For p=1 QAOA on Ising models, the paper derives analytic bandwidth bounds, eliminates the mixer angle to reduce optimization to a one-dimensional line search, and proves that for regular graphs the global optimum coincides with the first local optimum near gamma equals zero.
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Near-Optimal Parameter Tuning of Level-1 QAOA for Ising Models
For p=1 QAOA on Ising models, the paper derives analytic bandwidth bounds, eliminates the mixer angle to reduce optimization to a one-dimensional line search, and proves that for regular graphs the global optimum coincides with the first local optimum near gamma equals zero.