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The original Grover's algorithm has a success probability to output a correctsolution, while deterministic Grover's algorithms improve the successprobability to 100%. However, the success probability of deterministic Grover'salgorithm decreases in noisy environment. Here we improve the deterministictwo-parameter (D2p) Grover's algorithm to reach the upper bound for successprobability under phase noise. We prove that it is not possible to design anydeterministic Grover's algorithm whose success probability is higher than ourimproved D2p protocol's under phase noise.

Improving D2p Grover's algorithm to reach performance upper bound under phase noise