Computing and Software for Big Science [electronic resource] / edited by Volker Beckmann, Markus Elsing, Günter Quast.

Інтелектуальна відповідальність: Вид матеріалу: Серіальне виданняПублікація: Cham : Springer International Publishing : Imprint: Springer.Опис: online resourceISSN:
  • 2510-2044
Тематика(и): Додаткові фізичні формати: Printed version: : Немає назвиЕлектронне місцезнаходження та доступ: Зведення: This single-blind peer-reviewed journal is dedicated to the publication of high-quality material originating from all current and emerging scientific communities in which experimental research is increasingly based on large-scale research infrastructures. With particle, nuclear and astrophysics as prime examples, the journal welcomes contributions from all areas of fundamental and applied physics where collective international efforts take center stage. Research in these fields is characterized by huge amounts of data generated at the very frontiers of energy, intensity and detector technology and call for substantial advances to address the highly specialized and ever more demanding requirements in the areas of computing, software, data science and numerical simulations. Future experimental and theoretical challenges will require extensive collaborative efforts and may yield novel approaches and solutions to a range of different scientific communities. The journal welcomes Editorials – reflecting debated open issues or developments –, original research or technical papers, tutorials, reviews, and substantial community white papers. The journal's scope includes but is not limited to high-throughput computing high-performance computing related software and developments infrastructure middleware development data processing, hosting and sharing machine learning and data science statistical data analysis and data interpretations physics event generation software development for large-scale theoretical calculations detector simulation algorithms for data reconstruction and filtering frameworks and software integration heterogenous computing distributed data analysis software benchmarking and performance evaluation optimization of scientific algorithms online/offline software data quality monitoring .
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This single-blind peer-reviewed journal is dedicated to the publication of high-quality material originating from all current and emerging scientific communities in which experimental research is increasingly based on large-scale research infrastructures. With particle, nuclear and astrophysics as prime examples, the journal welcomes contributions from all areas of fundamental and applied physics where collective international efforts take center stage. Research in these fields is characterized by huge amounts of data generated at the very frontiers of energy, intensity and detector technology and call for substantial advances to address the highly specialized and ever more demanding requirements in the areas of computing, software, data science and numerical simulations. Future experimental and theoretical challenges will require extensive collaborative efforts and may yield novel approaches and solutions to a range of different scientific communities. The journal welcomes Editorials – reflecting debated open issues or developments –, original research or technical papers, tutorials, reviews, and substantial community white papers. The journal's scope includes but is not limited to high-throughput computing high-performance computing related software and developments infrastructure middleware development data processing, hosting and sharing machine learning and data science statistical data analysis and data interpretations physics event generation software development for large-scale theoretical calculations detector simulation algorithms for data reconstruction and filtering frameworks and software integration heterogenous computing distributed data analysis software benchmarking and performance evaluation optimization of scientific algorithms online/offline software data quality monitoring .

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