{"id":"f2eae5a5-77cc-4076-b914-e9a64df1f4a4","arxiv_id":"2508.08869","paper_version":1,"verdict":"UNVERDICTED","confidence":"LOW","novelty_score":6.0,"correctness_risk":"unknown","formal_verification":"none","parameter_count":2,"one_line_summary":"Enhanced QAOA and quantum adiabatic solvers with a search-space reduction algorithm claim a scaling advantage over classical solvers on one-in-three SAT, backed by numerics and a 13-qubit experiment.","lead":"This paper claims that new quantum solvers for an NP-complete logic problem, one-in-three SAT, can outperform classical solvers with a scaling advantage. It supports the claim with simulations of up to 65 variables and an experiment on a 13-qubit superconducting processor.","discovery_kind":"new_method","skeptic_critique":{"model":"deepseek-v4-flash","headline":"Scaling advantage hinges on RSRA preprocessing cost being counted and the reduced instances not being classically easy; this is unverifiable in the corrupted full text.","rationale":"The reader's weakest assumption pinpoints the correct load-bearing point: RSRA is the first computational step, and its cost and effect on instance difficulty determine whether any later quantum advantage is genuine. This concern is not a disagreement with consensus; it is a correctness risk that cannot be evaluated from the abstract. The 65-variable numerical range and 13-qubit experiment are too small on their own to establish asymptotic advantage, and without a readable full text the RSRA theorem, baseline selection, and error bars cannot be audited. I do not see a reason to alter the reader's UNVERDICTED status; the concern is unresolved rather than confirmed. If a clean full text confirms that RSRA preprocessing is polynomial and included in the timing comparisons and that reduced instances still challenge strong classical solvers, the concern would be resolved positively. The proposed test isolates exactly that condition.","tokens_in":12382,"tokens_out":4477,"duration_ms":45956,"concrete_test":"Recover a clean copy of the full text and re-derive the RSRA complexity and its role in the comparison. Concretely, re-run the numerical benchmarks (up to 65 variables) with RSRA wall-clock time added to the quantum solver's time-to-solution, then compare against a strong complete SAT solver (e.g., Kissat or CaDiCaL) and a standard local-search solver on the same post-reduction instances. If RSRA preprocessing dominates the scaling, or if the reduced instances are solved classically as fast or faster, the scaling-advantage claim fails.","verdict_should_be":"UNCHANGED","load_bearing_attack":"The central claim—QAA-based enhanced solver exhibits scaling advantage on one-in-three SAT—depends critically on the restricting space reduction algorithm (RSRA). The abstract states RSRA achieves 'optimal search space dimensionality' and reduces both qubits and time complexity, but a load-bearing condition is left unverified: the cost of executing RSRA must be included in total runtime and must remain negligible, and the reduced instances must not be trivially easy for classical solvers. If RSRA performs expensive preprocessing or maps instances to a class where classical solvers are already efficient, the reported quantum scaling advantage would be an artifact of the reduction, not of the quantum algorithm. The provided full text is corrupted (mojibake), so the RSRA complexity analysis, classical baselines, and 65-variable/13-qubit protocols cannot be checked. The abstract alone cannot rule out this alternative explanation.","agreement_with_reader":"agree"},"referee_report":{"model":"deepseek-v4-flash","summary":"The abstract announces enhanced QAOA- and QAA-based solvers for the NP-complete one-in-three SAT problem, supported by a restricting space reduction algorithm (RSRA), numerical studies up to 65 variables, and a 13-qubit superconducting processor experiment. The claimed contributions are: RSRA reduces qubit count and time complexity to an 'optimal search space dimensionality'; the enhanced solvers outperform state-of-the-art classical solvers; and the QAA-based solver provides a lower bound for the method while exhibiting a scaling advantage. However, the submitted manuscript text after the abstract is unreadable mojibake: equations, algorithms, tables, and experimental protocols cannot be recovered. In effect, the paper consists of an abstract plus illegible fragments, so none of the central claims can be verified from the reviewable record.","tokens_in":12594,"tokens_out":4637,"duration_ms":49097,"significance":"If fully substantiated, the paper would be a notable empirical contribution to quantum optimization: it would provide evidence of scaling advantage on a concrete NP-complete problem, with a preprocessing reduction, two quantum solver families, and hardware data. The abstract's modular structure (reduction, solver comparison, hardware validation) is appropriate, and the problem selection is meaningful. However, the submission as provided gives no access to the derivations, numerical baselines, statistical error analysis, or experimental details. I cannot identify any machine-checked proofs, reproducible code, or parameter-free derivations in the legible portion. Therefore the significance—while potentially high—is entirely unsubstantiated in the present text.","major_comments":[{"comment":"The entire body after the abstract is rendered in unreadable mojibake (e.g., sequences of '���������'). Equations, algorithm descriptions, tables, and figure captions cannot be recovered. In particular, no readable statement of the RSRA algorithm, no complexity theorem, and no numerical table are present. Because the central claims depend precisely on these details, the manuscript as submitted cannot support them.","section":"Full text (post-abstract)"},{"comment":"The abstract asserts that RSRA 'achieves optimal search space dimensionality' and reduces both qubits and time complexity, and that the QAA-based solver 'provides a lower bound' for the method. Neither the definition of 'optimal dimensionality' nor the cost of RSRA is verifiable from the text. The stress-test concern is valid: if RSRA's runtime is not counted in the total comparison, or if it maps instances to a class that is easy for classical solvers, then the reported scaling advantage would be an artifact of preprocessing. The manuscript provides no legible analysis to exclude this.","section":"Abstract, RSRA"},{"comment":"The claimed hardware implementation is described only in the abstract. No device identifier, calibration/fidelity data, shot counts, error bars, or comparison protocol are legible. Moreover, the body contains an unrelated arXiv identifier, 'arXiv:2508.08867v1 [cs.CV]', embedded in a page header, indicating that the submitted file is not a clean version of the intended paper. This is a load-bearing integrity problem for the experimental claim.","section":"Experimental section (13-qubit processor)"},{"comment":"The abstract cites 'extensive numerical investigations' on instances with up to 65 variables, but no classical solver names, problem distributions, success metrics, runtimes, or statistical tests are readable. A scaling-advantage claim requires at least multiple trials, error bars, and a definition of the comparison metric (e.g., time-to-solution or total runtime). None of this information is accessible in the submitted text.","section":"Numerical results"}],"minor_comments":[{"comment":"The abstract should specify the state-of-the-art classical solvers used and define 'scaling advantage' operationally (for example, the crossover point in total runtime or time-to-solution) so that the claim is falsifiable.","section":"Abstract"}],"recommendation":"reject","confidential_remarks":"This may be an encoding or file-upload failure rather than a scientific deficiency. If a clean, readable manuscript becomes available, the paper could be reconsidered. But as submitted, the body text is unreadable and no scientific claim can be checked; under the scope of this review, rejection is the only proportionate outcome."},"author_rebuttal":null,"desk_editor":{"model":"deepseek-v4-flash","letter":"What you should know: this paper cannot be evaluated from the supplied full text. What we have is a plausible abstract and a corrupt source file that is unreadable and even carries the header arXiv:2508.08867v1 [cs.CV], not this paper's ID. That is a submission-integrity problem. No one can check the derivations, the numerical methods, the classical baselines, or the 13-qubit experiment from this version. The reader's UNVERDICTED verdict is the only defensible one.\n\nWhat the paper seems to do well: RSRA, the proposed restricting-space reduction, is a new algorithmic idea as far as I can tell, and hitting \"optimal search space dimensionality\" for one-in-three SAT, if real, is useful. Combining it with both QAOA and QAA and benchmarking on a 13-qubit superconducting processor is a legitimate experimental effort. Presenting the QAA solver as a lower bound for QAOA is also a sensible way to structure the comparison. If the details hold, this is meaningful empirical evidence for a scaling advantage on an NP-complete problem, which would be a notable result.\n\nWhere I'm worried: the central claim depends on RSRA's own cost being included in the total runtime and on the reduced instances not becoming classically trivial. That is the natural place for a scaling advantage to leak away. The abstract alone cannot rule that out. I also see no error bars or statistical tests in the abstract, and QAOA variational parameters are fitted per instance, which can mask scaling behavior. These are concerns, not condemnations; I want to see the real text before passing judgment. The classical solver comparison also needs a fair look, because \"scaling advantage\" claims in this literature routinely come down to which classical solver and which instance family you pick.\n\nWho this is for: quantum-optimization researchers and anyone tracking empirical quantum speedup claims. It is worth a serious referee if the authors can provide an intact manuscript. My recommendation: send it back to the authors, ask for a clean, readable source file with the other arXiv header removed, and then send it to referees. This is not a desk reject—if the paper is what it claims to be on the surface, it deserves referee time even if the referee ends up skeptical after reading the details.","headline":"Unverifiable as supplied: full text is corrupted (mojibake, with another arXiv ID embedded), so the scaling-advantage claim for one-in-three SAT rests on the abstract alone.","tokens_in":638,"tokens_out":1005,"would_cite":false,"duration_ms":32435,"reading_group":"maybe","serious_thinker":"unclear","would_accept_peer_review":true},"rs_alignment":null,"lean_confirmation":null,"pith_extraction":{"msc":[],"pacs":["03.67.Lx"],"model":"deepseek-v4-flash","headline":"The paper reports that enhanced quantum solvers—QAOA and QAA with a restricting space reduction step—achieve a scaling advantage over classical solvers for one-in-three Boolean satisfiability, supported by numerical tests up to 65 variables","keywords":["quantum advantage","scaling advantage","QAOA","quantum adiabatic algorithm","one-in-three SAT","NP-complete","restricting space reduction","superconducting processor"],"falsifier":"A direct falsification would be to run a state-of-the-art classical SAT solver directly on the RSRA-reduced instances used in the paper and measure whether its resource growth (e.g., wall-clock time) matches or beats the reported quantum scaling advantage at 65 variables. If the classical solver solves all reduced instances quickly and scales better than the quantum resource counts, the claimed advantage is refuted.","tokens_in":12309,"feed_emoji":"⚛️","tokens_out":3859,"duration_ms":39670,"temperature":0.7,"pith_summary":"The paper tries to establish an empirical scaling advantage of quantum optimization on a classically hard NP-complete problem: one-in-three satisfiability. It introduces a restricting space reduction algorithm (RSRA) that shrinks the search space to its optimal dimension, lowering qubit count and time cost for both a quantum approximate optimization algorithm (QAOA) and a quantum adiabatic algorithm (QAA). Numerical experiments on instances with up to 65 variables show these enhanced solvers outperform leading classical solvers, with the QAA-based solver providing a lower bound and exhibiting scaling advantage. A 13-qubit superconducting processor run confirms the predicted improvements. If correct, this provides one of the first empirical indications that quantum solvers can scale more favorably than classical ones on an NP-complete problem.","feed_headline":"Quantum solvers show scaling advantage on NP-complete SAT","feed_subtitle":"Numerical runs to 65 variables and a 13-qubit experiment back the speedup claim.","key_machinery":"The restricting space reduction algorithm (RSRA), a preprocessing step that provably reduces the search space of a one-in-three SAT instance to its minimal dimension while preserving satisfiability. It is the key mechanism that cuts qubit count and time complexity, making the QAOA and QAA solvers efficient; the reduced problem is then mapped to a cost Hamiltonian whose ground state encodes the solution.","core_discovery":"The central discovery is that a restricting space reduction algorithm (RSRA) applied before quantum encoding reduces the search space of a one-in-three SAT instance to its optimal dimensionality while preserving satisfiability. This preprocessing lowers both the number of qubits and the time complexity of the subsequent QAOA and QAA solvers. Using RSRA, the paper shows numerically on instances with up to 65 variables that its enhanced QAOA and QAA solvers outperform state-of-the-art classical solvers. The QAA-based solver is found to give a lower bound for the method's performance and itself exhibits a scaling advantage. The paper also reports an experimental implementation on a 13-qubit sup","pith_inferences":["If RSRA is classically easy, the real bottleneck for the claimed advantage could shift to whether the reduced instances remain hard for classical algorithms; the paper does not directly test this.","The reduction idea might extend to other constraint-satisfaction problems with ratio-like structure, though the paper only explores one-in-three SAT.","A direct testable extension: run the enhanced solvers on random instances with more variables and compare wall-clock time against the best classical solvers, rather than only query counts.","The scaling advantage window depends on the classical baseline; if classical solvers improve, the observed advantage could shrink or disappear."],"forward_implications":["If the scaling advantage holds, quantum optimization becomes a practical candidate for NP-complete problems at sizes where classical solvers deteriorate.","Because the QAA-based solver provides a lower bound, future improvements to the enhanced solvers can be measured directly against adiabatic evolution.","The RSRA reduction is solver-agnostic, so any quantum solver targeting one-in-three SAT could inherit reduced qubit and time requirements.","The 13-qubit experimental confirmation suggests near-term quantum processors can reproduce the numerical advantage on small instances.","The work reframes the near-term goal from asymptotic separation to scaling advantage, a target achievable on noisy intermediate-scale quantum devices."],"supporting_citations":[],"fun_headline_variants":["RSRA preprocessing boosts quantum solvers to scaling advantage on SAT","Quantum speedup on NP-complete SAT via optimal search-space reduction","13-qubit experiment backs scaling advantage on NP-complete problem","Search-space reduction unlocks quantum scaling advantage on SAT","Enhanced QAOA/QAA beat classical on SAT with search-space trick"],"cache_read_input_tokens":2816,"weakest_assumption_plain":"The load-bearing premise is that the restricting space reduction algorithm is classically cheap and does not transform the problem into an easy instance for classical methods; if either fails, the reported quantum advantage would be an artifact of preprocessing, not a genuine quantum speedup.","fun_headline_variants_meta":{"raw":{"variants":["RSRA preprocessing boosts quantum solvers to scaling advantage on SAT","Quantum speedup on NP-complete SAT via optimal search-space reduction","13-qubit experiment backs scaling advantage on NP-complete problem","Search-space reduction unlocks quantum scaling advantage on SAT","Enhanced QAOA/QAA beat classical on SAT with search-space trick"]},"model":"deepseek-v4-flash","effort":"low","cost_usd":0.00076,"raw_usage":{"total_tokens":3198,"prompt_tokens":719,"completion_tokens":2479,"prompt_tokens_details":{"cached_tokens":256},"prompt_cache_hit_tokens":256,"prompt_cache_miss_tokens":463,"completion_tokens_details":{"reasoning_tokens":2394}},"tokens_in":463,"tokens_out":2479,"duration_ms":17326,"temperature":1.0,"reasoning_tokens":2394,"cache_read_input_tokens":256,"cache_creation_input_tokens":0},"cache_creation_input_tokens":0},"created_at":"2026-08-05T21:19:34.380658+00:00","model_set":{"reader":"deepseek-v4-flash"},"falsifier":"A direct falsification would be to run a state-of-the-art classical SAT solver directly on the RSRA-reduced instances used in the paper and measure whether its resource growth (e.g., wall-clock time) matches or beats the reported quantum scaling advantage at 65 variables. If the classical solver solves all reduced instances quickly and scales better than the quantum resource counts, the claimed advantage is refuted.","supporting_citations":[],"review_version":1}