Quantum

Sign-hedged Beam QAOA:Scaling Quantum Optimization Algorithms

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Briefings

A new quantum optimization algorithm called sign-hedged beam RQAOA improves approximation ratios on frustrated spin glasses by evaluating both possible sign assignments after standard recursive steps. On 50+ instances from HamLib and QOBLIB, beam recovers near-optimal AR 0.998 where standard recursion fails at AR 0.474, using classical pruning instead of increasing quantum circuit depth.

Key points

• Sign-hedged beam RQAOA evaluates both possible sign assignments after standard recursive QAOA steps to recover higher approximation ratios.
• On 50+ instances from HamLib and QOBLIB, beam achieves near-optimal AR 0.998 while standard recursion fails at AR 0.474 on similar instances.

Context

Quantum Approximate Optimization Algorithm (QAOA) encodes combinatorial objectives as Ising Hamiltonians and alternates cost and mixer operations for p rounds. Recursive QAOA (RQAOA) scales further by using correlations to eliminate variables one at a time, but early mistakes propagate through every later reduction. This paper proposes sign-hedged beam RQAOA to mitigate these issues.

Limitations

Results are limited to 50+ instances from HamLib and QOBLIB spanning 4 and 5 regular and Erdos Renyi MaxCut graphs, Sherrington Kirkpatrick spin glasses, and cardinality-constrained portfolio optimization. Hardware runs were limited to ibm kingston and ibm marrakesh, and simulator/device agreement is confirmed but not exhaustive.

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