Quantum Information Processing, Sensing and Communications: Their Myths, Realities and Futures

Balint Koczor; Daryus Chandra; Ivan B. Djordjevic; Lajos Hanzo; Mohsen Razavi; Osvaldo Simeone; Soon Xin Ng; Zhenyu Cai; Zunaira Babar

REVIEW 1 major objections 6 minor 300 references

Quantum Information Processing, Sensing and Communications: Their Myths, Realities and Futures

T0 review · 1 major / 6 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read Quantum error mitigation works only when circuits have about one removable error per run, because its sampling overhead grows exponentially with the errors it removes — so scalable quantum computing still needs error correction.

desk verdict A useful but uneven survey; the QEM overhead claim is qualitatively right but the e^λ formula is off by a factor of two in the exponent, and the copyedit needs serious work. read the letter →

arxiv 2412.00987 v1 pith:KYKCCPNN submitted 2024-12-01 quant-ph cs.ITmath.IT

Lajos Hanzo , Zunaira Babar , Zhenyu Cai , Daryus Chandra , Ivan B. Djordjevic , Balint Koczor , Soon Xin Ng , Mohsen Razavi

show 1 more author

Osvaldo Simeone

This is my paper · ORCID

classification quant-phcs.ITmath.IT MSC 81P6881P45

keywords quantumerrormitigationcorrectionsamplingoverheadcircuitfaultratekeydistributionmachinelearningradarinternetroadmap

verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper is a critical tour of quantum information processing, sensing, and communications, organized around separating myths from practical realities. Its load-bearing technical claim concerns quantum error mitigation (QEM): the sampling overhead of any QEM technique grows exponentially with the number of circuit errors it removes, so in practice QEM is usable only when the expected number of removable errors per circuit run is on the order of one (λ ≈ 1). If that boundary holds, near-term quantum computing should concentrate error mitigation on shallow, low-noise circuits, while any scalable path still requires quantum error correction. The same critical lens is applied to quantum machine learning (limited by data-encoding costs), quantum radar (marginal demonstrated advantages at microwave frequencies), and quantum key distribution (already commercial, but global reach requires a phased move from trusted relays to quantum repeaters). The payoff of getting these boundaries right is an honest roadmap: which quantum technologies are deployable now, which are next, and which require fault tolerance.

What carries the argument

The engine of the argument is the circuit fault rate λ = Np (number of gates times per-gate error rate) combined with a Poisson error count, for which the probability of ℓ errors in a run is $e^{{-λ}}$λ^ℓ/ℓ! and the fraction of noise-free runs is $e^{{-λ}}$. Because a QEM technique removes only a specific subset of errors, the sampling overhead scales as ~$e^{{λ_rm}}$, where λ_rm is the average number of removable errors; this single identity places the practical boundary at λ ≈ 1 and turns the QEM-versus-QECC tradeoff into a quantitative one. The same tradeoff analysis reappears in QKD, where the key-rate-versus-distance curve set by 0.2 dB/km fiber attenuation drives the phased roadmap from trusted relays to measurement-device-independent and satellite links, and eventually to quantum repeaters.

What would settle it

On a real device, count the circuit runs a chosen QEM technique needs to reach a fixed target precision in an expectation value while scaling the circuit's fault rate λ = Np upward by adding gates of known error rate. If the required sample count grows roughly as $e^{{λ}}$, the exponential-overhead claim holds; polynomial or flat growth at λ well above 1 would move the boundary far beyond what the paper asserts. A complementary check is to record the empirical per-run error-count distribution: if it deviates measurably from a Poisson law with the predicted λ, for instance through crosstalk or leakage, the $e^{{-λ}}$ estimate underlying the bound no longer applies.

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Extended reading notes

Core claim

The paper's central assessment is that decoherence can be countered in two complementary ways that trade qubit overhead against measurement overhead. Quantum error correction codes are scalable in principle but currently demand more physical qubits and fault-tolerant operations than near-term hardware can support, and today's implementable codes sit far from the hashing bound. Quantum error mitigation runs on existing devices but only removes errors on average: for stochastic errors with circuit fault rate λ = Np, the fraction of clean circuit runs is $e^{{-λ}}$, so capturing the information of one noiseless run costs roughly $e^{{λ_rm}}$ noisy runs, where λ_rm is the number of errors the technique actually removes. The paper concludes that QEM is therefore practical only when λ_rm is of order one or lower, that this is why recent 100+ qubit demonstrations concentrate on shallow circuits and carefully chosen observables, and that the early fault-tolerant era will combine QECC plus QEM, with coding suppressing the error rate and mitigation cleaning up the residue.

Load-bearing premise

The load-bearing premise is that circuit errors behave as independent stochastic events following a Poisson distribution with fault rate λ = Np, and that each QEM technique removes a well-defined subset of errors; in Section III.B.1 the paper itself flags that its overhead figures are upper bounds and that measured overheads can be lower. If real noise is correlated, non-stochastic, or hard to characterize, the λ ≈ 1 operating boundary and the whole QEM-versus-QECC tradeoff shift.

Editorial extensions

If this is right

Because the sampling overhead is ~e^{λ_rm}, error mitigation effort should be concentrated on shallow circuits whose total fault rate λ = Np is at or below about one.
QEM cannot scale to arbitrary system sizes; only quantum error correction offers a scalable path, so QEM is a complement to QECC rather than a replacement.
In the early fault-tolerant era the two will be combined: QECC first reduces the qubit error ratio, and QEM then cleans up residual errors without triggering avalanche-like error proliferation.
QKD networks will advance through three phases — trusted relays in service today, then measurement-device-independent, memory-assisted, and satellite links that reduce trust, and finally trust-free networks built on quantum repeaters.
The paper's reality check for near-term hardware is that uncontrolled errors severely limit practical applicability; 100+ qubit devices are not yet enabling useful applications on their own, and practical quantum advantage remains to be demonstrated.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

If the λ ≈ 1 boundary holds, it doubles as a hardware roadmap: halving per-gate error rates p roughly doubles the circuit depth that error mitigation can tolerate, giving device engineers a quantitative near-term target.
The Poisson assumption is the most testable link in the chain: real devices show crosstalk, leakage, and non-Markovian noise, and if error counts are super- or sub-Poissonian, the e^{λ} overhead estimate — and the operating boundary built on it — shifts accordingly.
The overhead analysis implies that mitigation costs depend on the measured observable; the paper's own caveat about lower actual overheads suggests that problem formulations keeping observables local will stretch how far mitigation can go on near-term hardware.
Applied to adjacent topics the paper only touches, such as terahertz-band quantum links or quantum-secured direct communication, the same move of locating a quantitative resource boundary would help separate engineering from hype.

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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Desk Editor's Note

read the letter

Colleague,

This is a survey and roadmap document, not a research contribution. Its value is in the synthesis: the QEM section lays out the exponential sampling overhead argument clearly, and the three-phase QKD roadmap (trusted nodes, partially trusted, trust-free) is a plausible framework for planning and standardization. The Myth/Reality/Future framing is a good editorial choice for a broad readership.

The strongest technical claim is in Section III.B.1: QEM sampling overhead grows exponentially with the number of removable errors, so the practical operating regime is roughly λ ≈ 1. The qualitative conclusion — exponential scaling, no scalable QEM, eventual need for QECC — is correct and standard. But the e^λ formula is a heuristic based on the probability that a run has no errors. For PEC with independent depolarizing gates the exact overhead is ∏ ||N_i^{-1}||_1 ≈ e^{2λ}, not e^λ. That shifts the practical boundary down to λ ≲ 0.5. The paper even cites cases where actual overheads are lower than worst-case bounds, so the argument is not internally inconsistent; it is just quantitatively loose. This should be corrected in revision.

The soft spots are mostly editorial but real. The D-Wave qubit count is outdated (2048 was several generations ago). Cross-references to the QML section point to Section III instead of Section IV. There are garbled equations and pervasive typos. The state-of-the-art sections lean heavily on the authors' own prior work — quantum turbo codes, EA radars, the QKD roadmap. That is not disqualifying in a survey, but independent citations would inspire more confidence.

Who is this for? Someone who wants a high-level map of quantum communications, error mitigation, and QKD deployment. It is not for someone seeking rigorous derivations or new protocols. As a planning document, it is useful, and it is likely to be widely cited.

Recommendation: send it to peer review. It deserves referee time because it is important as a synthesis, but the referee should require a corrected QEM overhead derivation and a serious copyedit before publication.

Referee Report

1 major / 6 minor

Summary. This manuscript is a broad survey of quantum information processing, sensing, and communications, organized around a 'Myth, Reality, Future' structure. It reviews quantum error correction codes and their classical precursors, quantum error mitigation without coding, quantum machine learning, quantum radar (with emphasis on entanglement-assisted schemes), quantum key distribution networks, and a roadmap toward quantum-aided wireless systems. The paper's central technical assessment, stated in Section III.B.1, is that the sampling overhead of quantum error mitigation grows exponentially with the number of removable errors, making QEM practical only when the circuit fault rate is on the order of λ ≈ 1 or lower; this is used to argue that QEM is a near-term bridge and that scalable quantum computing still requires quantum error correction. The survey also identifies knowledge gaps, provides historical timelines, and proposes a phased QKD network roadmap.

Significance. If the QEM overhead assessment is correct, it provides a concrete and practically relevant boundary for where error mitigation is useful on near-term devices, and it sharpens the QEM-versus-QECC tradeoff. The survey's strengths are its breadth, the accessible 'Myth/Reality/Future' framing, the extensive timelines, and the explicit enumeration of open research challenges. The paper also states important caveats, including that reported overheads are upper bounds and that actual overheads can be lower for some techniques. No machine-checked proofs or reproducible code are claimed, which is appropriate for a survey, but the QEM overhead claim functions as a falsifiable quantitative prediction and deserves precise derivation. The overall contribution is a useful roadmap document for a communications-engineering audience, provided the central quantitative claim is corrected.

major comments (1)

[III.B.1] The derivation of the sampling overhead as ∼ e^{λ_rm} is a post-selection argument, not a derivation for general QEM. The paragraph infers the overhead from the Poisson probability e^{-λ_rm} that a run is error-free, but PEC, ZNE, and purification-based methods combine all runs rather than retaining only error-free ones. For PEC with N independent gates each having bit-flip or depolarizing error probability p, the exact overhead is ∏ ||N_i^{-1}||_1 = (1+2p)^N ≈ e^{2Np} = e^{2λ_rm}, that is, a factor of 2 in the exponent. Consequently, the stated operating boundary 'λ ≈ 1 or lower' should be corrected to approximately λ ≲ 0.5 for PEC-style methods, or the e^{λ_rm} formula should be explicitly restricted to post-selection-based techniques. The qualitative conclusion that QEM overhead is exponential and hence not scalable is unchanged, but the quantitative boundary in this section is load-bearing and needs revision.

minor comments (6)

[I.A] The statement that the most capable D-Wave quantum computer 'only handles 2048 qubits' is outdated as of the manuscript's December 2024 submission; D-Wave Advantage systems have more than 5000 qubits. Please update the specification and correct 'DWave' to 'D-Wave'.
[III.A.1] The text says 'such as in certain QML applications discussed in Section III' but the QML discussion is in Section IV; likewise, Section III.A.6 refers to 'the subject of Section III' for QML, and Section III.B.2 repeats this error. All internal cross-references to the QML section should be corrected to Section IV.
[III.B.1] The sentence 'the effective noise level of the resultant circuit becomeλ−λ_rm' is garbled; it should read 'becomes λ − λ_rm.' Please proofread this passage and the surrounding equations for rendering errors.
[VI] Several typographical errors appear in the QKD introduction, including 'appied,' 'excersized,' 'lomng-haul,' and 'Helsinke.' A thorough proofreading pass across the manuscript is needed.
[V.B] The claim of an 'approximately 20 percent advantage' in the recent microwave quantum illumination experiment is under-specified. Please state the metric (e.g., error probability, SNR, or detection advantage) and provide the precise numerical result from the cited reference.
[VII.H] The closing sentence 'Valued Colleague, join this community-effort, which is dedicated to solving the suite of open problems touched upon in this treatise!' is an unusual exhortation for a technical survey and should be removed or rewritten in a neutral academic tone.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the QEM overhead estimate is a stated heuristic from a Poisson noise model, and the survey's self-citations are not load-bearing.

full rationale

The paper's central technical claim, the exponential QEM sampling overhead in Section III.B.1, is derived from an explicitly stated stochastic-noise model: the circuit fault rate is lambda = Np, the number of errors is Poisson-distributed, and the noiseless fraction is e^{-lambda}, from which the paper infers an overhead of approximately e^{lambda_rm}. This is a heuristic post-selection argument, and it may quantitatively underestimate the exact PEC overhead by a factor of two in the exponent, but it is not circular: the overhead is not defined as e^{lambda_rm} by construction, and it is not fitted to data or imported from the authors' prior work. The paper also explicitly notes the bound is an upper bound and that actual overheads can be lower, citing external work. The survey does contain many author-affiliated citations, notably for quantum turbo codes [3,4,69], entanglement-assisted radars [242-244,263], and QKD roadmaps [307,360], but these appear in state-of-the-art summaries and roadmap proposals rather than as load-bearing premises of the paper's main derivations. No equation in the paper reduces to its own input, no fitted parameter is renamed as a prediction, and no uniqueness claim is imported from the authors' prior results. The paper is a broad survey with independent technical content, so the appropriate finding is no significant circularity.

Assumptions & free parameters 0 free parameters · 5 assumptions · 0 invented entities

No free parameters or new entities are introduced because the paper is a survey. The central QEM claim relies on the stated axioms, while the roadmap's timelines and cited experimental point estimates are taken from prior literature without independent fitting.

assumptions (5)

domain assumption Decoherence can be modeled as a Pauli channel with bit-flip and phase-flip errors derived from amplitude and phase damping.
Section II.A introduces this as the foundation for QECC analysis; real devices also suffer leakage, crosstalk, and non-Markovian noise not captured by the Pauli model.
domain assumption QEM sampling overhead is governed by a Poisson error model with circuit fault rate λ = Np.
Section III.B.1 estimates the noiseless fraction as e^−λ and the overhead as roughly e^{λ_rm}; the paper notes this is a simplified upper bound and actual overheads can be lower.
domain assumption Security of QKD follows from no-cloning and measurement collapse, provided devices are implemented appropriately and characterized.
Sections VI.A and VI.B.4 assume ideal behavior or calibrated devices; implementation attacks such as Trojan horse require additional leakage modeling.
domain assumption Quantum illumination advantage bounds are valid only asymptotically and at high SNR.
Section V.A.2 states the quantum Chernoff bound was shown valid only for high SNR [242]; the survey uses these bounds to benchmark radar advantages.
standard math Standard quantum error correction results, including the hashing bound and stabilizer formalism, are taken as background.
Sections II.A and II.B use C_Q(p) = 1 − H2(p) − p log2 3 and the symplectic product condition without proof, relying on cited literature.

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Cite this review

Pith. "Pith review of Quantum Information Processing, Sensing and Communications: Their Myths, Realities and Futures." pith.science (2026). https://pith.science/paper/KYKCCPNN

@misc{pith2026241200987,
  author       = {Pith},
  title        = {Pith review of: Quantum Information Processing, Sensing and Communications: Their Myths, Realities and Futures},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/KYKCCPNN}},
  note         = {Machine review of arXiv:2412.00987}
}

read the original abstract

The recent advances in quantum information processing, sensing and communications are surveyed with the objective of identifying the associated knowledge gaps and formulating a roadmap for their future evolution. Since the operation of quantum systems is prone to the deleterious effects of decoherence, which manifests itself in terms of bit-flips, phase-flips or both, the pivotal subject of quantum error mitigation is reviewed both in the presence and absence of quantum coding. The state-of-the-art, knowledge gaps and future evolution of quantum machine learning are also discussed, followed by a discourse on quantum radar systems and briefly hypothesizing about the feasibility of integrated sensing and communications in the quantum domain. Finally, we conclude with a set of promising future research ideas in the field of ultimately secure quantum communications with the objective of harnessing ideas from the classical communications field.

Figures

Figures reproduced from arXiv: 2412.00987 by the authors.

**Figure 1.** Stylized vision of the Quantum Internet of the near future, which will rely on a combination of both classical and quantum devices ©Chandra [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗

**Figure 2.** Paper structure. binary linear classical codes. This framework laid the foundation of the well-known family of Calderbank-Shor-Steane (CSS) codes, which allows constructing an [n, k1 − k2] CSS code from a pair of classical linear block codes C1(n, k1) and C2(n, k2), provided that C2 ⊂ C1. The code C1 is exploited for bit-flip error correction, while the dual of code C2, denoted as C ⊥ 2 , is used for phase-flip err… view at source ↗

**Figure 3.** Transition of error correction codes from the classical to the quantum domain [ [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗

Figures from the paper (30 more)

**Figure 4.** Figure 4: Achievable performance at a word error rate (or frame error rate) of [PITH_FULL_IMAGE:figures/full_fig_p007_4.png]

**Figure 6.** Figure 6: The taxonomy of quantum stabilizer codes based on their binary [PITH_FULL_IMAGE:figures/full_fig_p007_6.png]

**Figure 7.** Figure 7: Timeline of quantum error-correction codes milestones (continued). [PITH_FULL_IMAGE:figures/full_fig_p008_7.png]

**Figure 8.** Figure 8: Timeline of quantum error-correction codes milestones. [PITH_FULL_IMAGE:figures/full_fig_p009_8.png]

**Figure 9.** Figure 9: Quantum error mitigation (QEM) techniques require drastically fewer [PITH_FULL_IMAGE:figures/full_fig_p012_9.png]

**Figure 10.** Figure 10: Timeline of quantum error mitigation milestones. [PITH_FULL_IMAGE:figures/full_fig_p013_10.png]

**Figure 11.** Figure 11: Purification-based techniques prepare n copies of a noisy quantum state ρ either by splitting an array of qubits into batches [146] or by using multiple quantum cores for state preparation [151]. A derangement Dn is a generalisation of the SWAP gate which applies a pe…

**Figure 12.** Figure 12: Possible applications of QML (adapted from [ [PITH_FULL_IMAGE:figures/full_fig_p018_12.png]

**Figure 14.** Figure 14: QML architectures for (Top:) classical data, quantum computing; and (Bottom:) quantum data and quantum computing. being quantum are the domain of QML. While processing quantum data for, e.g., chemistry and biology, is widely considered to be most promising in the long…

**Figure 15.** Figure 15: (Top:) General form of a hardware-aware ansatz; and (Bottom:) example of an entangling gate. measurement statistics average 1. Initialize parameter of the PQC 2. Estimate measurement statistics classical optimizer quantum computer 4. Update the parameters of the PQC 3…

**Figure 16.** Figure 16: Illustration of the process of training a PQC. [PITH_FULL_IMAGE:figures/full_fig_p019_16.png]

**Figure 17.** Figure 17: Timeline of quantum machine learning milestones (limiting the survey to variational quantum algorithms based on parameterized quantum circuits). [PITH_FULL_IMAGE:figures/full_fig_p021_17.png]

**Figure 18.** Figure 18: The general architecture of a hybrid classical-quantum model for [PITH_FULL_IMAGE:figures/full_fig_p022_18.png]

**Figure 19.** Figure 19: Illustration of the single photon monostatic quantum radar concept. [PITH_FULL_IMAGE:figures/full_fig_p023_19.png]

**Figure 20.** Figure 20: Illustration of the entanglement based bistatic quantum radar concept. [PITH_FULL_IMAGE:figures/full_fig_p024_20.png]

**Figure 23.** Figure 23: The optical parametric amplifier (OPA)-based receiver. [PITH_FULL_IMAGE:figures/full_fig_p025_23.png]

**Figure 24.** Figure 24: The EA monostatic quantum radar (modified from ref. [ [PITH_FULL_IMAGE:figures/full_fig_p026_24.png]

**Figure 27.** Figure 27: The integrated multistatic (MIMO) EA transmitter with transmit [PITH_FULL_IMAGE:figures/full_fig_p027_27.png]

**Figure 28.** Figure 28: The EA receiver corresponding to the l-th forward scattered component. The receive side phase modulator is used to select either in-phase or quadrature component of the corresponding phase-conjugated signal. The photodiode responsivity is set to 1 A/W. (Modified from …

**Figure 29.** Figure 29: The quantum illumination-based radar enabling devices. [PITH_FULL_IMAGE:figures/full_fig_p028_29.png]

**Figure 30.** Figure 30: The timeline describing the quantum radar research activities. [PITH_FULL_IMAGE:figures/full_fig_p029_30.png]

**Figure 31.** Figure 31: Three experiments at the heart of BB84: (a) A single photon does not [PITH_FULL_IMAGE:figures/full_fig_p031_31.png]

**Figure 32.** Figure 32: The conjugate encodings used in our toy model QKD protocol. (a) [PITH_FULL_IMAGE:figures/full_fig_p031_32.png]

**Figure 33.** Figure 33: Timeline of QKD milestones. B. Knowledge Gaps and Challenges 1) The issue of distance: Again, owing to the transmission of weak signals, point-to-point QKD suffers from a channel attenuation of about 0.2 dB/km in fiber and from hostile atmospheric propagation phenome…

**Figure 34.** Figure 34: Schematic view of exchanging secret keys between an indoor wireless [PITH_FULL_IMAGE:figures/full_fig_p034_34.png]

**Figure 35.** Figure 35: Diverse families of QKDPs and typical field trials of quantum networks around the world. [PITH_FULL_IMAGE:figures/full_fig_p036_35.png]

**Figure 36.** Figure 36: The schematic of a trusted node QKD network. In order for users A [PITH_FULL_IMAGE:figures/full_fig_p036_36.png]

**Figure 37.** Figure 37: The schematic of a partially trusted QKD network. We exchange [PITH_FULL_IMAGE:figures/full_fig_p038_37.png]

**Figure 38.** Figure 38: A next-generation quantum-secured wireless system vision. The integration of QECC os Section [PITH_FULL_IMAGE:figures/full_fig_p039_38.png]

**Figure 39.** Figure 39: Petahertz band ©Xu et al. [406] detailed by Xu et al. [406], but these bands deserve further exploration in the context of quantum communications. The most mature solutions can be found in the realms of visible light communications. Xu et al. [406] also survey their …

Discussion (0). Continue with ORCID to comment.

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Pith tools

Reviewed August 12, 2026 · model on record in the stance chip above.

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