Scientific Computing Plan for the ECCE Detector at the Electron Ion Collider

Abstract

The Electron Ion Collider (EIC) is the next generation of precision QCD facility to be built at Brookhaven National Laboratory in conjunction with Thomas Jefferson National Laboratory. There are a significant number of software and computing challenges that need to be overcome at the EIC. During the EIC detector proposal development period, the ECCE consortium began identifying and addressing these challenges in the process of producing a complete detector proposal based upon detailed detector and physics simulations. In this document, the software and computing efforts to produce this proposal are discussed; furthermore, the computing and software model and resources required for the future of ECCE are described.

References in corpus (10)

• A Brief Introduction to PYTHIA 8.1
• High-Energy-Physics Event Generation with PYTHIA 6.1
• Rucio - Scientific data management
• Science Requirements and Detector Concepts for the Electron-Ion Collider: EIC Yellow Report
• A comprehensive real-time analysis model at the LHCb experiment
• The dipole model Monte Carlo generator Sartre 1
• AI-optimized detector design for the future Electron-Ion Collider: the dual-radiator RICH case
• Implementation of ACTS into sPHENIX track reconstruction
• A GPU-based Kalman Filter for Track Fitting
• AI for Experimental Controls at Jefferson Lab

Cited by in corpus (4)

• Design and Simulated Performance of Calorimetry Systems for the ECCE Detector at the Electron Ion Collider
• AI-assisted Optimization of the ECCE Tracking System at the Electron Ion Collider
• Test of streaming and triggered readout schemes for the TPEX Lead Tungstate Calorimeter
• Cohort Organized Learning: Clustering Through Agreement