QAOA for random k-SAT derives efficacy from an adiabatic manifold that supports rigorous performance guarantees at depth Θ(n²) and sublinear parameter optimization via SAMP at depth O(n).
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Mechanism of Efficacy in QAOA for Random k-SAT: From Adiabatic Manifold to Sublinear Parameter Optimization
QAOA for random k-SAT derives efficacy from an adiabatic manifold that supports rigorous performance guarantees at depth Θ(n²) and sublinear parameter optimization via SAMP at depth O(n).