Conveners
Physics and Engineering Applications -I
- Junichi Tanaka (University of Tokyo)
Description
Submissions should report on research for physics and engineering applications exploiting grid, cloud, or HPC services, applications that are planned or under development, or application tools and methodologies.
Topics of interest include:
(1) Data analysis and application including the use of ML/DL and quantum calculation algorithms;
(2) Management of distributed data;
(3) Performance analysis and system tuning;
(4) Workload scheduling;
(5) Management of an experimental collaboration as a virtual organization, in particular learning from the COVID-19 pandemic;
(6) Expectations for the evolution of computing models drawn from recent experience handling extremely large and geographically diverse datasets,and
(7) Expectations for the evolution of computing operations etc. towards the carbon neutral.
Models of physical systems simulated on HPC clusters often produce large amounts of valuable data that need to be safely managed both during the research projects ongoing activities and afterwards. To help to derive the most benefit for scientific advancement, we use results of the Horizon Europe Project EXA4MIND applying the tools to managing Particle In Cell simulation data from research...
Future collider experiments will require fast, scalable, and highly accurate calorimeter simulation to cope with unprecedented event rates and detector granularity. While machine-learning-based simulation has become a central strategy, the next step may come from quantum-native generative models capable of learning expressive, bijective mappings between physics parameters and detector...
The increasing demands on simulation statistics for HL-LHC analyses challenge the scalability of traditional calorimeter simulation within all LHC collaborations. Fast simulation techniques based on machine learning have proven effective, yet further improvements may arise from quantum-inspired models.
In this study we investigate the feasibility of integrating Quantum Neural Network (QNN)...
Scientific Computing and Data Facilities (SCDF) at Brookhaven Lab began in
1997 when the Relativistic Heavy Ion Collider (RHIC) and ATLAS Computing Facility was established. The full-service scientific computing facility has since supported some of the most notable physics experiments, including Broad RAnge Hadron Magnetic Spectrometers (BRAHMS), Pioneering High Energy Nuclear Interaction...
