new ArXiv paper from Rodrigo Capucha, et. al., supported by the Comprehensive Multiboson Experiment-Theory Action (CA22130)

#COMETA video supported by the Comprehensive Multiboson Experiment-Theory Action (CA22130).

new #COMETA video, supported by the Comprehensive Multiboson Experiment-Theory Action (CA22130)Recording of the COMETA Colloquium on the 25th November 2024 by Tehar Aarrestad. Title: Detecting the rare and complex: Machine Learning for precision and efficiency at the LHC Abstract: As datasets in particle physics get progressively larger, algorithms to swiftly and accurately process this data have become increasingly complex. Machine Learning (ML) has emerged as a solution to tackle several of the challenges experiments face: to efficiently select and reconstruct interesting observational data, to enhance sensitivity to increasingly rare processes and to efficiently generate accurate simulations of complex physical systems. The forthcoming High Luminosity LHC (HL-LHC) will collect roughly ten times the data of the LHC, providing new opportunities for precision measurements of rare processes such as the Higgs self coupling, vector boson scattering and vector boson fusion. In this talk, I will present recent developments in ML techniques applied to event selection, reconstruction, and analysis, and discuss their impact on enhancing searches for these rare processes. I will review the pivotal role of ML in particle physics, from its contributions to the discovery of the Higgs boson in 2012 to its application in real-time event filtering in HL-LHC, where data rates will approach 5% of global internet traffic.

new #COMETA video, supported by the Comprehensive Multiboson Experiment-Theory Action (CA22130).

Comprehensive Multiboson Experiment-Theory Action

Comprehensive Multiboson Experiment-Theory Action

Comprehensive Multiboson Experiment-Theory Action

Comprehensive Multiboson Experiment-Theory Action

Comprehensive Multiboson Experiment-Theory Action webpage

COMETA webpage