QISS classically samples a pairwise model built from O(N) low-weight QAOA correlators and outperforms standard QAOA at larger depths on MaxCut and MIS benchmarks.
The Overlap Gap Property and Approximate Message Passing Algorithms for $p$-spin models
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abstract
We consider the algorithmic problem of finding a near ground state (near optimal solution) of a $p$-spin model. We show that for a class of algorithms broadly defined as Approximate Message Passing (AMP), the presence of the Overlap Gap Property (OGP), appropriately defined, is a barrier. We conjecture that when $p\ge 4$ the model does indeed exhibits OGP (and prove it for the space of binary solutions). Assuming the validity of this conjecture, as an implication, the AMP fails to find near ground states in these models, per our result. We extend our result to the problem of finding pure states by means of Thouless, Anderson and Palmer (TAP) based iterations, which is yet another example of AMP type algorithms. We show that such iterations fail to find pure states approximately, subject to the conjecture that the space of pure states exhibits the OGP, appropriately stated, when $p\ge 4$.
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quant-ph 1years
2026 1verdicts
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Quantum-informed surrogate sampling for combinatorial optimization
QISS classically samples a pairwise model built from O(N) low-weight QAOA correlators and outperforms standard QAOA at larger depths on MaxCut and MIS benchmarks.