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Evidence for effectively constant shot complexity in the quantum approximate optimization algorithm without per-instance optimization
We study a modified fixed-point version of the Quantum Approximate Optimization Algorithm (fpQAOA), where parameters are trained classically on small instances and then transferred to larger problems. Our scheme combines three ingredients: (i) targeting approximate solutions via a prescribed approxi
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