Presents new concepts for large-scale, collaborative computing and software development for particle, astroparticle, and nuclear physics domains, as well as observational astronomy and cosmology, or high-brilliance light sources.

Addressing challenges ranging from data reduction via data sharing, to the need for data-driven modeling, this journal explores concepts for large-scale, collaborative computing and software development as well as new algorithms and techniques for data processing.

Papers solicited include primarily research articles presenting new and original results, review papers (including white papers), advanced, self-contained tutorials, as well as documentation papers with the explicit aim to collect and combine knowledge spread over many internal documents to foster proper technology transfer.

  • Explores emerging issues in big-science development
  • Includes coverage of distributed data analysis and deep learning algorithms
  • Presents articles on software benchmarking, performance assessment and on data-quality monitoring on or off-line
  • Discusses aspects of evolving computing infrastructures
  • Investigates physics event generation and detector simulation

Journal information

  • Volker Beckmann,
  • Markus Elsing,
  • Günter Quast
Publishing model
Hybrid (Transformative Journal). Learn about publishing Open Access with us

Journal metrics

83 days
Submission to first decision
179 days
Submission to acceptance
21,644 (2020)

Latest articles

This journal has 26 open access articles


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About this journal

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Abstracted and indexed in
  1. Astrophysics Data System (ADS)
  2. CNKI
  3. Dimensions
  4. EBSCO Discovery Service
  5. Google Scholar
  8. Institute of Scientific and Technical Information of China
  9. Japanese Science and Technology Agency (JST)
  10. Naver
  11. OCLC WorldCat Discovery Service
  12. ProQuest-ExLibris Primo
  13. ProQuest-ExLibris Summon
  14. SCOPUS
  15. TD Net Discovery Service
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