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Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. Similarly, it requires commensurate investment in the R&D of software to acquire, manage, process, and analyse the shear amounts of data to be recorded. In planning for the HL-LHC in particular, it is critical that all of the collaborating stakeholders agree on the software goals and priorities, and that the efforts complement each other. In this spirit, this white paper describes the R&D activities required to prepare for this software upgrade.
In modern High Energy Physics (HEP) experiments visualization of experimental data has a key role in many activities and tasks across the whole data chain: from detector development to monitoring, from event generation to reconstruction of physics ob
At the heart of experimental high energy physics (HEP) is the development of facilities and instrumentation that provide sensitivity to new phenomena. Our understanding of nature at its most fundamental level is advanced through the analysis and inte
To produce the best physics results, high energy physics experiments require access to calibration and other non-event data during event data processing. These conditions data are typically stored in databases that provide versioning functionality, a
Data processing frameworks are an essential part of HEP experiments software stacks. Frameworks provide a means by which code developers can undertake the essential tasks of physics data processing, accessing relevant inputs and storing their outputs
Common and community software packages, such as ROOT, Geant4 and event generators have been a key part of the LHCs success so far and continued development and optimisation will be critical in the future. The challenges are driven by an ambitious phy