Work

Hybrid classical-quantum linear solver using Noisy Intermediate-Scale Quantum machines

Year: 2019

Type: article

Abstract: We propose a realistic hybrid classical-quantum linear solver to solve systems of linear equations of a specific type, and demonstrate its feasibility with Qiskit on IBM Q systems. This algorithm makes use of quantum random walk that runs in [Formula: see text](N log(N)) time on a quantum circuit made of [Formula: see text](log(N)) qubits. The input and output are classical data, and so can be easily accessed. It is robust against noise, and ready for implementation in applications such as machine learning.

Source: Scientific Reports

DOI: 10.1038/s41598-019-52275-6

Authors: Chih-Chieh Chen, Shiue-Yuan Shiau, Ming-Feng Wu, Yuh-Renn Wu

Institutions: Industrial Technology Research Institute, National Center for Theoretical Sciences, Physics Division, National Taiwan University

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,790

Funders: Ministry of Science and Technology, Taiwan, National Taiwan University