No Track left behind: Graph-based Vertexing for long-lived Particle Reconstruction

Abstract

Reconstruction of displaced vertices is a cornerstone of both precision flavour physics and searches for long-lived particles (LLPs) at colliders. While existing vertexing algorithms are highly optimised for primary and short-lived secondary vertices, they face limitations when confronted with the large displacements and heterogeneous topologies characteristic of LLP decays. In this work we present a new approach to displaced vertex reconstruction combining a graph-based track clustering strategy as a vertex finder with the established robust vertex fitting procedure. The algorithm is implemented as a self-contained Delphes module and can be straightforwardly integrated into existing detector cards, providing a turn-key tool for phenomenological studies. This plug-and-play functionality fills an important gap in public fast-simulation frameworks by providing automated pattern recognition for displaced vertex finding, while remaining readily usable in phenomenological studies. We validate our approach in an IDEA-like FCC-ee detector, using Higgs-strahlung $e^{+}{e}^{-}\to Zh$ with exotic $h\to NN$ decays as a benchmark process. We demonstrate excellent efficiency, resolution, and purity across a broad range of lifetimes, and derive model-independent projections for the FCC-ee sensitivity to exotic Higgs branching fractions.

37 pages, 14 figures, code available at https://github.com/jkriewald/delphes-LLP , comments are welcome, v2: several clarifications added, quantitative results unchanged, accepted for publication in JHEP