ML4FE Workshop, University of Hawaii

Session

Physics, Contributed

May 20, 2025, 10:00 AM

Conveners

Physics, Contributed

• Dylan Rankin (University of Pennsylvania)

33. Low-Latency On-Chip $\tau$ Event Selection with Machine Learning for the Belle II Level-1 Trigger

Deven Misra (Kavli IPMU)

5/20/25, 10:00 AM

Contributed talk (12'+3')

Belle II is the second-generation $B$ physics experiment located at the SuperKEKB asymmetric $e^+ e^−$ collider, operating at the $\Upsilon(4S)$ resonance. The $\tau$ physics program at Belle II involves both probes of new physics and precision measurements of SM parameters with large statistics. These include placing strong constraints on lepton flavor violation [1], probing CP violation in...

43. 5-D calorimeter design issues with an integrated online/offline AI/ML approach

Andrew White (U. Texas at Arlington)

5/20/25, 10:15 AM

Contributed talk (12'+3')

Many physics analyses use some form of AI/ML to identify physics objects such as jets and electrons and/or for whole event classification. However, such an approach has generally been taken a long time after the detector was designed and constructed. It is therefore relevant to question whether a proposed design of a future calorimeter is optimal for the application of AI/ML techniques and,...

50. In-pixel integration of signal processing and machine learning based data filtering for particle tracking detectors

Benjamin Parpillon (Fermi National Accelerator Laboratory)

5/20/25, 10:30 AM

Contributed talk (12'+3')

We present a smart pixel prototype readout integrated circuit (ROIC), designed in a 28 nm CMOS bulk process, featuring in-pixel implementation of a machine learning based data filtering algorithm. This serves as a proof-of-principle for future particle tracking detectors. The ROIC integrates in-pixel signal processing with a fully connected two-layer neural network that analyzes information...