On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments

no code implementations • 20 Jul 2023 • Shruti R. Kulkarni, Aaron Young, Prasanna Date, Narasinga Rao Miniskar, Jeffrey S. Vetter, Farah Fahim, Benjamin Parpillon, Jennet Dickinson, Nhan Tran, Jieun Yoo, Corrinne Mills, Morris Swartz, Petar Maksimovic, Catherine D. Schuman, Alice Bean

We present our insights on the various system design choices - from data encoding to optimal hyperparameters of the training algorithm - for an accurate and compact SNN optimized for hardware deployment.

Machine Learning for Particle Flow Reconstruction at CMS

no code implementations • 1 Mar 2022 • Joosep Pata, Javier Duarte, Farouk Mokhtar, Eric Wulff, Jieun Yoo, Jean-Roch Vlimant, Maurizio Pierini, Maria Girone

The standard particle flow algorithm reconstructs stable particles based on calorimeter clusters and tracks to provide a global event reconstruction that exploits the combined information of multiple detector subsystems, leading to strong improvements for quantities such as jets and missing transverse energy.

BIG-bench Machine Learning