The k4Clue package: Empowering Future Collider Experiments with the CLUE Algorithm
High granularity calorimeters have become increasingly crucial in modern particle physics experiments, and their importance is set to grow even further in the future. The CLUstering of Energy (CLUE) algorithm has shown excellent performance in clustering calorimeter hits in the High Granularity Calo...
Gespeichert in:
Hauptverfasser: | , , |
---|---|
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | High granularity calorimeters have become increasingly crucial in modern
particle physics experiments, and their importance is set to grow even further
in the future. The CLUstering of Energy (CLUE) algorithm has shown excellent
performance in clustering calorimeter hits in the High Granularity Calorimeter
(HGCAL) developed for the Phase-2 upgrade of the CMS experiment. In this paper,
we investigate the suitability of the CLUE algorithm for future collider
experiments and test its capabilities outside the HGCAL software
reconstruction. To this end, we developed a new package, k4Clue, which is now
fully integrated into the Gaudi software framework and supports the EDM4hep
data format for inputs and outputs. We demonstrate the performance of CLUE in
three detectors for future colliders: CLICdet for the CLIC accelerator, CLD for
the FCC-ee collider and a second calorimeter based on Noble Liquid technology
also proposed for FCC-ee. We find excellent reconstruction performance for
single gamma events, even in the presence of noise, and also compared with
other baseline algorithms. Moreover, CLUE demonstrates impressive timing
capabilities, outperforming the other algorithms and independently of the
number of input hits. This work highlights the adaptability and versatility of
the CLUE algorithm for a wide range of experiments and detectors and the
algorithm's potential for future high-energy physics experiments beyond CMS. |
---|---|
DOI: | 10.48550/arxiv.2311.03089 |