Conveners
ML Workshop: III session
- Anna Sfyrla (Universite de Geneve (CH))
- Thea Aarrestad (ETH Zurich (CH))
Machine learning has become an indispensable tool in the field of high-energy physics, particularly in the CMS experiment at CERN.
In this talk, we will discuss some of the new developments in ML techniques implemented in the CMS experiment. These advancements have improved tasks like event reconstruction, jet flavour tagging, data quality monitoring, anomaly detection in the triggers, and...
In the ATLAS trigger and data acquisition system we can use machine learning to approximate existing online algorithms and accelerate trigger decisions in real time. This will be particularly important for the ATLAS Phase II upgrade in the high-luminosity LHC which will enforce strict latency requirements in the trigger. This work introduces a novel application of a Convolutional Neural...
Jets containing b-hadrons (b-jets) are a key signature to trigger events at collider experiments, as they're associated to many interesting physics processes, such as Higgs decays. Charged particle tracks reconstruction, the main input for b-tagging algorithms, makes the b-jet trigger selections some of the most CPU intensive ones at the ATLAS High-Level-Trigger (HLT). To cope with the...
Long lived particles (LLP) are ubiquitous in many Standard Model extensions, and could provide solutions to long-standing problems in modern physics. LLPs would present unique signatures, such as decays in flight far from the interaction point. New trigger and reconstruction techniques are required to search for such events. We propose using the LHCb muon detector as a sampling...
Leveraging the current industry shift towards heterogeneous computing and the widespread
adoption of FPGAs as accelerators to deploy machine learning algorithms, this project
introduces the Vitis accelerator backend, a novel backend for HLS4ML. HLS4ML is a python package tailored for machine learning inference on FGPAs that translates traditional
open-source machine learning package models...
The general-purpose Geant4 based calorimeter framework Lorenzetti Showers is being presented. It provides an ideal tool for simulating various configurations of calorimeter systems or testing their responses in complex scenarios. Its limits are being investigated by simulating a system very close to the ATLAS calorimeters and comparing their signatures under challenging conditions. Such a...
The Large-Sized Telescope (LST) is one of three telescope types being built as part of the Cherenkov Telescope Array Observatory (CTAO) to cover the lower energy range between 20 GeV and 200 GeV. The Large-Sized Telescope prototype (LST-1), installed at the La Palma Observatory Roque de Los Muchachos, is currently being commissioned and has successfully taken data since November 2019. The...
Imaging atmospheric Cherenkov telescopes (IACTs) observe extended air showers (EASs) initiated by the interaction of very-high-energy gamma rays and cosmic rays with the atmosphere. Cherenkov photons induced by a given shower are focused onto the camera plane of the telescopes resulting into a spatial and temporal charge development in the camera pixels. Besides the Cherenkov light emitted by...
