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REVIEW 3 major objections 5 minor 53 references

Quantum Computing in Industrial Environments: Where Do We Stand and Where Are We Headed?

T0 review · 3 major / 5 minor · reviewed 2026-08-16 · deepseek-v4-flash

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Pith's one-line read Quantum computing is a viable industrial tool, review concludes

desk verdict A readable survey with a modest outreach tool; the 'viable alternative' claim rests on anecdotes, and the qubit roadmap passage contradicts itself. read the letter →

arxiv 2505.00891 v1 pith:LU624XX6 submitted 2025-05-01 quant-ph cs.ET

Eneko Osaba , Iñigo Perez Delgado , Alejandro Mata Ali , Pablo Miranda-Rodriguez , Aitor Moreno Fdez de Leceta , Luka Carmona Rivas This is my paper · ORCID
classification quant-phcs.ET
keywords quantumcomputingindustrialoptimizationannealinggate-basedcomputerstensornetworksjobshopschedulingbinpackingvehiclerouting
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 review argues that quantum computing is becoming a viable alternative for solving real industrial problems, at least at proof-of-concept scale. Drawing on published studies of bin packing, job-shop scheduling, and route planning, it walks through three computational paradigms—gate-based quantum computers, quantum annealers, and tensor networks—and shows how hybrid classical-quantum methods have produced working solutions on current NISQ hardware. The authors also present a free online demonstrator for the job-shop scheduling problem that lets non-experts run these methods. The paper is careful to note that no true quantum advantage has been demonstrated yet, but it sees the breadth of proof-of-concept results as evidence that the field is moving toward industrial utility.

What carries the argument

The argument is carried by the three computational paradigms it surveys—gate-based quantum computers, quantum annealers, and tensor networks—plus the hybrid classical-quantum design shared by most of the cited applications. In the hybrid approach, a classical routine decomposes the industrial problem (clustering customers, assigning jobs to machines) and the quantum device solves the resulting subproblems, whether through QAOA/VQE circuits, a quantum annealer evolving an Ising Hamiltonian, or a tensor network that represents all candidate solutions and discards infeasible ones. The paper also introduces its own online JSSP demonstrator, which exposes these methods to non-specialist users, as a practical vehicle for the same idea.

What would settle it

Run the hybrid quantum, annealing, and tensor-network methods from the cited studies on standard public benchmark instances of bin packing, job-shop scheduling, or vehicle routing, alongside best-in-class classical solvers; if the classical solvers match or beat them on solution quality and time across the board, the 'viable at proof-of-concept scale' claim would lose its support.

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Extended reading notes

Core claim

The paper's central claim is that quantum computing is emerging as a viable alternative to tackle complex real-world problems 'at least on a proof-of-concept scale.' It grounds this claim in a selection of recent studies: hybrid algorithms on D-Wave annealers solve realistic three-dimensional bin packing and delivery-route problems; QAOA and annealing implementations address job-shop scheduling; and tensor-network methods compress and generate data tensors for combinatorial optimization, including a traveling-salesman network. The authors read this accumulated activity as indicating that NISQ-era devices, while not yet beating classical supercomputers, can already provide value in specific industrial tasks. They further argue that quantum computers are special-purpose devices that will complement, not replace, classical computers.

Load-bearing premise

The conclusion rests on the assumption that the selected proof-of-concept studies are representative of what quantum and quantum-inspired methods can do in real industrial settings, even though the paper itself states that no true quantum advantage has yet been shown and presents no comparison against the best classical solvers.

Editorial extensions

If this is right

  • If the proof-of-concept claim holds, industrial early adopters can already experiment with hybrid quantum methods on real logistics, manufacturing, and scheduling instances without waiting for fault-tolerant hardware.
  • The pattern of results suggests that quantum annealers, despite lacking universality, are the most immediately usable hardware class for combinatorial optimization in industry.
  • Tensor-network methods, being classical, offer a low-risk way to gain experience with quantum-inspired formulations; their successes (e.g., 93% compression of large language models) strengthen the case that quantum-derived approaches can pay off before quantum hardware matures.
  • Continued investment in NISQ-era tools is justified even while the field faces a 'quantum winter' of reduced private funding, since the proof-of-concept work documented here does not depend on fault tolerance.
  • IBM's strategy shift from qubit count to qubit quality and modular coupling implies, if the paper's reading is right, that progress in quantum industrial applications will come from error mitigation and hybrid workflows rather than raw qubit counts.

Reading between the lines

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

  • One implication the authors do not spell out: even without a quantum speedup, hybrid methods may win in practice if the annealer or circuit quickly produces high-quality solutions that a classical local search then refines; this is testable today with open benchmark instances.
  • The survey's case-study selection suggests a concrete experiment: take standard bin-packing or JSSP instances from the literature, run the paper's cited hybrid methods against the best classical solvers, and record time-to-solution and solution quality; the result would quantify the gap the paper leaves open.
  • If the online demonstrator is extended with such classical baselines, it could serve as a neutral testbed for the 'viable at proof-of-concept scale' claim, letting readers see directly where quantum and quantum-inspired methods win or lose.
  • The comparison between China's large public investment and North America's private-investment drop hints that the next industrial quantum advances may be geographically uneven, a trajectory the paper mentions but does not analyze.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 5 minor

Summary. This manuscript is a survey/position paper on the use of quantum computing in industrial environments. It reviews three computational paradigms: gate-based quantum computers, quantum annealers, and tensor networks, and then discusses selected industrial applications including bin packing, job-shop scheduling, and robot/vehicle routing. The paper also describes an online demonstrator for the job-shop scheduling problem developed by the authors, and it concludes with a discussion of vendor roadmaps (IBM and D-Wave), investment trends, and the 'quantum winter' narrative. The central conclusion, stated in Section 3, is that quantum computing is 'emerging as a viable alternative to tackle complex real-world problems, at least on a proof-of-concept scale.'

Significance. As a survey, the paper is useful as an accessible introduction to three computational paradigms and to a curated set of recent industrial applications. Its main value is organizational: it brings together examples from bin packing, scheduling, and routing, and it makes the authors' JSSP demonstrator visible to a wider audience. The paper does not present original benchmark results, and its evidence is selected rather than systematic. Its central claim, that quantum computing is a 'viable alternative' at proof-of-concept scale, is plausible but not established by the cited studies, which lack comparisons against classical solvers. If properly qualified, the survey could serve as a starting point for practitioners, but in its current form the conclusion overreaches relative to the evidence.

major comments (3)
  1. [Section 3, last paragraph] The sentence 'it is prudent to conclude that quantum computing is emerging as a viable alternative to tackle complex real-world problems, at least on a proof-of-concept scale' is the load-bearing claim of the paper, but it is not supported by the evidence presented. None of the cited works is compared against best-in-class classical solvers, and Section 1 itself states that 'there is not yet a true quantum advantage.' The cited studies demonstrate that industrial problems can be encoded and that small instances can be solved, but that is not the same as demonstrating viability, which requires competitive solution quality and runtime on realistic instances. The authors should either qualify the conclusion explicitly, for example by saying that quantum and quantum-inspired methods are 'objects of active research' rather than viable alternatives, or add a critical comparison of quantum/quantum-inspired results with classical baselines on common benchmark instances.
  2. [Section 2.3 and Section 3] The paper introduces tensor networks as 'quantum-inspired' classical methods that run on classical devices, yet in Section 3 it includes tensor-network works [24]-[26] among the evidence for the potential of quantum computing in industry. This conflates quantum-inspired classical computation with quantum hardware: a classical method's success cannot validate the prospects of NISQ hardware. The ambiguity affects the central claim, because the 'viable alternative' conclusion could be read as referring either to genuine quantum computers or to a mix that is largely classical. The paper should consistently distinguish these two categories when drawing conclusions, or explicitly extend the claim to 'quantum and quantum-inspired methods.'
  3. [Section 5, IBM roadmap] The text states that 'projections for the maximum number of next-generation qubits (through modular coupling) have been moderated to 1,092 qubits by 2028,' and then in the same paragraph introduces 'Starling and Flamingo' chips with '200 and 2,000 qubits, respectively.' As written, a 2,000-qubit chip appears to contradict the 1,092-qubit projection. The authors should clarify whether the 1,092 figure applies only to a particular class of modular systems, and they should specify the timeline and system configurations to which each number refers.
minor comments (5)
  1. [Section 4 and Section 5] The figure numbering is inconsistent: the demonstrator page and the IBM roadmap are both numbered Figure 7, and the D-Wave roadmap is numbered Figure 8. The figures should be renumbered sequentially.
  2. [Footnote 2] The footnote repeatedly uses 'cubits' instead of 'qubits'; this typo should be corrected throughout the footnote.
  3. [Section 3, bin packing paragraph] The descriptions of references [29] and [30] appear to be swapped relative to their titles: [30] is 'Aircraft Loading Optimization,' while the text attributes cargo-plane loading to [29] and spent nuclear fuel storage to [30]. Please verify and correct this attribution.
  4. [References] References [49]-[51] are listed in the bibliography but are not cited anywhere in the text; they should either be cited in the relevant discussion of European initiatives or removed.
  5. [Section 3, tensor-network applications] The only tensor-network industrial examples cited in Section 3 are the authors' own papers [24]-[26]. Including independent case studies would strengthen the survey's credibility and reduce the appearance of selection bias.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the survey's conclusion is an editorial inference from a broad literature, with self-citations only descriptive and not load-bearing.

full rationale

This paper is a survey/position article rather than a derivation: it contains no equations, fitted parameters, or predicted quantities. The closest thing to a central claim is Section 3's statement that 'it is prudent to conclude that quantum computing is emerging as a viable alternative to tackle complex real-world problems, at least on a proof-of-concept scale.' That is an inductive editorial inference drawn from the volume and variety of cited studies, not a result derived from those studies by construction. The authors' own prior works (refs [17], [24]–[26], [39]) appear among many external references (e.g., [27], [31], [32], [35]–[38], [40]) and are used descriptively, for example to illustrate tensor-network algorithms and routing applications; the central claim does not rest on those particular works, so the self-citations are not load-bearing. Section 1 explicitly concedes that 'there is not yet a true quantum advantage,' and the conclusion is explicitly qualified as proof-of-concept, so the paper does not present its own results as validated industrial evidence. No fitted parameter is later renamed a prediction, no uniqueness theorem is imported from the authors' prior work, and no ansatz is smuggled in via citation. Any concern that the 'viable alternative' conclusion overreaches because no systematic comparison against best classical solvers is provided is a correctness/evidentiary issue, not a circularity issue under the definitions used here.

Assumptions & free parameters 0 free parameters · 3 assumptions · 0 invented entities

The paper is a survey and introduces no fitted parameters, no new entities, and no derivations. The listed axioms are domain-level assumptions about the NISQ era, the role of quantum computers, and the inclusion of tensor networks as a quantum-computing paradigm.

assumptions (3)
  • domain assumption NISQ devices cannot yet outperform classical supercomputers, but can still solve industrially relevant problems.
    Section 1 states there is 'not yet a true quantum advantage' yet Section 3 concludes quantum computing is a 'viable alternative' on a proof-of-concept scale; this tension is an assumed state of the field rather than demonstrated by the paper.
  • domain assumption Quantum computers are special-purpose devices that will complement, not replace, classical computers.
    Stated in Section 1 footnote and repeated; it underlies the paper's framing of industrial use cases.
  • domain assumption Tensor networks are a valid third computational paradigm for quantum computing, despite being classical algorithms.
    Section 2.3 groups quantum-inspired tensor network methods under 'computational paradigms' of quantum computing, which is a taxonomic assumption.

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Cite this review

Pith. "Pith review of Quantum Computing in Industrial Environments: Where Do We Stand and Where Are We Headed?." pith.science (2026). https://pith.science/paper/LU624XX6

@misc{pith2026250500891,
  author       = {Pith},
  title        = {Pith review of: Quantum Computing in Industrial Environments: Where Do We Stand and Where Are We Headed?},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/LU624XX6}},
  note         = {Machine review of arXiv:2505.00891}
}
read the original abstract

This article explores the current state and future prospects of quantum computing in industrial environments. Firstly, it describes three main paradigms in this field of knowledge: gate-based quantum computers, quantum annealers, and tensor networks. The article also examines specific industrial applications, such as bin packing, job shop scheduling, and route planning for robots and vehicles. These applications demonstrate the potential of quantum computing to solve complex problems in the industry. The article concludes by presenting a vision of the directions the field will take in the coming years, also discussing the current limitations of quantum technology. Despite these limitations, quantum computing is emerging as a powerful tool to address industrial challenges in the future.

Figures

Figures reproduced from arXiv: 2505.00891 by the authors.

Figure 1
Figure 1. Graphic representation of all possible states of a qubit known as the "Bloch Sphere". [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 4
Figure 4. Two examples of solutions to the three-dimensional bin packing problem. Images extracted from [27] Another problem widely addressed from the quantum perspective is the Job-Shop Scheduling Problem (JSSP). This problem, illustrated in [PITH_FULL_IMAGE:figures/full_fig_p005_4.png] view at source ↗
Figure 5
Figure 5. Solution to an example instance of the JSSP consisting of 5 jobs, each defined by 5 tasks with durations ranging fr [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗
Figures from the paper (1 more)
Figure 7
Figure 7. Figure 7: Main page of the demonstrator developed for solving the JSSP problem. [PITH_FULL_IMAGE:figures/full_fig_p007_7.png]

Discussion (0). Continue with ORCID to comment.

Reference graph

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