Conveners
Fri PM Plenaries: Plenaries
- Concezio Bozzi (INFN Ferrara)
- Graeme A Stewart (CERN)
Long term sustainability of the high energy physics (HEP) research software ecosystem is essential for the field. With upgrades and new facilities coming online throughout the 2020s this will only become increasingly relevant throughout this decade. Meeting this sustainability challenge requires a workforce with a combination of HEP domain knowledge and advanced software skills. The required...
The upgraded LHCb detector, due to start datataking in 2022, will have to process an average data rate of 4~TB/s in real time. Because LHCb's physics objectives require that the full detector information for every LHC bunch crossing is read out and made available for real-time processing, this challenge mirrors that of the ATLAS and CMS HL-LHC software triggers, but deliverable five years...
Recent work has demonstrated that geometric deep learning methods such as graph neural networks (GNNs) are well-suited to address a variety of recon- struction problems in HEP. In particular, tracker events are naturally repre- sented as graphs by identifying hits as nodes and track segments as edges; given a set of hypothesized edges, edge-classifying GNNs predict which rep- resent real track...
