Hunting long-lived particles with intelligent triggers at the High-Luminosity LHC

Hunting long-lived particles with intelligent triggers at the High-Luminosity LHC The discovery of the Higgs boson at the LHC closes a central chapter of the standard model of particle physics but rais-es questions about dark matter, neutrino masses, and baryon asymmetry. Answers may involve long-lived particles (LLPs) with non-standard signatures, requiring advanced identification algorithms. Enhancing trigger capabilities to dis-cover LLPs and evidence of beyond-the-standard-model (BSM) physics is therefore a crucial task. INTREPID uses ad-vanced machine learning and ultra-fast processing to improve future trigger systems, potentially revolutionising high-energy physics and benefiting industries that need real-time data processing.

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Publication Details

Journal
The Project Repository Journal
Published
2026-04-30
DOI
https://doi.org/10.54050/prj2624534
Primary Topic
Particle physics theoretical and experimental studies
Type
article
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article

Hunting long-lived particles with intelligent triggers at the High-Luminosity LHC

Santiago Folgueras
The Project Repository Journal
Particle physics theoretical and experimental studies
article

Hunting long-lived particles with intelligent triggers at the High-Luminosity LHC

Santiago Folgueras
article en

Abstract

Hunting long-lived particles with intelligent triggers at the High-Luminosity LHC The discovery of the Higgs boson at the LHC closes a central chapter of the standard model of particle physics but rais-es questions about dark matter, neutrino masses, and baryon asymmetry. Answers may involve long-lived particles (LLPs) with non-standard signatures, requiring advanced identification algorithms. Enhancing trigger capabilities to dis-cover LLPs and evidence of beyond-the-standard-model (BSM) physics is therefore a crucial task. INTREPID uses ad-vanced machine learning and ultra-fast processing to improve future trigger systems, potentially revolutionising high-energy physics and benefiting industries that need real-time data processing.

The Project Repository JournalVol. 26(1)
Universidad de Oviedo (ES)
Industry, innovation and infrastructure
Openalex Percentile: Top 7%
Particle physics theoretical and experimental studies
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