  We demonstrate machine learning assisted design of a two-qubit gate in a
Rydberg tweezer system. Two low-energy hyperfine states in each of the atoms
represent the logical qubit and a Rydberg state acts as an auxiliary state to
induce qubit interaction. Utilizing a hybrid quantum-classical optimizer, we
generate optimal pulse sequences that implement a CNOT gate with high fidelity,
for experimentally realistic parameters and protocols, as well as realistic
limitations. We show that local control of single qubit operations is
sufficient for performing quantum computation on a large array of atoms. We
generate optimized strategies that are robust for both the strong-coupling,
blockade regime of the Rydberg states, but also for the weak-coupling limit.
Thus, we show that Rydberg-based quantum information processing in the
weak-coupling limit is a desirable approach, being robust and optimal, with
current technology.
