologies and theoretical schemes have continued to develop. Today, photonic quantum computing represents an exciting path to medium- and large-scale processing. It promises to out aside its reputation for requiring excessive resource overheads due to inefficient two-qubit gates. Instead, the ability to generate large numbers of photons---and the development of integrated platforms, improved sources and detectors, novel noise-tolerant theoretical approaches, and more---have solidified it as a leading contender for both quantum information processing and quantum networking. Our concise review provides a flyover of some key aspects of the field, with a focus on experiment. Apart from being a short and accessible introduction, its many references to in-depth articles and longer specialist reviews serve as a launching point for deeper study of the field.

I. INTRODUCTION

Photonic quantum computing exploits photons’ high-fidelity single-qubit control and suitability for communication, while addressing weak interactions, loss, storage, and resource overhead. This review focuses on selected experimental and theoretical advances toward universal linear-optical quantum computing.

  • Photons offer clean, low-decoherence information carriers with highly precise single-qubit operations and natural suitability for quantum communication.
  • Photon loss, weak single-photon interactions, and possible storage requirements make deterministic two-qubit gates and scalable processing challenging.
  • These challenges create substantial optical quantum-computing resource overhead, contributing to negative perceptions of the photonic approach.
  • The review selects technological, experimental, and theoretical advances relevant to universal computing with individual photons and linear operations.
  • B. Basics: Dual-rail encoding represents a qubit across two optical modes, while interferometry implements reliable population shifts and phase operations.
  • B. Basics: Two-qubit operations are difficult because they require effective nonlinear interactions, so linear optics and measurement provide probabilistic alternatives using postselection or heralding.

A. Detecting a photon

Photon detection is central to photonic quantum computing, but detectors trade off efficiency, speed, noise, wavelength coverage, and photon-number resolution. Superconducting detectors substantially improve efficiency, while TES devices provide photon-number resolution at slower operating speeds.

  • Ideal detectors would combine unit detection efficiency, immediate reset, no dark counts, and exact photon-number resolution, but no such detector exists.
  • Detector performance is characterized by efficiency, reset time, timing jitter, dark counts, and photon-number resolution, all relevant to scalable platforms.
  • Si avalanche photodiodes typically provide reset times at most 100 ns and efficiencies up to approximately 65%, limiting simultaneous multi-photon detection.
  • Ten-photon detection with ten Si APDs has probability below 2%, while these detectors also lack photon-number resolution and telecom-band coverage.
  • SNSPDs reach efficiencies of approximately 0.93, recently at least 0.95, in telecom wavelengths with reset times around 40 ns, although they require cryogenic operation.
  • SNSPD research continues to improve reset times, timing jitter, and efficiency measurements, while thermal background radiation can require spectral filtering.
  • A. Detecting a photon: TES detectors resolve approximately 20 photons and reach efficiencies near 0.95 to 0.98 in telecom wavelengths, but typically operate with microsecond reset times and at least 50 ns jitter.

B. Generating a photon

Photonic quantum computing needs many efficiently generated, high-quality photons, but conventional SPDC sources remain probabilistic and lossy. Advances in phase matching and source engineering improve coupling, heralding, purity, and entanglement quality, while deterministic sources offer another route with remaining coupling challenges.

  • Large-scale photonic processors require simultaneous generation of roughly 10^4–10^11 single-photon states with efficient collection and high quality.
  • SPDC generates high-quality photons nondeterministically through χ(2) three-wave mixing, where a pump photon converts into signal and idler photons.
  • Basic SPDC sources suffer from poor fiber coupling, spectral entanglement, filtering loss, unfavorable wavelengths, and heralding efficiencies typically at or below 10–15%.
  • Using several photon-pair sources enabled complex states of up to ten photons, but low collective detection rates and state quality limited long-term prospects.
  • Quasiphase matching enables telecom-band, collinear, beam-like downconversion with near-identical Gaussian modes, reducing coupling and propagation losses.
  • Improved sources achieve heralding efficiencies above 0.8, state purities at least 0.997, and entangled-state qualities above 0.99.

C. Generating a photon deterministically

Because probabilistic photon-pair sources operate at low generation probabilities, scalable photonic experiments require multiplexing or deterministic sources to produce photons more reliably. Spatial and temporal multiplexing improve availability while preserving single-photon quality, although practical loss and coupling challenges remain.

  • Probabilistic sources: Photon-pair sources such as SPDC and SFWM are limited to generation probabilities ξ ≲1% because higher pump powers increase multiple-pair noise.Directly combining n sources would produce n simultaneous pairs with probability ξ^n, making that approach unsuitable for scalable photonic quantum computing.
  • Deterministic sources: Quantum-dot sources provide a more feasible route to deterministic photon generation and have enabled new quantum-computation demonstrations through increased brightness.Current limitations include coupling efficiencies ≲33% into single-mode fibers and distinguishability between photons from different dots.
  • Multiplexing: Spatial multiplexing heralds successful sources and actively routes one photon to the output, theoretically raising efficiency to ξmulti = 1 −(1 −ξ)^n without increasing multiple-pair noise.Integrated fiber- and waveguide-based platforms have helped move this experimentally demonstrated concept toward practicality.
  • Multiplexing: Temporal multiplexing records the heralding time bin and uses an active delay network to output photons at a fixed, lower repetition rate.The number n of time bins plays the role of n spatially separated sources.
  • Scaling beyond one photon: Multiplexing and optical quantum memories are being explored for synchronizing multiple probabilistic sources and generating more than one photon simultaneously.These approaches target states with one photon in each of N > 1 modes.
  • Outlook: Photon detection and probabilistic high-quality photon generation have advanced substantially, while deterministic sources remain under development without in-principle barriers to realization.The discussion excludes some advances, including spectrally narrowband sources for metrology and fundamental physics applications.

D. Manipulating a photon

Photonic quantum computing manipulates photons through precise control of polarization, path, and time-bin states, increasingly extending this capability to reconfigurable mode transformations in integrated optics.

  • Photon manipulation: Precise control of photon polarization, path, and time-bin states has long been a strength of photonic quantum computing.Recent developments extend this control to reconfigurable mode transformations in integrated quantum optics using fast electro-optic elements.

E. Integrated quantum photonics

Integrated quantum photonics combines scalable waveguides, sources, detectors, and programmable optical circuits on compact platforms. Its rapid growth expands circuit complexity and component density, while optical loss remains a central challenge.

  • Platforms and scalability: Integrated waveguides and optical chips offer a path to implementing photonic circuits at scale as demonstrations use larger numbers of photons and gates.Different materials support distinct geometries, nonlinearities, switching speeds, and integration capabilities.
  • Platforms and scalability: A silicon circuit integrates 16 photon-pair sources, 93 thermooptical phase shifters, 122 beamsplitters, 256 waveguide crossers, and 64 grating couplers.SFWM generates tunable multidimensional entanglement, while filters, crossers, MZI networks, and SNSPDs support state manipulation and detection.
  • Integrated detectors: Integrated SNSPDs now support fast, efficient, and low-noise detection at telecom wavelengths, with efforts extending toward waveguided photon-number-resolving detectors.Embedding detectors directly into optical chips is part of the broader integration strategy.
  • Integrated sources: Integrated photon sources can combine high brightness with high heralding efficiency because transverse confinement keeps pump, signal, and idler modes aligned through the nonlinear material.This addresses a disadvantage of bulk SPDC, where configurations optimized for brightness and heralding efficiency differ.
  • Integrated sources: SFWM provides a practical photon-pair-generation alternative on integrated platforms lacking χ(2) nonlinearities, where χ(3) nonlinearities dominate.Control of the daughter photons’ joint spectrum has also been generalized to SFWM.
  • Circuit development: Integrated quantum photonics has rapidly increased the scale, complexity, and performance of optical circuits, including fully reconfigurable processors for growing numbers of modes.The number of components on integrated chips has been observed to undergo Moore’s-law-like exponential growth with time.
  • Remaining challenges: Optical loss from material absorption, waveguide roughness, and coupling on and off chip remains a major challenge for integrated platforms.Proposed responses include improved materials, higher-index contrast, direct source and detector integration, and modular architectures.

III. QUANTUM COMPUTING

Photonic quantum computing evolved from KLM-inspired circuit approaches toward intermediate-scale and universal processors. Cluster-state computing is especially well matched to photons because it can exploit efficient entanglement generation, reliable measurements, and loss tolerance.

  • Circuit-based approaches: The KLM scheme established a scalable optical-processing route using linear optics, single-photon detection, and classical feed-forward, motivating worldwide photonic quantum-computing research.A full-scale error-corrected universal machine was not built then and remains challenging across quantum platforms.
  • Circuit-based approaches: Circuit-based approaches derived from KLM remain active theoretical and experimental paths toward intermediate-scale and universal photonic processors.The field continues to pursue increasingly capable gates and processors.
  • Cluster-state approaches: Cluster-state, or one-way, quantum computing is well suited to photon qubits because large cluster states can in principle be built efficiently with entangled sources and teleportation gates.Reliable photon measurements and tolerance to photon loss make cluster-state schemes a realistic path toward scalable photonic quantum computing.
  • Intermediate goals: Intermediate goals include more complex individual gates, small-scale algorithms, non-universal circuits or clusters, and supporting techniques for circuit and cluster-state models.These goals provide short- to medium-term targets on the path toward full-scale devices.

A. Intermediate quantum computing

Intermediate photonic quantum computing spans controlled-unitary gates, computational demonstrations, and BosonSampling. These approaches exploit precise optical control while confronting the difficulty of conditional interactions, photon loss, and noise.

  • Controlled-unitary gates: Controlled-unitary gates apply a unitary to target qubits conditionally on a control qubit, but adding this control is difficult even when U itself is easy.The general scheme doubles the target Hilbert space using an auxiliary photonic degree of freedom, routes modes through or around U, and recombines them.
  • Controlled-unitary gates: The scheme for adding control to arbitrary unitaries enabled experimental arbitrary controlled-single-qubit unitaries, CNOT, Toffoli, and Fredkin gates.It was also used for linear-equation solving, factoring 21, state-overlap and purity measurements, and eigenstate witnessing.
  • Intermediate demonstrations: Photonic gate architectures have realized intermediate-scale simulations including spin chains, molecular ground-state energies, Hamiltonian learning, eigenstate witnessing, and complex Fourier and Kravchuk transforms.These demonstrations used both bulk and integrated optics platforms.
  • BosonSampling: BosonSampling sends n single photons through a random unitary over m ≫ n modes, producing output samples that are classically hard to obtain but arise naturally from bosonic evolution.Better-than-classical performance is thought possible with 50–100 photons, although photon loss and other noise remain challenging constraints.
  • Noise control: Because fully fledged error correction is likely absent at the intermediate scale, machine learning is being investigated to handle unknown or difficult-to-model noise in photonic protocols.The approach targets noisy intermediate-scale quantum devices and can be applied to photonic and other systems.

B. Cluster-state based computing

Cluster-state computing shifts the difficult resource from online two-photon gates to offline entangled-state generation and deterministic single-qubit measurements. Improved construction, loss tolerance, and ballistic processing make cluster schemes increasingly plausible routes to large-scale photonic computation.

  • Cluster-state based computing: One-way computing builds cluster states offline using nondeterministic interactions, then performs computation through deterministic single-qubit operations suited to optics.This separates nondeterministic entanglement generation from the online computation.
  • Cluster-state based computing: More efficient cluster-state construction significantly reduces resource requirements, measured in Bell-pairs per effective two-qubit gate, and is more loss-tolerant than KLM.Experiments have expanded cluster states and computing networks while improving feed-forward and demonstrating blind computation.
  • Loss tolerance: Fusion failures or optical loss need not destroy cluster computation: below a threshold, percolation can reshape incomplete clusters, and fault-tolerant error correction appears achievable at modest loss thresholds.The percolation operation is described as a classically efficient relabeling of the cluster.
  • Ballistic cluster-state computing: Ballistic cluster-state computing generates and adaptively measures three-dimensional clusters on the fly without storing photons in an optical quantum memory.The required cluster depth is only of the order of a few tens of photons, allowing computation to proceed indefinitely in principle with continued source generation.
  • Field progress: Photonic quantum information science has progressed from two-to-four-photon experiments to demonstrations using 12 photons, while theory advances more resource-efficient and noise-tolerant schemes.Experimental progress includes improved sources, detectors, and integrated reconfigurable circuits.

IV. NETWORKING QUANTUM PROCESSORS

Photonic networking links quantum processors and distributes entanglement, but channel loss remains the dominant obstacle to secure and metrological applications. Heralded amplification, entanglement swapping, nondemolition measurements, and error correction are among the approaches being pursued.

  • Networking quantum processors: Quantum communication is essential for building distributed quantum processors, while verified entanglement links also support secure communication and distributed metrology.Photons are suited to transmitting quantum information between separated processors.
  • Networking quantum processors: Loophole-free entanglement verification supports device-independent protocols, but very high communication loss remains a challenge and predominant source of added noise.Loss degrades entanglement in the same way it degrades photonic quantum computation.
  • Loss and amplification: Postselecting successful detections can neglect loss, but it does not provide device-independent security or quantum advantage in metrology.The no-cloning theorem prevents identical backup copies of unknown states, while deterministic state-independent amplification would degrade purity.
  • Loss and amplification: Heralded amplification, or noiseless linear amplification, probabilistically identifies successful amplification through an independent detection signal and can distribute entanglement despite loss in principle.Failed trials produce a wrong output, so successful events must be heralded and sorted.
  • Quantum repeaters: Entanglement swapping has enabled sharing entanglement with the detection loophole closed over high-loss channels, alongside proposed nondemolition photon-number measurements and error-correction protocols.These methods contribute to quantum-repeater architectures for lossy environments.

V. CONCLUSION

The review focuses on experimental Fock-state photonic quantum information processing while noting broader encoding and technology directions. It concludes that improved cluster schemes, hardware, and intermediate tasks support substantial long-term promise, alongside unresolved alternatives and development needs.

  • Scope: The review briefly covers error correction, optical memories, algorithms, protocols, alternative encodings, and source and detector technologies outside its main experimental scope.Its focus is photonic Fock-state quantum information processing for medium-term experimental development.
  • Long-term prospects: Cluster-state improvements reduce nondeterministic overhead and loss error thresholds, while high-quality sources, detectors, gates, and integrated platforms support processors with many elements.These developments provide hardware and theoretical progress toward large-scale photonic devices.
  • Long-term prospects: BosonSampling offers a route toward demonstrating quantum computational advantage, while photonics remains a platform for connecting distant processors and sharing remote entanglement.The conclusion presents these as complementary near- and long-term opportunities.
  • Open technologies: Single-photon nonlinear interactions could greatly reduce the overhead of linear-plus-measurement approaches, but substantial research and development is still required.The review treats these interactions as potentially transformational technologies rather than established solutions.
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