Using Line Segment Tracking to enable ML-based Track Reconstruction in CMS
High-pileup conditions in CMS during the HL-LHC era make charged-particle tracking increasingly challenging as detector occupancy and combinatorics grow. We present a hybrid approach that exploits Line Segment Tracking (LST) objects rather than individual hits to enable the first CMS ML-based track reconstruction algorithm. The LST objects, namely the triplets used in this study, are built according to geometry- and physics-driven criteria and carry richer local structure, geometrical cues, and physics quantities such as transverse momentum, which helps the model incorporate detector-level information from the start. We apply a Transformer encoder with geometrically masked sparse self-att...
| Authors | Aashay Arora on behalf of the CMS Collaboration |
|---|---|
| Primary category | hep-ex |
| Published | 11 October 2026 |
| Last updated at source | 11 October 2026 |
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