{ "schema_version": "0.2", "manifest_id": "DEMO-NETLIB-LP-001", "audit_tier": "Standard", "workload": { "identity": "netlib-lp-portfolio-afiro-adlittle-agg", "problem_class": "linear_programming", "inputs": { "format": "MPS", "instance_count": 3, "raw_dimensions": { "afiro": {"rows": 27, "columns": 32, "nonzeros": 83}, "adlittle": {"rows": 56, "columns": 97, "nonzeros": 383}, "agg": {"rows": 488, "columns": 163, "nonzeros": 2410} }, "sparsity": 0.0303, "input_hash": "sha256:08a7065a6cfbf7312eed776d3e0c1c8116c6c4c78c3cc27e5046a94dcbfd8c84" }, "precision_target": "1e-6 relative", "operational_constraints": { "latency": "batch", "explainability": "required for board memo", "re_run_frequency": "one_off", "budget_cycle_context": "ad_hoc" } }, "classical_baselines": [ { "solver": "HiGHS", "version": "1.14.0", "configuration": { "presolve": "on", "solver": "default_dual_simplex", "platform": "Apple silicon, single core" }, "presolve": true, "runtime_seconds": 0.0022633750340901315, "optimality_status": "optimal", "precision_achieved": 1e-9, "baseline_confidence": "strong", "accelerator": "CPU", "notes": "Wall-clock on agg, the largest of the three instances. afiro and adlittle terminated in 0.0217s and 0.000945s respectively. Captured by baselines/run-baseline.py against highspy 1.14.0." }, { "solver": "Clp", "version": "1.17.9", "configuration": { "presolve": "on", "solver": "primal_simplex", "platform": "single-core CPU" }, "presolve": true, "runtime_seconds": 0.05, "optimality_status": "optimal", "precision_achieved": 1e-7, "baseline_confidence": "adequate", "accelerator": "CPU", "notes": "Estimated runtime for agg under Clp 1.17.9 primal simplex. Source: COIN-OR Clp benchmark notes for NETLIB instances at this scale (small LPs solve in tens of milliseconds). No runtime executed in this Audit; the second baseline establishes that the verdict does not hinge on a single solver." } ], "quantum_candidates": [ { "algorithm": "hybrid_QIPM", "formal_model": "binkowski_2026_lp_qipm", "newton_system": "MNES", "cost_drivers": { "sparsity": 0.0303, "condition_number_lower_bound": 10000.0, "qlsa_precision": 1e-6, "output_extraction": "tomography", "state_preparation_cost": "block-encoded coefficient matrix per IPM iteration" }, "assumption_tier": "A", "cycle_lower_bound": 50000000000, "notes": "Modified Newton system (MNES) formulation across the three instances under Tier A benevolent bound. Cycle figure dominated by agg, the largest of the three. Output extraction via tomography over the full primal-dual vector." }, { "algorithm": "hybrid_QIPM", "formal_model": "binkowski_2026_lp_qipm", "newton_system": "OSS", "cost_drivers": { "sparsity": 0.0303, "condition_number_lower_bound": 8000.0, "qlsa_precision": 1e-6, "output_extraction": "tomography", "state_preparation_cost": "block-encoded augmented system per IPM iteration" }, "assumption_tier": "A", "cycle_lower_bound": 30000000000, "notes": "Orthogonal subspaces system (OSS) formulation. Lower condition number than MNES on these instances; cycle bound also dominated by output extraction over the full vector." } ], "assumption_tiers": { "A": { "name": "Benevolent lower bound", "noise": "noise-free", "cycles_per_oracle_call": 1, "ipm_iterations": "lower-bound count from Binkowski 2026", "precision": "favorable", "condition_estimates": "lower-bound from instance structure" } }, "reformulation_log": [ { "step_index": 0, "reformulation": "Replace full primal-dual vector output with a single scalar utility (objective value with a chosen linear functional of the optimum).", "outcome": "tested", "notes": "Reduces output extraction from O(n) tomography to a single amplitude estimation. Documented as a redirect path; not promoted to a route in this demo because the source paper's lower bound assumes full-vector extraction." }, { "step_index": 1, "reformulation": "Block-structured solver path on the constraint matrix, exploiting sparsity below 0.05 across the three instances.", "outcome": "tested", "notes": "Considered as a redirect path for the OSS route. Did not change the Tier A verdict because the dominant term remains output extraction, not Newton-system inversion." } ], "results": [ { "route_id": "lp-qipm-mnes-vs-highs-tier-a", "candidate": "hybrid_QIPM (MNES)", "baseline": "HiGHS 1.14.0", "tier": "A", "cycle_time_to_runtime_seconds": 50000.0, "break_even_cycle_time_seconds": 4.5e-14, "verdict": "REDIRECT", "verdict_sensitivity": [ {"assumption": "output_extraction", "sensitivity": "verdict_flips_if", "threshold": "scalar output (amplitude estimation) instead of full primal-dual vector"}, {"assumption": "condition_number", "sensitivity": "verdict_invariant_to", "threshold": "any kappa within one order of magnitude of 1e4 leaves the verdict at REDIRECT"} ], "redirect_path": "Scalar utility output via amplitude estimation. See reformulation_log step 0.", "notes": "The verdict reflects that 5e10 logical cycles, normalized by a benevolent 1ns-per-cycle assumption, produce wall times five orders of magnitude greater than HiGHS at the workload scale." }, { "route_id": "lp-qipm-oss-vs-highs-tier-a", "candidate": "hybrid_QIPM (OSS)", "baseline": "HiGHS 1.14.0", "tier": "A", "cycle_time_to_runtime_seconds": 30000.0, "break_even_cycle_time_seconds": 7.5e-14, "verdict": "REDIRECT", "verdict_sensitivity": [ {"assumption": "output_extraction", "sensitivity": "verdict_flips_if", "threshold": "scalar output instead of full primal-dual vector"}, {"assumption": "condition_number", "sensitivity": "verdict_flips_if", "threshold": "kappa below 1e3 changes the dominant term"} ], "redirect_path": "Block-structured solver path. See reformulation_log step 1.", "notes": "OSS is the structurally cheaper Newton system on these instances but the verdict at Tier A still rests on output extraction." }, { "route_id": "lp-qipm-mnes-vs-clp-tier-a", "candidate": "hybrid_QIPM (MNES)", "baseline": "Clp 1.17.9", "tier": "A", "cycle_time_to_runtime_seconds": 50000.0, "break_even_cycle_time_seconds": 1.0e-12, "verdict": "REDIRECT", "verdict_sensitivity": [ {"assumption": "output_extraction", "sensitivity": "verdict_flips_if", "threshold": "scalar output instead of full primal-dual vector"} ], "redirect_path": "Scalar utility output via amplitude estimation." }, { "route_id": "lp-qipm-oss-vs-clp-tier-a", "candidate": "hybrid_QIPM (OSS)", "baseline": "Clp 1.17.9", "tier": "A", "cycle_time_to_runtime_seconds": 30000.0, "break_even_cycle_time_seconds": 1.7e-12, "verdict": "REDIRECT", "verdict_sensitivity": [ {"assumption": "output_extraction", "sensitivity": "verdict_flips_if", "threshold": "scalar output instead of full primal-dual vector"} ], "redirect_path": "Block-structured solver path." } ], "portfolio_summary": { "instance_count": 3, "excluded_under_tier_A": 0.0, "redirected": 1.0, "monitored": 0.0, "passed": 0.0, "most_sensitive_assumption": "output_extraction", "worst_classical_competitor": "HiGHS 1.14.0", "best_case_quantum_scenario": "OSS Newton system with scalar utility output via amplitude estimation", "recommended_action": "Test the scalar utility output redirect path. Defer full-vector LP/QIPM until logical cycle time falls below 1e-13 seconds at the named precision and the output requirement is reduced from a primal-dual vector to a scalar functional.", "forbidden_generalization": "Verdicts are bounded by this workload, these baselines, and the stated assumption envelope. They do not generalize to all quantum candidates for this problem class." }, "citations": { "primary_methodology": [ { "citation_key": "binkowski_2026_lp_qipm", "full_citation": "Binkowski, Practical lower bounds for hybrid quantum interior point methods in linear programming, arXiv:2604.24362, 2026", "role": "Source paper for the LP/QIPM lower-bound methodology. DeployQuantum did not author this paper. The Audit operationalizes its decision logic into a customer-facing audit workflow.", "license": "arXiv abstract page references CC BY 4.0; associated GitHub repository licence reviewed at runner-publication time.", "applies_to_routes": [ "lp-qipm-mnes-vs-highs-tier-a", "lp-qipm-oss-vs-highs-tier-a", "lp-qipm-mnes-vs-clp-tier-a", "lp-qipm-oss-vs-clp-tier-a" ] } ], "independence_statement": "Informed by published lower-bound analysis of hybrid quantum interior point methods. DeployQuantum did not author that research." }, "sign_off": { "audit_owner": "DeployQuantum", "publication_release": "named_with_release" }, "hash": "sha256:e11a927f69827d5617ee3ce6a8f0838e057f64f7b4786f9ab8746a554129a813" }