# DCTracks: An Open Dataset for Machine Learning-Based Drift Chamber Track Reconstruction

arXiv: https://arxiv.org/abs/2602.14571 · HTML: https://mlsanity.com/paper/2602.14571/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 33 references that are in the map.
- First posted on arXiv 16 Feb 2026.

## Builds on (most cited first, 1 of 1)

- [ColliderML: The First Release of an OpenDataDetector High-Luminosity Physics Benchmark Dataset](https://mlsanity.com/paper/2512.15230/) (2025)

## Abstract (arXiv)

We introduce a Monte Carlo (MC) dataset of single- and two-track drift chamber events to advance Machine Learning (ML)-based track reconstruction. To enable standardized and comparable evaluation, we define track reconstruction specific metrics and report results for traditional track reconstruction algorithms and a Graph Neural Networks (GNNs) method, facilitating rigorous, reproducible validation for future research.