A Survey of NISQ Era Hybrid Quantum-Classical Machine Learning Research

Authors

  • Gennaro De Luca Arizona State University, USA

DOI:

https://doi.org/10.37965/jait.2021.12002

Keywords:

hybrid quantum-classical, NISQ era, quantum computing, quantum ML

Abstract

Quantum computing is a rapidly growing field that has received a significant amount of support in the past decade in industry and academia. Several physical quantum computers are now freely available to use through cloud services, with some implementations supporting upwards of hundreds of qubits. These advances mark the beginning of the noisy intermediate-scale quantum (NISQ) era of quantum computing, paving the way for hybrid quantum-classical (HQC) systems. This work provides an introductory overview of gate-model quantum computing through the Visual IoT/Robotics Programming Language Environ- ment and a survey of recent applications of NISQ era quantum computers to HQC machine learning.

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Published

2021-12-01

How to Cite

De Luca, G. (2021). A Survey of NISQ Era Hybrid Quantum-Classical Machine Learning Research. Journal of Artificial Intelligence and Technology, 2(1), 9–15. https://doi.org/10.37965/jait.2021.12002

Issue

Section

Research Article