Exploring new directions in enhancing the ACTS parameter optimization suite
Track seeding strongly affects both the quality and computational cost of charged-particle reconstruction, yet its many configuration parameters are commonly tuned through expert intuition and repeated trial and error. ACTS reduces this burden with an Optuna Tree-structured Parzen Estimator auto-tuner, but expensive evaluations, a restricted search space, and a scalarized objective can limit evaluation efficiency, exclude promising configurations, and obscure performance trade-offs. We investigate whether Bayesian optimization can address these limitations using ACTS with the Open Data Detector (ODD). Under identical search ranges and a common 100-trial budget, we compare Expected Improve...
| Authors | Chance LaVoie, Qi Bin Lei, Rocky Bala Garg et al. |
|---|---|
| Primary category | physics.data-an |
| Published | 11 August 2026 |
| Last updated at source | 11 August 2026 |
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