IN2P3/IRFU Machine Learning workshop 2025

Session

AI at the edge

27 nov. 2025, 15:45

G. Iltis (LPC) and Seminar room maison d'hôtes (GANIL) (LPC Caen and GANIL)

Présidents de session

AI at the edge

• Georges AAD (CPPM, Aix-Marseille Université, CNRS/IN2P3 (FR))

Description

Real-time processing and trigger

142. Development of innovative methods for a fission trigger construction

Brigitte Pertille Ritter (Université Paris-Saclay / IJCLab)

27/11/2025 15:45

Analysis : event classification, statistical analysis and inference, anomaly detection

The development of innovative methods for fission trigger construction addresses the challenge of recognising fission signature in very complex detector’s response functions.
The fission recognition approaches available today have intrinsic limitations.
To draw a clearer picture, the existing dedicated detectors for fission triggering present constraints regarding experimental setup geometry...

138. Deconvolution du signal de détecetur de R2D2 dans un FPGA par réseau de neurone convolutif 1D

Frederic Druillole (CNRS-LP2IB)

27/11/2025 16:05

Analysis : event classification, statistical analysis and inference, anomaly detection

A travers la R&T THINK, nous essayons de créer des modèles pouvant remplacer le traitement classique du signal au plus près des détecteurs. Je présenterais la problématique des modèles dans l'embarqué. Puis, je presenterai la problématique du signal de R2D2 pour la recherche sur la nature des neutrino. Je presenterai alors un modèle de déconvolution de la chaine électronique pour retrouver la...

139. Optimising the High Granularity Calorimeter trigger primitives for machine learning based particle identification in the CMS Level-1 trigger

Trisha Debnath (LLR. École Polytechnique | CNRS)

27/11/2025 16:25

Fast ML : DAQ/Trigger/Real Time Analysis

As part of its upgrade for the High-Luminosity LHC (HL-LHC) , the CMS experiment is deploying a novel High Granularity Calorimeter (HGCAL) in the endcap regions. Designed with fine segmentation in both longitudinal and transverse directions, HGCAL will be the first calorimeter specifically optimised for particle-flow reconstruction to operate at a colliding-beam experiment. The calorimeter...

141. Optimization of embedded neural networks for the energy reconstruction of the liquid argon calorimeter cells of ATLAS

Raphael BERTRAND (Aix Marseille Univ, CNRS/IN2P3, CPPM, Marseille, France)

27/11/2025 16:45

Fast ML : DAQ/Trigger/Real Time Analysis

The Large Hadron Collider (LHC) collides protons at nearly the speed of light, producing new particles observed by the ATLAS detector. In 2026, the LHC will undergo a major upgrade to the High-Luminosity LHC (HL-LHC), increasing luminosity by a factor of 5–7 and delivering up to 200 simultaneous collisions. To cope with the resulting data rates, ATLAS will replace the readout electronics of...

160. DBSCAN for anomaly detection of Turn-by-turn Beam Position Monitors

Quentin Bruant (CEA/IRFU/DACM)

27/11/2025 17:05

Analysis : event classification, statistical analysis and inference, anomaly detection

Collider rings need to have several sensors all around the ring to operate. One of these sensors is the Beam Position Monitor (BPM), which allows operators to measure if the beam travelling in the ring is well centered between the different magnets. One specific category of BPMs, which stands out because of its high acquisition rate, is called the Turn-by-turn BPMs (TbTBPMs). Several methods...