Improving primary-vertex reconstruction with a minimum-cost lifted multicut graph partitioning algorithm

TL;DR

This paper introduces a new graph partitioning algorithm based on minimum-cost lifted multicut formulation to improve primary-vertex reconstruction in particle physics experiments, outperforming heuristic methods especially at high vertex multiplicities.

Contribution

The paper presents a universal, principled approach for vertex reconstruction using a minimum-cost lifted multicut algorithm, advancing beyond ad hoc heuristics.

Findings

Outperforms heuristic algorithms in vertex reconstruction accuracy

Effective at high vertex multiplicities in LHC environments

Demonstrates robustness despite detector-induced reconstruction errors

Abstract

Particle physics experiments often require the simultaneous reconstruction of many interaction vertices. Usually, this problem is solved by ad hoc heuristic algorithms. We propose a universal approach to address the multiple vertex finding through a principled formulation as a minimum-cost lifted multicut problem. The suggested algorithm is tested in a typical LHC environment with multiple proton-proton interaction vertices. Reconstruction errors caused by the particle detectors complicate the solution and require the introduction of special metrics to assess the vertex-finding performance. We demonstrate that the minimum-cost lifted multicut approach outperforms heuristic algorithms and works well up to the highest vertex multiplicity expected at the LHC.