What question did this study set out to answer?

The aim is to explore the potential of intelligent triggers to identify long-lived particles in high-energy physics experiments.

May 6, 2026

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

Key Points

The aim is to explore the potential of intelligent triggers to identify long-lived particles in high-energy physics experiments.
Utilized advanced machine learning techniques for processing data.
Focused on the High-Luminosity LHC for experimental applications.
Improved trigger capabilities to capture non-standard signatures.
Enhanced trigger systems show promise in identifying long-lived particles.
Potential applications in discovering evidence for dark matter and baryon asymmetry.
Revolutionary improvements could benefit real-time data processing in various industries.

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.

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