Quantum search on noisy intermediate-scale quantum devices

Abstract

The Quantum search algorithm (also known as Grover's algorithm) lays the foundation of many other quantum algorithms. It demonstrates an advantage (for unstructured search) over the classical algorithm. Although it is very simple, its implementation is limited on the noisy intermediate-scale quantum (NISQ) processors. The limitation is due to the circuit depth, rather than the number of qubits. For the first time, we present detailed and completed benchmarks of the five-qubit quantum search algorithm on different quantum processors, including IBMQ, IonQ and Honeywell quantum devices. Besides Grover's algorithm, we also present the implementations of a recently proposed optimized quantum search algorithm [Phys. Rev. A 101, 032346 (2020)]. Noisy simulations are also applied to interpret the results. We report the highest success probability of the five-qubit search algorithm compared to previous works. Our study shows that different quantum processors, with different levels of errors, have different optimal ways to realize the quantum search algorithms. The original Grover's algorithm might not be the best choice. To maximize the power of NISQ computers, designing error-aware algorithms is necessary.