Published November 11, 2025 | Version v1

Optimization and Outer Tracker Extension of the Cellular Automaton Algorithm for CMS Phase-2 HLT Tracking

Authors/Creators

  • 1. ROR icon RWTH Aachen University
  • 2. ROR icon European Organization for Nuclear Research
  • 1. ROR icon European Organization for Nuclear Research
  • 2. ROR icon University of Bologna
  • 3. ROR icon Centre de Calcul de l'Institut National de Physique Nucléaire et de Physique des Particules
  • 4. ROR icon RWTH Aachen University

Description

The Phase-2 Upgrade for the CMS experiment at the HL-LHC brings with it new and improved detectors, including a new tracker. It will provide the means to reconstruct higher-quality tracks in the pixel detector, especially in the endcaps (pseudorapidity |η| ≳ 2), by allowing to record hits in many more layers than what is currently possible. The Phase 2 CMS tracking at the HLT currently plans to take advantage of complementary methods to reconstruct tracks in the inner and outer tracker, with the former using a Cellular Automaton (CA) algorithm for pattern recognition producing tracks with at least four hits, and the latter relying on Line Segment Tracking (LST) together with mkFit: a CMS-developed vectorizable and parallel alternative to the traditional Combinatorial Kalman Filter (CKF). This contribution focuses on the CA algorithm, with its optimization for Phase 2 and, in particular, its extension to the first layers of the outer tracker. This extension aims to improve tracks in the barrel region of the pixel detector (pseudorapidity |η| ≲ 2), where more tracks are expected to have only three hits, specifically avoiding the significant drawback of increased fake and duplicate tracks produced by other attempts to recoup efficiency.

Files

CTD2025-CMS-PatatrackPixelTracking.pdf

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Additional details

Related works

References
Technical note: 2948318 (CDS)

Funding

Schmidt Family Foundation

Dates

Accepted
2025-11-11

CERN

Conference

Title
Connecting The Dots 2025
Acronym
CTD2025
Dates
10-14 November 2025
Place
Tokyo, Japan
Indico
1499357

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