Quantum Information Processing Algorithms with Emphasis on Machine Learning

Glen S. Uehara, Andreas Spanias, William Clark

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Quantum Computing (QC) promises to elevate computing speed by an estimated 100 million times. Several applications, including signal processing, machine learning, big data, communication, and cryptography, will benefit from quantum computing. This paper provides a brief survey of quantum information processing algorithms with an emphasis on machine learning. We begin first, covering with an introduction to quantum systems. Then we describe briefly the fundamental blocks and principles of quantum mechanics, and we present several related QC concepts such as qubits, correlation, and entanglement. We also present simulations and tools for the quantum implementation of select algorithms. We cover specifically Quantum Machine Learning (QML) and demonstrate simple implementations. The paper also describes current research and provides an extensive bibliography for further reading.

Original languageEnglish (US)
Title of host publicationIISA 2021 - 12th International Conference on Information, Intelligence, Systems and Applications
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665400329
DOIs
StatePublished - Jul 12 2021
Event12th International Conference on Information, Intelligence, Systems and Applications, IISA 2021 - Virtual, Chania Crete, Greece
Duration: Jul 12 2021Jul 14 2021

Publication series

NameIISA 2021 - 12th International Conference on Information, Intelligence, Systems and Applications

Conference

Conference12th International Conference on Information, Intelligence, Systems and Applications, IISA 2021
Country/TerritoryGreece
CityVirtual, Chania Crete
Period7/12/217/14/21

Keywords

  • Quantum Computing
  • deep learning
  • entanglement
  • machine learning
  • qubit
  • signal processing

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management

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