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Photonic Quantum Computing Explained

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TECHNOLOGY EXPLAINER

Photonic Quantum Computers
― How a photon becomes a qubit, the biggest wall of "optical loss," and the optical materials behind it

A photonic quantum computer uses particles of light (photons) as qubits. Photons are little affected by their environment and are easy to link by optical fiber, but photons normally pass through one another without interacting, so two-qubit gates need ingenuity. A photon also keeps travelling and is finally detected and gone, so it is handled differently from a "qubit that stays put." And the biggest challenge is that photons are lost a little at every component they pass (loss). This article explains, step by step with figures and small numerical examples: (1) how a photon becomes 0 and 1, (2) how to "connect" photons that pass through each other, (3) fusion-based quantum computation and the continuous-variable approach that measures the light wave, (4) why optical loss is decisive, (5) chip materials and temperature (cooling of detectors), and (6) the state of play as of the check date (16 October 2026) together with claims of quantum advantage and the rebuttals. Thin-film lithium niobate, silicon nitride waveguides, silicon photonics and photodetectors are covered in separate explainers in this series.

Sources: peer-reviewed papers (Nature, Science, Rev. Mod. Phys., Nat. Photon., Nat. Phys., and others), arXiv papers, and official pages of RIKEN and JST. Some numbers are our own calculations. Checked 16 October 2026

Optical fibers are aligned with high precision to a photonic quantum chip to bring light in and out. The image does not show any actual device or company's equipment.
Fig. 1. Conceptual illustration generated with ImageGen. Optical fibers are aligned with high precision to a photonic quantum chip to bring light in and out. The image does not show any actual device or company's equipment. Not an actual product, facility, dimensional specification or measurement. Distinguish enlarged models from full-scale scenes.
In this article
  1. In three lines / what to know first / where this sits in the series
  2. Recap: a qubit is an "arrow"
  3. How a photon becomes a qubit
  4. Photons pass through each other: so how do we "connect" them?
  5. Fusion-based quantum computation, and the continuous-variable approach
  6. The biggest wall: photon loss
  7. The key points on a common "card," and a side-by-side with the other three approaches
  8. Chips, materials and temperature
  9. Where things stand (checked 16 October 2026), plans, and claims of quantum advantage
  10. Limits, what we could not confirm, and a summary
  11. How to read evaluations and standards
  12. Glossary
  13. References (primary sources)
  14. Claim-to-source audit
How this article labels its statements

Sourced = stated in a published source (with a link)
Our calculation = a value this article computed from stated assumptions
Not yet confirmed = plans, targets, drafts and other items that are not settled
Readings for materials research and analogies are marked as commentary. An inference is shown in bold.

How to read the numbers in this article

A quantum-computing number means little unless it comes with what was measured and how. Here, error rates, fidelities and lifetimes come with the approach, the thing measured, whether it is an average or a best value, and the date. Company announcements are labeled as the company's claims, and plans and targets are shown as Not yet confirmed, kept apart from achieved facts. The loss graph in Chapter 6 is our own "feel-for-the-size" calculation, not an estimate of the loss of any real machine. We did not read the full texts of the standards (ISO/IEC, IEEE), which are paid; we give only titles and status. We do not tell lies to keep things simple. Every analogy comes with its limits.

1. In three lines / what to know first / where this sits in the series

  • The qubit of a photonic quantum computer is a photon, a particle of light. For example, which of two waveguides (paths for light) holds the photon sets 0 and 1 (dual-rail). Photons are little affected by the environment (low decoherence), most parts can run at room temperature, and optical fiber can link them[Ref. 1, 2, 3]Sourced
  • Photons pass through one another without interacting, so two-qubit gates are built with interference and measurement (the KLM scheme). Success is probabilistic, so fusion-based quantum computation, which combines small resource states with measurements called "fusions," is now a leading approach[Ref. 4, 5]Sourced
  • The biggest challenge is photon loss. A little is lost at each component and it accumulates. Aghaee Rad et al. call optical loss "the dominant and most challenging hurdle" to crossing the fault-tolerant threshold[Ref. 2]Sourced. As of the check date, we could not confirm a report that achieved practical-scale error correction including loss
The one line to remember

A photonic quantum computer "manipulates ever-travelling photons with interference and measurement." Its strengths are robustness to the environment and ease of linking by optical fiber. Its biggest challenge is that small losses at each component add up.

What to know first / where this sits in the series

Prerequisites: none. The arrow picture is recapped in the next chapter (no quantum-mechanics formulas are used).

Place in the series: read this after "The Basics of Quantum Computing" and "Quantum Gates and Circuits." It is easiest to read side by side with the other three approaches (superconducting, trapped ions, neutral atoms). The materials behind photonic quantum computers are covered in our explainers on thin-film lithium niobate, silicon nitride waveguides, silicon photonics, photodetectors, semiconductor lasers and optical fiber. How to read claims of quantum advantage is in our explainer on that topic, and communication in our explainers on quantum key distribution and quantum communication, and on quantum networks and repeaters.

2. Recap: a qubit is an "arrow"

In this series, a qubit's state is drawn as an arrow from the center of a sphere to its surface. Pointing at the north pole means "0," pointing at the south pole means "1," and pointing in between is a superposition. When the arrow is tilted, a measurement always gives 0 or 1, and the chance of each is set by the tilt. After the measurement the arrow is fixed at a pole, and the old tilt does not come back.

A qubit's state drawn as an arrow (a quick recap) 0 (north pole) 1 (south pole) Tilted = superposition Measure it, and you get either 0 or 1 If the arrow is tilted by θ from the north pole, the chance of reading 0 is cos²(θ/2) and of reading 1 is sin²(θ/2). After a measurement the arrow sits at a pole and the old tilt is gone. Example: θ = 60° (our calculation) P(0) = cos²(30°) = 0.75 P(1) = sin²(30°) = 0.25 They add up to 1. Measure 100 times and you get about 75 zeros and 25 ones. * The series' shared picture. The arrow's direction is the qubit's state. It does not mean a coin is showing heads and tails at once.
Fig. 2 Drawing that includes our own calculation (vector drawing). A recap of the arrow picture. The probabilities for θ = 60° are our own calculation (cos²(30°) = 0.75). It does not mean a coin shows heads and tails at once.
A common misconception: "a qubit is a coin that is both 0 and 1 at once"

That is wrong. A tilted arrow is not "holding both 0 and 1" but "pointing in a definite direction between 0 and 1." Measure it and you get just one of 0 or 1. A quantum computer's power comes from combining these arrow directions like waves so that the right answer reinforces itself (see our explainer on quantum algorithms).

3. How a photon becomes a qubit

Light is a wave and also a collection of "particles of light (photons)" (a property of the quantum world). A photonic quantum computer takes one photon as a qubit. The easiest encoding to picture is dual-rail. Two paths for light (waveguides) are placed side by side, and a photon in the upper waveguide is 0, in the lower one 1. When a photon goes through a half-silvered mirror (a beam splitter), it ends up "spread over both" paths. This is a superposition, the arrow tilted. Measured, it is found on just one path[Ref. 3, 6]Sourced. Combining beam splitters with phase shifters, which shift the phase of light, turns the arrow to any direction (one-qubit gates).

Dual-rail encoding uses which path contains one photon. Distribution across paths represents probability amplitudes, not copying the photon into two particles.
Fig. 3. Conceptual illustration generated with ImageGen. Dual-rail encoding uses which path contains one photon. Distribution across paths represents probability amplitudes, not copying the photon into two particles. Not an actual product, facility, dimensional specification or measurement. Distinguish enlarged models from full-scale scenes.
View original SVG, values and sources
A photon becomes a qubit: the "path" of light sets 0 and 1 (concept diagram) (a) Dual-rail: which of two waveguides holds the photon |0⟩ |1⟩ A photon in the upper waveguide is 0; in the lower one, 1. BS A beam splitter (BS) divides light between two paths. The photon is in a state "spread over both" (superposition). Measured, it is found in just one. (b) Other ways to take 0 and 1 Polarization: whether the light vibrates vertically or horizontally. Time: whether the photon arrives in an early or a late slot (time-bin). 0 1 There is also a way to place the qubit in the light wave itself (its amplitude and phase), the continuous-variable approach (Chapter 5). How this differs from the other approaches A qubit in superconducting, ion or neutral-atom machines is something that stays put. A photon keeps travelling at the speed of light, so it is operated on as it passes through the chip, is finally detected, and its job ends (it is gone). Limits of the analogy: if a photon is a "parcel in transit," operations are "sorting along the way" and detection is " checking arrival." But unlike a parcel, a photon is gone once checked. That a qubit becomes 0 or 1 when read out corresponds here to "the place where the photon is found being decided." * A concept diagram. Real circuits combine many beam splitters and phase shifters.

Original SVG reference: Concept diagram (vector drawing). Concept diagram of dual-rail encoding of a photon and other ways to take 0 and 1 (polarization, time-bin). The encodings follow the review by Kok et al. [Ref. 3] and PsiQuantum's dual-rail qubits [Ref. 6].

A place people stumble: a photon "keeps travelling"

Superconducting circuits and ions or atoms in vacuum are qubits that stay put in a chip or machine. A photon keeps travelling at the speed of light, so it is operated on as it passes through the chip and finally is caught by a detector and gone. So in a photonic quantum computer, rather than "placing a qubit in one spot and operating on it many times," computation means "applying operations one after another to the photons as they flow, and measuring at the end" (commentary). Limits of the analogy: "sorting parcels in transit" is easy to picture, but unlike a parcel a photon is gone once measured.

4. Photons pass through each other: so how do we "connect" them?

To connect two qubits (a two-qubit gate) an "interaction" between them is needed. But photons normally pass through one another without interacting. This is why light resists noise, and also why gates are hard to make. The idea of the solution is interference and measurement. Knill, Laflamme and Milburn (2001, KLM) showed that efficiently scalable quantum computing is possible with single photons, linear optics and measurement alone[Ref. 4]Sourced. The review by Kok et al. summarizes later improvements and the errors of real components[Ref. 3]Sourced.

Photons pass through each other: so how do we "connect" them? (concept diagram) (a) Photons pass through Even when two photons cross, they normally do not affect each other (no collision and bending). So photons resist noise and are easy to carry, but it is hard to make the interaction a two-qubit gate needs. (b) HOM interference BS both on one side If two indistinguishable (exactly identical) photons enter the two sides of a half-silvered mirror (a 50:50 beam splitter) at once, they always leave together on the same side. If the photons are distinguishable, the effect weakens. How much is the "HOM visibility," a gauge of photon quality. (c) Measurement links The KLM scheme (Knill, Laflamme and Milburn, 2001) showed that scalable quantum computing is possible with single photons, linear optics and measurement alone. The mechanism: interfere the photons, then "measure" some of them with detectors. The result decides the state of the remaining photons (measurement stands in for interaction). Success is probabilistic. The original idea of photonic quantum computing The starting point is that even photons that pass through each other can make gates, the parts of quantum computation, by combining interference and measurement (Knill et al., 2001; summarized in the review by Kok et al.). Gates succeed only probabilistically, though, so tricks to repeat until success, and many photons and detectors, are needed. Folding this "probabilistic" nature into the framework of error correction gives fusion-based quantum computation, the next chapter. * A concept diagram. The paths in (a) and the outputs in (b) are simplified.
Fig. 4 Concept diagram (vector drawing). Concept diagram of photons passing through each other, HOM interference and measurement-induced interaction. The KLM scheme is from Knill et al. [Ref. 4], the summary from the review by Kok et al. [Ref. 3], and the HOM-visibility number from PsiQuantum's paper [Ref. 6].

The key phenomenon here is HOM interference. If two perfectly indistinguishable photons enter the two sides of a half-silvered mirror at once, they always leave together on the same side. If they can be told apart (even slightly in time, color or shape), the effect weakens. The strength of this effect (the visibility) is a gauge of how identical photons are. The PsiQuantum team reported an HOM visibility of 99.50 ± 0.25% between photons from independent sources[Ref. 6]Sourced. Making photons so alike that they cannot be told apart is directly tied to gate quality (commentary).

A common misconception: "light resists noise, so photonic quantum computers make few errors"

It is true that photons are little affected by the environment (low decoherence)[Ref. 1]Sourced. But photons have a different kind of error: they are "lost." Loss differs from a photon's state being disturbed by the environment; the photon is gone. Moreover, photon sources emit photons only probabilistically, and photons are not necessarily perfectly identical. "Robust to the environment" and "few errors" are different things; in optics, loss and photon quality (sameness) are the main origins of error[Ref. 2, 6]Sourced.

5. Fusion-based quantum computation, and the continuous-variable approach

(1) Fusion-based quantum computation (FBQC): make → fuse → count

Using two-qubit gates that succeed only probabilistically as they are is hard. So Bartolucci et al. showed a computation model in which many small entangled states (resource states) are made and linked by "fusions" that take one photon from each of two resource states, interfere and measure them. The probabilistic failure of fusion and photon loss are handled within the error-correction framework. It can be built from repeated identical parts, and the depth of operations on each photon is low, so few components lie in a photon's path[Ref. 5]Sourced. Another root is measurement-based (one-way) quantum computing (Raussendorf and Briegel, 2001), in which a large entangled state (a cluster state) is prepared in advance and the computation proceeds just by measuring one qubit after another[Ref. 7]Sourced.

Fusion-based quantum computation: "make → fuse → count" (concept diagram) 1. Make photons On-chip sources make photons one at a time (they appear probabilistically) 2. Build small entangled states A few photons are interfered to make small " resource states" 3. Fusion (a linking measurement) Take one photon from each of two resource states, interfere and measure. If it succeeds, the two are linked 4. Count and decide Detector results are analyzed on an ordinary computer and errors are corrected The idea of this approach Fusion-based quantum computation (FBQC) of Bartolucci et al. is a model of universal computation using only small resource states and measurements called "fusions." The hardware can be made of many identical modules, and the depth of operations on each photon is extremely low, so few components lie in a photon's path. The probabilistic failure of fusion is handled within the error-correction framework. Another root: measurement-based (one-way) Raussendorf and Briegel (2001) proposed the "one-way quantum computer," in which a large entangled state (a cluster state) is prepared in advance and the computation proceeds by measuring one qubit after another. Light can carry distant photons while staying entangled, so it is said to suit this approach. Numbers for orientation Bartolucci et al. showed a "ballistic" scheme that tolerates a 10.4% probability of losing a photon in each fusion, under their error model (the number is for that model's conditions). * A concept diagram. The actual design of fusion differs between schemes.
Fig. 5 Concept diagram (vector drawing). Concept diagram of the flow of fusion-based quantum computation. The model is from Bartolucci et al. [Ref. 5] and the measurement-based approach from Raussendorf and Briegel [Ref. 7].

(2) The continuous-variable approach: measuring the light wave

Instead of counting photons one by one, another approach puts information in the amplitude and phase of the light wave (the continuous-variable approach). It uses "squeezed light," light whose wave fluctuation is reduced in one direction, and measures the wave amplitude by homodyne detection. Akira Furusawa and colleagues at the University of Tokyo and RIKEN made a two-dimensional cluster state by time-domain multiplexing (lining up light pulses in time so one optical system is used repeatedly)[Ref. 8, 9]Sourced. Konno et al. realized a GKP qubit state (an error-robust qubit placed in a single light wave) in propagating light at a telecom wavelength and showed homodyne measurements on it without loss correction for the first time; they showed non-classicality at room temperature and atmospheric pressure[Ref. 10]Sourced. A Xanadu team generated GKP states on a silicon nitride chip (negative regions of the Wigner function in a 3×3 grid); the authors state that after further loss reduction such states could reach the fault-tolerant regime[Ref. 11]Sourced.

Two ways to use light: count photons, or measure the light wave (concept diagram) (a) Discrete-variable: counting photons Interferometer det. det. det. Information is placed in the number of photons or which path they take, and detectors count them. Examples: PsiQuantum (fusion-based), Quandela (gate-based), boson sampling (Jiuzhang, Borealis). Strength: detectors that reliably count single photons can be used. Weakness: losses of sources and detectors hit directly. Many detectors are cooled. (b) Continuous-variable: measuring the wave Homodyne detection ← wave amplitude Information is placed in the amplitude and phase of the light wave ("squeezed light," etc.) and the wave is measured. Time-domain multiplexing lines it up in time: the Furusawa group at the University of Tokyo and RIKEN, and Xanadu's Aurora. The GKP qubit is a code that places a qubit in a single light wave and makes it robust to errors. Konno et al. (2024) realized a GKP state in propagating light at a telecom wavelength and showed non-classicality at room temperature and atmospheric pressure. In both approaches the biggest challenge is optical loss. Aghaee Rad et al. analyzed in detail the tolerances of their architecture for optical loss and state it is "the dominant and most challenging hurdle" to crossing the fault-tolerant threshold. * A concept diagram.
Fig. 6 Concept diagram (vector drawing). Concept diagram of the discrete-variable (counting photons) and continuous-variable (measuring the light wave) approaches. Sources: Alexander et al. [Ref. 6], Maring et al. [Ref. 1], Konno et al. [Ref. 10], Aghaee Rad et al. [Ref. 2] and RIKEN's official page [Ref. 9].

6. The biggest wall: photon loss

The biggest challenge of a photonic quantum computer is photons being lost. A photon passes through many parts on its way from the source through waveguides, filters, interferometers and connections to the detector. Every part scatters or absorbs a little light, and detectors miss some. Aghaee Rad et al. analyzed in detail how much optical loss their architecture can tolerate and state that optical loss is "the dominant and most challenging hurdle" to crossing the fault-tolerant threshold[Ref. 2]Sourced.

How much loss can be tolerated? Bartolucci et al. showed a scheme that tolerates a 10.4% probability of losing a photon in each fusion, under their error model (the value is for that model's conditions)[Ref. 5]Sourced. Let us do a calculation to get a feel for scale (Our calculation). If 0.1% (1 in 1,000) of photons are lost at one component, then after a photon passes through 100 components the total fraction lost is 1−0.999¹⁰⁰ ≈ 9.5%. After 200 components it is 18.1%, above 10.4%. With 0.5% per component, about 22 components reach 10.4%; with 1%, about 11 (see the figure below).

Photon loss: a little is lost at every component (our calculation) 0% 10% 20% 30% 40% 50% 0 50 100 150 200 250 300 10.4% 0.1% per part 0.5% 1% Number of components a photon passes Total fraction of photons lost Calculation: how many parts reach 10.4% Loss per part Parts 0.1% about 110 0.5% about 22 1% about 11 Total loss is computed as 1−(1−ℓ)ⁿ (ℓ is the loss per part, n the number of parts). A photon loses a little at each part, and it adds up. 10.4% is the loss per fusion that Bartolucci et al.'s scheme can tolerate. It is placed here only against a photon's whole-life loss for a feel of scale, and is not an estimate for a real machine. That is why, in photonic quantum computing, pushing the loss per part as low as possible (low-loss waveguides, connections to optical fiber, high-efficiency detectors) is the biggest challenge. * The calculation of total loss 1−(1−ℓ)ⁿ. The numbers of parts and the losses are conceptual examples.
Fig. 7 Drawing that includes our own calculation (vector drawing). Relation between the number of components a photon passes and the total fraction lost (our calculation: 1−(1−ℓ)ⁿ). The 10.4% (dotted line) is the tolerable loss "per fusion" of Bartolucci et al.'s scheme [Ref. 5], placed here only to give a feel for scale.
A common misconception: "loss doesn't matter in photonic computers; just add more photons"

Loss also affects how hard the quantum computation is. Oh et al. showed that in Gaussian boson sampling, an optical experiment, high photon loss makes the experiment easier to simulate efficiently on a classical computer, and they questioned the experiments' claims of "quantum advantage"[Ref. 12]Sourced. Adding photons does not make detected photons easy to multiply if the fraction lost stays the same, nor does it raise the value of the computation. Lowering the loss per component before increasing the number is this approach's central challenge[Ref. 2]Sourced.

7. The key points on a common "card," and a side-by-side with the other three approaches

Here is everything so far as a "card" that answers the series' five shared questions (what it is made of, what 0 and 1 are, how it is controlled, how it is read, strengths and weaknesses). The other three articles use the same card.

The photonic-quantum-computer "card" (five questions plus materials) 1. What is it? A single particle of light (a photon) travelling in a waveguide or optical fiber. The optical circuit is built on a chip of silicon or similar. 2. What are 0 and 1? Which of two waveguides holds the photon (dual-rail). It can also be encoded in polarization, time-bin, or the amplitude and phase of the light wave. 3. How is it controlled? Beam splitters and phase shifters adjust the interference of light. Two qubits are linked by interference and detection (measurement) (fusion). Photons pass through each other. 4. How is it read out? Photodetectors count which path the photon arrived on. In one example superconducting nanowire detectors run at about 2 K. The continuous-variable approach measures wave amplitude by homodyne detection. 5. Strengths and weaknesses Strengths: little affected by the environment; most parts run at room temperature; easy to link by optical fiber; can be built on a semiconductor manufacturing line. Weaknesses: photon loss is the biggest challenge; photon sources are probabilistic; photons do not interact. + Materials Silicon and silicon nitride waveguides, NbN detectors, phase shifters such as BTO, optical fiber. Low-loss materials and connections are the key (Chapter 8). * Numbers follow the chapters of this article (with sources).
Fig. 8 Concept diagram (vector drawing). A card answering the five questions. Sources for the numbers are given in each chapter.

Reading the four approaches in the same format

ItemSuperconductingTrapped ionNeutral atomPhotonic
What the qubit isA superconducting circuit (e.g., a transmon): an "artificial atom" about 1 mm across, drawn on a chip[Ref. 13]One atomic ion floated in vacuum by radio-frequency electric fields (e.g., Ba⁺, Yb⁺)[Ref. 14, 15]One neutral atom caught in vacuum by an optical tweezer, a tightly focused laser beam (e.g., Rb, Cs, Yb)[Ref. 16, 17, 18]A photon (a particle of light) travelling in a waveguide, a path for light, or in an optical fiber[Ref. 6, 2]
How 0 and 1 are told apartThe lowest two energy steps of the circuit[Ref. 13]Two internal states of the atom (e.g., two hyperfine levels of Ba⁺)[Ref. 15]Two internal states of the atom (e.g., two hyperfine levels of Rb)[Ref. 16]Which of two paths the photon takes (e.g., one of two waveguides); it can also be an early or late time slot[Ref. 6, 3]
How it is controlledMicrowave pulses. Two-qubit gates use a coupler or the cross-resonance effect[Ref. 13, 19]Laser light (or microwaves or electrical signals). Two-qubit gates use the shared motion of the ions as a go-between[Ref. 14, 20, 21]Laser light. In a two-qubit gate, atoms are lifted to a highly excited Rydberg state so that nearby atoms affect each other[Ref. 22, 16]Interference in an optical circuit and photon detection (measurement). Photons pass through each other, so measurement creates the interaction[Ref. 3, 5]
How it is read outMeasure a small shift in the microwave response of a resonator (dispersive readout)[Ref. 23, 24]Shine light and see whether it fluoresces (bright / dark)[Ref. 14]Image the fluorescence and see which atoms are bright or dark[Ref. 25]Photodetectors count which path the photon arrived on (one example runs superconducting nanowire detectors at about 2 K)[Ref. 6]
Operating environmentAbout 20 mK in a dilution refrigerator[Ref. 13]Ultra-high vacuum. Traps exist at room temperature and in cooled form[Ref. 26, 27]Lasers and optics around an ultra-high-vacuum chamber. Atoms at about 10 μK, apparatus at room temperature[Ref. 16, 25]Most circuit parts run at room temperature. Detectors are often cooled[Ref. 2, 6]
Example two-qubit gate time43 ns (an example by Barends et al.) or about 200 ns (a cross-resonance example)[Ref. 13]About 70 μs (an example from Helios). One study scanned 3.8 μs to 520 μs[Ref. 15, 26]Gate pulses are on the order of hundreds of ns (one calibration value in Evered et al.: 275 ns). Rearranging and imaging take longer[Ref. 16, 28]We could not confirm a representative value
Example of two-qubit quality (definitions differ)EPLG 3.7×10⁻³ as shown on IBM's official page (measurement conditions could not be confirmed)[Ref. 19, 29]Average infidelity 7.9×10⁻⁴ (Helios, average over all zones of a 98-qubit machine)[Ref. 15]Fidelity 99.5% (up to 60 atoms in parallel, Evered et al.)[Ref. 16]"Fusion" fidelity 99.22% (only when detection succeeds; loss not included)[Ref. 6]
StrengthsFast. Semiconductor-style microfabrication can be used[Ref. 13]Ions of one species are all identical. Control precision is high[Ref. 14, 15]Many identical atoms can be lined up (6,100). The layout can be changed[Ref. 25, 30]Easy to link with optical fiber. Optical circuits can be built in a semiconductor factory (the plan)[Ref. 6, 2]
WeaknessesQubit lifetimes are relatively short. Wiring and cooling; fabrication variation[Ref. 31, 32, 33, 34]Gates are slow. Scaling adds electrodes, lasers and wiring[Ref. 15, 14]Atoms get lost. Cycles are slow[Ref. 35, 28]Photon loss is the biggest challenge. Photons barely interact with each other[Ref. 2, 3]

The arrangement is commentary; the numbers and facts in each cell come from the references (checked 16 October 2026). The numbers are different quantities under different conditions, so please do not rank the approaches by them.

Four approaches, one set of five questions (concept diagram) Superconducting Trapped ion Neutral atom Photonic 1. What is it? A superconducting circuit on a chip (an artificial atom) One ion held in place by electric fields One atom held by an optical tweezer One photon travelling in a waveguide or fiber 2. What are 0 and 1? The lowest two energy steps of the circuit Two internal states of the ion (e.g., hyperfine levels) Two internal states of the atom (e.g., hyperfine levels) Which of two paths (waveguides) or which time slot the photon takes 3. How is it controlled? Microwave pulses Laser light (or microwaves / electrical signals) Laser light (two atoms interact via Rydberg states) Optical interference and photon detection (measurement) 4. How is it read out? Microwaves probe a small shift of a resonator's tone Does it fluoresce? (bright / dark) Image the fluorescence (bright / dark) Photodetectors count whether a photon arrived 5. What environment? About 20 mK (dilution refrigerator) Ultra-high vacuum; both room-temperature and cooled traps exist Ultra-high vacuum; apparatus at room temperature Most circuit parts at room temperature; detectors are often cooled * Each cell summarizes a chapter of this article (with sources). This diagram only lines up what the qubit is and how it is controlled; it does not rank performance.
Fig. 9 Concept diagram (vector drawing). A concept diagram lining up what the qubit is in each of the four approaches by the same five questions. This article's approach is outlined. It does not rank performance. The other three are covered in their own explainers in this series.
A place people stumble: which one is best?

The answer is "not settled yet." Each has different strengths: speed (superconducting), precision and all-to-all connectivity (ions), large numbers and freedom of layout (neutral atoms), and compatibility with communication (photons). All of them attack the same hard problem — keeping quality while adding qubits — by different routes. The numbers in this article's table have different definitions and conditions, so please do not compare them directly.

8. Chips, materials and temperature

A feature of photonic quantum computers is that the optical circuits can be built on a semiconductor manufacturing line. The PsiQuantum team integrated modules that generate, manipulate, network and detect light in a 300 mm silicon-photonics process flow and reported state-preparation-and-measurement fidelity of 99.98 ± 0.01% for dual-rail qubits, HOM visibility of 99.50 ± 0.25% between independent sources, two-qubit fusion fidelity of 99.22 ± 0.12% and chip-to-chip interconnect fidelity of 99.72 ± 0.04%. However, the paper states these are "conditional on photon detection and not accounting for loss"[Ref. 6]Sourced (a paper by a company team; we have not confirmed reproduction by other laboratories). As next-generation parts the authors show low-loss silicon nitride (SiN) waveguides to reduce loss, fabrication-tolerant photon sources, high-efficiency photon-number-resolving detectors, low-loss fiber coupling and barium-titanate (BTO) electro-optic phase shifters[Ref. 6]Sourced.

Sources, optical manipulation circuits, fiber coupling and single-photon detectors are distinct. Materials and operating temperatures differ; the whole system need not operate at room temperature.
Fig. 10. Conceptual illustration generated with ImageGen. Sources, optical manipulation circuits, fiber coupling and single-photon detectors are distinct. Materials and operating temperatures differ; the whole system need not operate at room temperature. Not an actual product, facility, dimensional specification or measurement. Distinguish enlarged models from full-scale scenes.
View original SVG, values and sources
A photonic quantum-computer chip, and the materials and temperature issues (concept diagram) Source Filters Interferometer phase shifters Detectors Direction of the photons → Much of it can run at room temperature about 2 K (cooled) Chip materials and manufacturing (Alexander et al.) Silicon photonics: a 300 mm wafer manufacturing flow Detectors: a roughly 5 nm NbN (niobium nitride) film, about 90 nm wide, run at about 2 K Next generation: low-loss silicon nitride (SiN) waveguides, BTO (barium titanate) electro-optic phase shifters, low-loss fiber coupling Reported values from PsiQuantum's chips (a company team's paper) 99.98 ± 0.01% state-preparation-and-measurement fidelity of dual-rail qubits 99.50 ± 0.25% HOM visibility between independent sources 99.22 ± 0.12% fidelity of two-qubit fusion 99.72 ± 0.04% fidelity of the chip-to-chip qubit interconnect All of these are stated in the paper as " conditional on photon detection and not accounting for loss." Performance including loss remains a separate challenge. * A concept diagram. The values are reported in the paper by Alexander et al. (treated as the company's claims).

Original SVG reference: Concept diagram (vector drawing). Concept diagram of a photonic quantum chip and its materials and temperature issues. The values are from Alexander et al. [Ref. 6] (values reported by a company team).

Temperature: the circuit at room temperature, the detectors cooled

Aghaee Rad et al. state that photonic quantum computers have the advantage that "most components run at room temperature"[Ref. 2]Sourced. But in practice detectors that count photons one at a time are often cooled. In PsiQuantum's example, superconducting nanowire single-photon detectors (SNSPDs) run at about 2 K, with a roughly 5 nm niobium-nitride (NbN) film and hairpin-shaped wires about 90 nm wide introduced into the silicon-photonics stack[Ref. 6]Sourced. In the continuous-variable work of Konno et al., the light states are generated at room temperature and atmospheric pressure[Ref. 10]Sourced. For detectors that count photon numbers, the Furusawa project of the JST Moonshot program lists the development of a superconducting photon-number discriminator[Ref. 36]Sourced. So "photonic means room temperature" should accurately be read as most of the circuit is at room temperature, while detectors often need cooling (commentary). Detector materials and cooling are covered in our explainer on photodetectors.

A materials engineer's view (1): materials that make "0.1% per component"

As the calculation in Chapter 6 shows, a practical starting point for a photonic quantum computer is to bring the loss per component to the order of 0.1% (Our calculation). Scattering from sidewall roughness of waveguides, optical absorption of materials and coupling loss at fiber-to-chip connections translate directly into photon loss. That is why PsiQuantum's paper lists silicon nitride waveguides, with lower loss than silicon waveguides, among its next-generation parts[Ref. 6]Sourced. A Xanadu team made GKP states with an ultra-low-loss chip built on a 300 mm wafer multilayer silicon nitride platform[Ref. 11]Sourced. These materials and their manufacturing are covered in our explainers on silicon nitride waveguides, silicon photonics and thin-film lithium niobate. For a materials engineer, a photonic quantum computer is a field that uses telecom optical-materials technology against a loss standard orders of magnitude stricter (commentary).

A materials engineer's view (2): making "the same photon," filters and shielding

The HOM visibility gauges how identical photons are, so manufacturing variation of the photon source translates directly into gate quality. The PsiQuantum team lists "fabrication-tolerant photon sources" among its next-generation parts[Ref. 6]Sourced. The source's laser (pump light) is orders of magnitude stronger than the photons, so on-chip filters remove it by 99.1 ± 1.2 dB and the detectors are further encased in metal to protect them from scattered light (about 115 dB of pump suppression was observed)[Ref. 6]Sourced. Inference: this suggests that the materials challenge of photonics extends beyond loss to materials technology for shielding, filters and multilayer wiring — how to block strong light next to a detector.

The connection between optical fiber and chip is a place where photon loss easily arises. The image does not show any actual factory or company's tools.
Fig. 11. Conceptual illustration generated with ImageGen. The connection between optical fiber and chip is a place where photon loss easily arises. The image does not show any actual factory or company's tools. Not an actual product, facility, dimensional specification or measurement. Distinguish enlarged models from full-scale scenes.

9. Where things stand (checked 16 October 2026), plans, and claims of quantum advantage

(1) Peer-reviewed papers by company research teams

PsiQuantum (Alexander et al., Nature 2025): as in Chapter 8, a manufacturable platform and fidelities that do not account for loss[Ref. 6]Sourced. Xanadu: Aghaee Rad et al. (Nature 2025) built Aurora, a "(sub-performant) scale model" of a quantum computer using 35 photonic chips, 84 squeezers and 36 photon-number-resolving detectors to furnish 12 physical-qubit modes at each clock cycle, and showed a cluster state entangled across 86.4 billion modes and real-time decoding of a distance-2 repetition code[Ref. 2]Sourced. Larsen et al. (Nature 2025) generated GKP states on a silicon nitride chip[Ref. 11]Sourced. Quandela: Maring et al. (Nature Photonics 2024) reported, for a cloud-accessible prototype with a quantum-dot single-photon source and a reconfigurable optical chip, fidelities of 99.6 ± 0.1%, 93.8 ± 0.6% and 86 ± 1.2% for one-, two- and three-qubit gates[Ref. 1]Sourced. All are papers by company teams, and we have not confirmed reproduction by other laboratories. The paper itself calls Aurora "sub-performant."

(2) Japan: the Furusawa laboratory at the University of Tokyo and RIKEN, and the national project

RIKEN's Optical Quantum Computing Research Team (Akira Furusawa) states its final goal as "fault-tolerant large-scale universal optical quantum computers" and says it makes cluster states of optical modes larger and more precise by time-domain multiplexing[Ref. 9]Sourced. The page of the Furusawa project in the JST Moonshot R&D program aims at a large-scale optical quantum computer that operates at room temperature by 2050 and lists, as a milestone by 2030, research and development of a fault-tolerant large-scale universal machine that partly uses electrical signal processing (plans and goals)[Ref. 36]Not yet confirmed. As of the check date we could not confirm an official report that these goals have been achieved. We do not use news about companies' (startups') plans or funding, because they are not primary sources.

(3) Claims of quantum advantage and the rebuttals (who, on what, against what)

Claim / studyWhat was doneAgainst what, and what was claimedCautions in reading
Jiuzhang (Zhong et al., Science 2020)Gaussian boson sampling. 50 squeezed-light inputs fed into a 100-mode interferometer, sampled by 100 high-efficiency detectors; up to 76 photon detections observedClaimed a sampling rate 10¹⁴ times faster than state-of-the-art simulation and supercomputers[Ref. 37]SourcedA rebuttal points to the high photon loss of this kind of experiment and says it can be reproduced on a classical computer (next row)
Borealis (Madsen et al., Nature 2022, Xanadu)Gaussian boson sampling. 216 squeezed-light modes (three-dimensional connectivity), photon-number-resolving detectors, a photonic processor programmable on all gatesClaimed that the best algorithms and supercomputers would need on average more than 9,000 years to produce one sample by exact methods, versus 36 μs for Borealis (a company team's claim)[Ref. 38]SourcedThe same paper notes that earlier photonic experiments were vulnerable to classical shortcuts (spoofing)
Oh et al. (Nature Physics 2024)A classical tensor-network algorithm simulating the largest Gaussian-boson-sampling experiment so farComplexity falls when photon loss is high; shows evidence that the classical sampler can simulate the ideal distribution better than the experiment, calling the claim of advantage into question[Ref. 12]SourcedAn "advantage" can be overturned later by progress in the best classical methods

The arrangement is commentary; the facts in each row come from the references. These are claims of advantage on a "specific task," boson sampling, and do not mean that general-purpose quantum computing has surpassed classical computers. Our explainer on reading quantum-advantage claims covers this in detail.

A place people stumble: boson sampling is not "general-purpose"

Boson sampling is the task of sending photons through a linear-optical circuit and counting the output photons. Aaronson and Arkhipov (2010) gave evidence that this task cannot be simulated efficiently on a classical computer, but they also state that this model is not believed to be universal for quantum computation[Ref. 39]Sourced. So an "advantage" in boson sampling is not evidence that useful computation can be done; it means that a task that (perhaps) only a quantum device can do has been run in an experiment (commentary).

10. Limits, what we could not confirm, and a summary

(1) Full texts of standards

We did not read the full text of ISO/IEC 4879:2024, which is paid. For IEEE P7130 and P7131 we could not retrieve the IEEE pages and confirmed only the existence of the projects through StandICT.eu. We could not confirm any standard specific to photonic quantum computers.

(2) Company papers

The PsiQuantum, Xanadu and Quandela papers are by company teams, and we have not confirmed reproductions by other laboratories. The numbers are treated as values reported by company teams.

(3) Loss estimates

The loss calculation in Chapter 6 is an example for feel, not an estimate of a real machine's loss or the number of parts needed. We could not confirm a real machine's loss budget.

(4) Content not covered

We do not cover the detailed kinds of photon sources (quantum dots, spontaneous parametric down-conversion, etc.), quantum memories, quantum repeaters, or the plans of Japanese companies (startups).

(5) Progress on plans

Whether the JST Moonshot goals and companies' roadmaps have been achieved is stated only as far as official reports of achievement could be confirmed.

Summary of this article
  • A photonic quantum computer takes a single photon as a qubit. For example, which of two waveguides it is in (dual-rail) sets 0 and 1Sourced
  • Photons pass through each other, so two-qubit gates are built with interference and measurement. Fusion-based quantum computation is a leading approachSourced
  • Optical loss is the biggest wall. Even 0.1% per component becomes about 18% after 200 components (our calculation)Our calculation
  • Strengths: robust to the environment, most of the circuit at room temperature, and linkable by optical fiber. But detectors are often cooledSourced
  • "Quantum advantage" is a claim about a specific task, and rebuttals exist. It does not mean general-purpose quantum computing has surpassed classical computersSourced

11. How to read evaluations and standards

A photonic quantum computer's performance is read through photon quality (HOM visibility), gate and fusion fidelity (with or without loss), how much loss can be tolerated, and claims of quantum advantage and their rebuttals. The main caution in photonics is that a fidelity "not accounting for loss" and the quality of the whole machine including loss are different things. For standards, vocabulary has come first, while standards for how to measure performance are still at the project stage (checked 16 October 2026).

What is evaluatedRepresentative benchmarks and evaluation methods (name, source)Standards and guidance (NIST, ISO/IEC, IEEE, ETSI, ITU-T, IETF, etc.)Cautions in reading
Photon quality (sameness)HOM visibility. 99.50 ± 0.25% between independent sources (PsiQuantum)[Ref. 6]SourcedWe could not confirm oneThe number changes with the type of photon source and measurement conditions (independent sources or the same source)
Gate and fusion qualityTwo-qubit fusion fidelity 99.22 ± 0.12%, chip-to-chip 99.72 ± 0.04%, SPAM 99.98 ± 0.01%: values only when detection succeeds, not accounting for loss (PsiQuantum)[Ref. 6]Sourced. One-, two- and three-qubit gates 99.6%, 93.8% and 86% (Quandela)[Ref. 1]SourcedWe could not confirm oneA fidelity "not accounting for loss" is a different thing from the quality of the whole machine including loss. Always check the conditions
Loss and the error-correction thresholdTolerable loss for each scheme. Examples: 10.4% per fusion (Bartolucci et al.'s ballistic scheme, under that model's conditions), the analysis of optical loss (Aghaee Rad et al.)[Ref. 5, 2]SourcedWe could not confirm oneThe tolerance depends on the scheme and error-model conditions. We could not confirm a real machine's loss budget
Claims of quantum advantageBoson sampling: Zhong et al. (2020), Madsen et al. (2022). Classical-side rebuttal: Oh et al. (2024)[Ref. 37, 38, 12]SourcedWe could not confirm oneCheck who claims what on which task against what. If there is a re-evaluation by the best classical methods, read both side by side
Plans versus achievementsGoals of the JST Moonshot program (2030, 2050). We could not confirm companies' roadmaps[Ref. 36]Not yet confirmedWe could not confirm oneA goal is not an achieved fact. Check whether the figure is physical or logical
Is the physical system a good raw material for a quantum computer?DiVincenzo's seven items (five requirements plus two on communication): (1) many well-characterized qubits, (2) initialization, (3) coherence time much longer than a gate, (4) a universal set of gates, (5) qubit-specific measurement, (6)(7) two items on communication[Ref. 41]SourcedWe could not confirm one (this is a paper's framework, not a standard)It is a checklist, not a score. Each of the four approaches meets the items in different ways and has different weak points
Gate accuracy (one- and two-qubit)Randomized benchmarking (RB): run random gate sequences and infer the average error from how success decays (Knill et al., 2008; Magesan et al., 2011)[Ref. 42, 43]SourcedIEEE P7131 (quantum computing performance metrics and benchmarking) is at the project stage[Ref. 44]Not yet confirmedRead "99.9% fidelity" together with which operation was measured and how. RB numbers depend on how the test is done
Quality of the whole machineQuantum volume (Cross et al., 2019), EPLG (McKay et al., 2023), CLOPS (Wack et al., 2021), a method to measure capabilities (Proctor et al., 2022)[Ref. 45, 29, 46, 47]SourcedWe could not confirm one (IEEE P7131 is at the project stage)[Ref. 44]Not yet confirmedEach metric measures something different. Do not decide a machine's merit from one number (a survey of benchmarks: Acuaviva et al., 2026[Ref. 48])
Terminology and definitions— (a vocabulary standard, not an evaluation method)ISO/IEC 4879:2024 "Information technology — Quantum computing — Vocabulary" (first edition, May 2024, published)[Ref. 40]Sourced. IEEE P7130 (quantum technology definitions) is at the project stage[Ref. 49]Not yet confirmedThe standards' full texts are paid, so we did not read them. We do not state their requirements or definitions

The arrangement of the table is Our calculation (organization). Because the standards' full texts are paid, we give only titles and status (checked 16 October 2026).

Cautions in reading (for materials engineers)

  • "How many qubits" alone does not tell performance. Aurora's "12 physical-qubit modes" and PsiQuantum's "dual-rail qubits" are counted differently[Ref. 2, 6]
  • A fidelity "not accounting for loss" is not the quality of the whole machine. In photonics, loss is the biggest challenge, so always check the figure that includes loss[Ref. 6, 2]
  • A company's announcement and third-party verification are different. Read claims of quantum advantage together with classical-side rebuttals.[Ref. 38, 12]
  • Check whether a standard is a recommendation or a requirement, and whether it is legally binding. ISO/IEC 4879 is a vocabulary standard and does not guarantee performance[Ref. 40]. Plans are Not yet confirmed

12. Glossary

Qubit
The unit of information in a quantum computer. It can point in a direction between 0 and 1. In the series' shared picture, an "arrow."
Photon
A particle of light. In a photonic quantum computer a single photon is a qubit.
Waveguide
A path for light inside a chip that confines and guides it.
Dual-rail
A way to represent 0 and 1 by which of two waveguides holds the photon.
Beam splitter (BS)
A half-silvered mirror that divides light in two. It puts a photon in a superposition.
Phase shifter
A part that shifts the phase of light. Used to turn the arrow.
Interference
The adding of light waves (reinforcing and cancelling).
HOM interference
The phenomenon in which two indistinguishable photons leave a beam splitter on the same side. A gauge of photons' sameness.
Linear optics
Optics built from parts such as beam splitters and phase shifters in which light does not interact with light.
KLM scheme
The scheme showing that scalable quantum computing is possible with single photons, linear optics and measurement alone (2001).
Measurement-based (one-way) quantum computing
A scheme that prepares a large entangled state in advance and computes just by measuring one qubit after another.
Fusion
An operation that takes one photon from each of two resource states, interferes and measures them, and links the two.
Resource state
A small entangled state that serves as material for computation.
Photon loss
Photons being lost through scattering, absorption and so on. The biggest challenge of photonic quantum computers.
Photon-number-resolving detector (PNR)
A detector that can count the number of photons.
Superconducting nanowire single-photon detector (SNSPD)
A high-efficiency single-photon detector that operates at cryogenic temperature.
Squeezed light
Light whose wave fluctuation is reduced in one direction. Used in the continuous-variable approach.
Homodyne detection
Detection that measures the amplitude of a light wave. Used in the continuous-variable approach.
GKP qubit
A qubit placed in a single light wave in an error-robust form.
Time-domain multiplexing
A way of lining up light pulses in time so one optical system is used repeatedly.
Gaussian boson sampling
The task of sending squeezed light through an interferometer and counting the output photons. Not general-purpose computation.
Claim of quantum advantage
A claim that a specific task is faster than on a classical computer. Classical-side rebuttals may exist.

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14. Claim-to-source audit

Claim in the textBasisType
PsiQuantum (Alexander et al.): dual-rail SPAM 99.98 ± 0.01%, HOM visibility 99.50 ± 0.25%, two-qubit fusion 99.22 ± 0.12%, chip-to-chip 99.72 ± 0.04% (conditional on detection, not accounting for loss), 300 mm silicon photonics, SNSPDs (NbN about 5 nm, about 90 nm wide, about 2 K), pump suppression 99.1 ± 1.2 dB and about 115 dB, next-generation parts (SiN, BTO, PNR detectors, fiber coupling, fabrication-tolerant photon sources)Alexander et al. (text of the arXiv version, abstract of the Nature paper)
Reference 6 https://doi.org/10.1038/s41586-025-08820-7		Sourced
Aghaee Rad et al. (Xanadu): 35 chips, 84 squeezers, 36 PNR detectors, 12 physical-qubit modes per clock, a cluster state over 86.4 billion modes, a distance-2 repetition code, a "sub-performant scale model," most components at room temperature, optical loss as the dominant and most challenging hurdleAbstract on the Nature paper page
Reference 2 https://doi.org/10.1038/s41586-024-08406-9		Sourced
Larsen et al. (Xanadu): GKP states on a silicon nitride chip (300 mm wafer, multilayer), negative Wigner-function regions in a 3×3 grid, possibly reaching the fault-tolerant regime after further loss reductionAbstract on the Nature paper page
Reference 11 https://doi.org/10.1038/s41586-025-09044-5		Sourced
Maring et al. (Quandela): quantum-dot photon source, a reconfigurable optical chip, one-, two- and three-qubit gates at 99.6 ± 0.1%, 93.8 ± 0.6% and 86 ± 1.2%, and the advantages of photonics (low decoherence, modest cryogenic requirements)Abstract on the Nature Photonics paper page
Reference 1 https://doi.org/10.1038/s41566-024-01403-4		Sourced
The KLM scheme (2001), measurement-based quantum computing (2001), fusion-based quantum computation (a ballistic scheme tolerating 10.4% loss per fusion), the review of photonic quantum computing, and Bourassa et al. (a design for a room-temperature photonic computer)Bibliographic records and abstracts
Reference 4 https://doi.org/10.1038/35051009
Reference 7 https://doi.org/10.1103/PhysRevLett.86.5188
Reference 5 https://doi.org/10.1038/s41467-023-36493-1
Reference 3 https://doi.org/10.1103/RevModPhys.79.135		Sourced
Konno et al.: a GKP state in propagating light at a telecom wavelength, homodyne measurement without loss correction, room temperature and atmospheric pressure. Asavanant et al.: a time-domain-multiplexed two-dimensional cluster state. RIKEN's optical team: final goal and time-domain multiplexing. JST Moonshot: a large-scale machine operating at room temperature by 2050, the 2030 milestone, a superconducting photon-number discriminatorAbstracts of each paper, and the official pages of RIKEN and JST (checked 16 October 2026)
Reference 10 https://doi.org/10.1126/science.adk7560
Reference 8 https://doi.org/10.1126/science.aay2645
Reference 9 https://www.riken.jp/en/research/labs/rqc/opt_qtm_comput_res/
Reference 36 https://www.jst.go.jp/moonshot/en/program/goal6/64_furusawa.html		Sourced
Zhong et al. (Jiuzhang): 50 squeezed-light inputs, 100 modes, 100 detectors, 76 photons, 10¹⁴ times. Madsen et al. (Borealis): 216 modes, over 9,000 years versus 36 μs, earlier photonic experiments vulnerable to spoofing. Oh et al.: classical tensor-network simulation, complexity falls with high loss, calling the advantage claim into question. Aaronson and Arkhipov: boson sampling is not believed to be universalAbstracts of each paper
Reference 37 https://doi.org/10.1126/science.abe8770
Reference 38 https://doi.org/10.1038/s41586-022-04725-x
Reference 12 https://doi.org/10.1038/s41567-024-02535-8
Reference 39 https://arxiv.org/abs/1011.3245		Sourced
DiVincenzo's framework of five requirements (plus two on communication)Abstract and text of DiVincenzo (2000)
Reference 41 https://arxiv.org/abs/quant-ph/0002077		Sourced
Existence and titles of the original randomized-benchmarking papers (Knill et al.; Magesan et al.)Bibliographic records (checked via Crossref / the publisher's page)
Reference 42 https://doi.org/10.1103/PhysRevA.77.012307
Reference 43 https://doi.org/10.1103/PhysRevLett.106.180504		Sourced
Titles and abstracts of the papers on quantum volume, EPLG, CLOPS, capability measurement and the benchmarking surveyAbstracts of each paper
Reference 45 https://doi.org/10.1103/PhysRevA.100.032328
Reference 29 https://arxiv.org/abs/2311.05933
Reference 46 https://arxiv.org/abs/2110.14108
Reference 47 https://doi.org/10.1038/s41567-021-01409-7
Reference 48 https://doi.org/10.1088/2058-9565/ae4269		Sourced
Number, title and publication date of ISO/IEC 4879:2024 (first edition, May 2024, published)ISO page
Reference 40 https://www.iso.org/standard/80432.html		Sourced
IEEE P7130 and P7131 exist as IEEE projects (we treat their status as project stage and do not call them settled standards)Listing in the StandICT.eu standards repository (the IEEE page itself could not be retrieved)
Reference 49 https://standict.eu/standards-repository/p7130-standard-quantum-technologies-definitions
Reference 44 https://standict.eu/standards-repository/p7131-standard-quantum-computing-performance-metrics-performance-benchmarking		Not yet confirmed
Facts on other approaches (the four-approach table): the review by Krantz et al., Willow and IBM, ions such as Helios and Ballance et al., neutral atoms such as Evered et al., and othersAbstracts, texts and official pages
Reference 13 https://doi.org/10.1063/1.5089550
Reference 31 https://doi.org/10.1038/s41586-024-08449-y
Reference 32 https://doi.org/10.1038/s41586-025-09687-4
Reference 33 https://doi.org/10.1140/epjqt/s40507-019-0072-0
Reference 34 https://arxiv.org/abs/2012.08475
Reference 19 https://www.ibm.com/quantum/technology
Reference 14 https://doi.org/10.1063/1.5088164
Reference 15 https://doi.org/10.1038/s41586-026-10676-4
Reference 20 https://doi.org/10.1103/PhysRevLett.82.1971
Reference 21 https://doi.org/10.1103/h4wk-v31j
Reference 26 https://doi.org/10.1103/PhysRevLett.117.060504
Reference 27 https://doi.org/10.1038/s41586-020-2823-6
Reference 16 https://doi.org/10.1038/s41586-023-06481-y
Reference 17 https://doi.org/10.1038/s41586-023-06438-1
Reference 18 https://doi.org/10.1103/66s8-jj18
Reference 22 https://doi.org/10.1103/RevModPhys.82.2313
Reference 25 https://doi.org/10.1038/s41586-025-09641-4
Reference 30 https://doi.org/10.1038/s41586-022-04592-6
Reference 28 https://doi.org/10.1038/s41586-025-09848-5
Reference 35 https://doi.org/10.1038/s41586-025-09596-6
Reference 23 https://doi.org/10.1103/RevModPhys.93.025005
Reference 24 https://doi.org/10.1038/nature02851
Reference 29 https://arxiv.org/abs/2311.05933		Sourced
Total loss by 1−(1−ℓ)ⁿ (0.1%: 100 components give 9.5% and 200 give 18.1%; the numbers of components reaching 10.4% are about 110, 22 and 11)Our calculation (Python; inputs are conceptual examples; 10.4% is Bartolucci et al.'s value)Our calculation
Explanations, analogies and the materials engineer's views such as "photons pass through each other," the explanation of HOM interference, "a photon keeps travelling," "loss sways the value of gates," materials and shielding issues, and "boson sampling is not general-purpose," plus the "In three lines" and "common misconception" boxesThis article's organization and commentary based on published content (our own explanation). Not views expressed by the institutions concernedCommentary
Figures 1 and 11 being ImageGen-generated conceptual illustrations; the other figures being drawings made to explain, not observations of real dataA note in this article (our own)Commentary
Not confirmed: the full texts of ISO/IEC and IEEE standards, the IEEE official pages, any standard specific to photonic quantum computers, reproductions of company teams' results by other laboratories, loss budgets, companies' roadmaps, and achievement of the Moonshot goalsCould not be confirmed in the primary sources accessible within this study, so not stated (our own)Commentary

Last updated: 16 October 2026. Sources are limited to primary ones (peer-reviewed papers, arXiv papers, and the official pages of ISO, RIKEN and JST). The standards' full texts are paid and were not read. The loss calculation is our own feel-for-the-size example, not the loss of any real machine. We could not confirm reproductions of company teams' results by other laboratories, the IEEE official pages, loss budgets, companies' roadmaps, or achievement of the Moonshot goals, so we do not state them. All figures are explanatory concept diagrams or drawings that include our own calculations; Figures 1 and 11 are ImageGen-generated conceptual illustrations.

Illustration update: 17 October 2026. References to vector drawings in the article and source tables describe the retained original SVGs. See each current caption for the foreground image format and reading guide. ImageGen illustrations are not measurements or photographs of actual products; original SVGs, values and sources remain available in expandable references.
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