QAOA Inside ADMM: Subproblem Wins Do Not Become Decomposition Wins at Matched Budgets

arXiv:2611.10527v1 Announce Type: new Abstract: We benchmark the quantum approximate optimization algorithm (QAOA) as the binary subproblem solver in a two-block alternating direction method of multipliers (ADMM) for mixed-binary problems against classical solvers under matched budgets. With 23 optimizer evaluations per subproblem, scoring determines the comparison: on its final readout, the optimized QAOA loses to random search at $n=12$ and 16 binary variables (inconclusive at 20; exploratory and post hoc tests). When credited with its best sample, it wins.