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Physics - Particle and Nuclear Physics | Computing and Software for Big Science

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Computing and Software for Big Science

Computing and Software for Big Science

Editor-in-Chief: V. Beckmann; M. Elsing; G. Quast

ISSN: 2510-2036 (print version)
ISSN: 2510-2044 (electronic version)

Journal no. 41781

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  • 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  

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.

Related subjects » Particle and Nuclear Physics

Abstracted/Indexed in 

INSPEC, Google Scholar, EBSCO Discovery Service, INSPIRE, OCLC WorldCat Discovery Service, ProQuest-ExLibris Primo, ProQuest-ExLibris Summon

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For authors and editors

  • Aims and Scope

    Aims and Scope


    This peer-reviewed journal is dedicated to the publication of high-quality material originating from the collective effort by the scientific community to address the special and ever more demanding computing and software needs of the future. At its core will be particle, astro-particle and nuclear physics, as well as observational astronomy and cosmology, or high-brilliance light sources - fields in which experimental research is increasingly organized in large and global collaborations around large-scale instruments with huge output of data, and typically operating at the very frontier of energy, intensity and detector technology.

    Facing similar challenges ranging from data reduction, via data sharing, to increasingly data-driven modeling of different facets of the same physical universe, the scientific community requires fundamental and novel concepts for large-scale and collaborative computing and software development, as well as novel algorithms and techniques for data processing.


    -infrastructures for large-scale, high-throughput computing

    -related software and development

    -infrastructure middleware development

    -data processing, hosting and sharing

    -novel algorithms for efficient data reconstruction and filtering

    -software benchmarking and performance assessment

    -frameworks and software integration

    -online/offline data quality monitoring

    -distributed data analysis

    -deep learning algorithms

    -event and object classification

    -data visualization

    - physics event generation and detector simulation

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