# A novel method for reconstruction of collision vertices at high-intensity hadron colliders

## TL;DR

This paper introduces a new clustering algorithm for reconstructing collision vertices in high-luminosity hadron colliders, improving accuracy amid many simultaneous interactions.

## Contribution

The paper presents a novel agglomerative clustering method tailored for high-luminosity collider environments, enhancing vertex reconstruction performance.

## Key findings

- Significantly improved position resolution for hard-scatter interactions.
- Effective in high pile-up conditions simulating LHC Run 3.
- Reduces contamination from multiple interactions in vertex fitting.

## Abstract

This paper presents a novel method for the reconstruction of interaction vertices in particle collision data. The algorithm is an agglomerative clustering technique designed for high-luminosity environments in current and future proton-proton colliders. Studies are presented in benchmark scenarios reproducing the LHC data-taking conditions and showing the performance as a function of the number of interactions per bunch crossing. Particular focus will be given to the foreseen data-taking conditions at the Run 3 of the LHC. The proposed algorithm is found to significantly improve the position resolution on the hard-scatter interaction by limiting the contamination of tracks from additional interactions in the vertex fit.