Prospect of using Grover's search in the noisy-intermediate-scale quantum-computer era
arXiv:2006.10037 · doi:10.1103/PhysRevA.102.042609
Abstract
In order to understand the bounds of utilization of the Grover's search algorithm for the large unstructured data in presence of the quantum computer noise, we undertake a series of simulations by inflicting various types of noise, modelled by the IBM QISKit. We apply three forms of Grover's algorithms: (1) the standard one, with 4-10 qubits, (2) recently published modified Grover's algorithm, set to reduce the circuit depth, and (3) the algorithms in (1) and (2) with multi-control Toffoli's modified by addition of an ancilla qubit. Based on these simulations, we find the upper bound of noise for these cases, establish its dependence on the quantum depth of the circuit and provide comparison among them. By extrapolation of the fitted thresholds, we predict what would be the typical gate error bounds when apply the Grover's algorithms for the search of a data in a data set as large as thirty two thousands.
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- Variational Quantum Linear Solver with Dynamic Ansatz
- Scalable estimation of pure multi-qubit states
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- Reduction of circuit depth by mapping qubit-based quantum gates to a qudit basis
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- Grover's search meets Ising models: a quantum algorithm for finding low-energy states
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- Quantum Perceptron Revisited: Computational-Statistical Tradeoffs