Quantum multi-programming for Grover’s search

Quantum multi-programming is a method utilizing contemporary noisy intermediate-scale quantum computers by executing multiple circuits concurrently. Despite early research on it, the remains gates or small-size algorithms without correlation. In this paper, we propose (QMP) algorithm for Grover’s search. Our decomposes partial diffusion operator and executes decomposed in parallel QMP. We proved that new increases rotation angle of Grover which, as result, success probability. The implemented IBM compared with canonical other variations algorithms. empirical tests validate our outperforms well algorithm.