Quantum Machine Intelligence publishes original articles on cutting-edge experimental and theoretical research in all areas of quantum artificial intelligence. The Journal is unique in promoting a synthesis of machine learning, data science and computational intelligence research with quantum computing developments. Its primary goal is to foster the utilization of quantum computing for real-world problems so as to pave the way towards the next generation of artificial intelligence systems. The Journal also publishes innovative papers reporting on machine intelligence theories, methods and applications inspired by physics and nature, e.g. computational intelligence, fuzzy systems, evolutionary computation, machine and deep learning.

All papers submitted undergo a rigorous peer review to ensure their originality, timeliness, relevance and readability. The journal also welcomes occasional review articles and short communications in all of the above-mentioned topic areas.

  • The first scientific journal that highlights the synergies between quantum computing and artificial intelligence
  • Promotes a synthesis of the research areas of machine learning and data science, and their engineering applications based on quantum technologies
  • Fosters the application of quantum computing and artificial intelligence to address real-world problems
Editor-in-Chief
  • Giovanni Acampora
Publishing model
Hybrid. Open Choice – What is this?

Articles

About this journal

Electronic ISSN
2524-4914
Print ISSN
2524-4906
Abstracted and indexed in
  1. ACM Digital Library
  2. EBSCO Discovery Service
  3. Google Scholar
  4. INSPEC
  5. Institute of Scientific and Technical Information of China
  6. Japanese Science and Technology Agency (JST)
  7. Naver
  8. OCLC WorldCat Discovery Service
  9. ProQuest-ExLibris Primo
  10. ProQuest-ExLibris Summon
Copyright information

Rights and permissions

Springer Nature policies

© Springer Nature Switzerland AG