Sign-hedged Beam QAOA:Scaling Quantum Optimization Algorithms

arXiv:2611.08646v1 Announce Type: new Abstract: Quantum Approximate Optimization Algorithm (QAOA) encodes a combinatorial objective as an Ising Hamiltonian and alternates cost and mixer operations for p rounds. Recursive QAOA (RQAOA) scales further by using the resulting correlations, whether variables tend to agree or disagree, to eliminate variables one at a time. But each inferred sign is accepted irrevocably, so a single early mistake propagates through every later reduction and can discard the global optimum. As elimination proceeds, residuals shrink while effective edge density typically rises, so later decisions face denser Ising problems, a regime that fully connected Sherrington Kirkpatrick (SK) instances stress test directly.