Where the Quantum Lives in D-Wave Hybrid Portfolio Optimization: An Operational Decomposition Audit

Battle Count: 76

Directly relevant to quantitative portfolio managers evaluating D-Wave hybrid solvers for constrained allocation problems. Provides operational guidance: use CQM over BQM for cardinality-constrained MV problems, report all three timing fields, include matched-budget classical baselines. The financial overlay shows post-projection direct-QPU portfolios underperform 1/N benchmark (Sharpe 1.94 vs 2.22), and CQM objective levels are classically attainable at matched compute. However, the paper is primarily a benchmarking methodology audit rather than a trading strategy paper. Relevant for fintech engineering teams and quantitative researchers benchmarking quantum-assisted portfolio optimization.

Requires access to D-Wave Leap cloud platform (commercial service), Gurobi MIQP solver, and D-Wave Ocean SDK. The audit protocol itself is straightforward (four metrics computed from exposed timing fields and objective values). The theorem proving and density-collapse analysis are mathematically involved but not computationally intensive. The matched-budget Tabu comparison is simple to replicate. Main complexity lies in the experimental design across multiple solver paths, density families, and problem sizes. Reference implementation provided in Python.

All source code, synthetic instance generators with fixed seeds, solver configurations, and processed result JSONLs are publicly available under MIT License on GitHub. Equity data from Kenneth French Data Library is public. However, the paper notes that hybrid backend version strings and per-submission problem IDs were not retained in saved records, limiting cross-version replication. The protocol self-audit (Table 1) shows partial compliance on several items (P1, P3, P5, P6, P7).