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arXiv · 2602.14571

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

Qian Liyan·Zhang Yao·Yuan Ye·Zhang Zhaoke·Fang Jin·Jiang Shimiao·Zhang Jin·Li Ke·Liu Beijiang·Xu Chenglin·Zhang Yifan·Jia Xiaoqian·Qin Xiaoshuai·Huang Xingtao
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Abstract

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.

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Qian Liyan, Zhang Yao, Yuan Ye, Zhang Zhaoke, Fang Jin, Jiang Shimiao, Zhang Jin, Li Ke, Liu Beijiang, Xu Chenglin, Zhang Yifan, Jia Xiaoqian, Qin Xiaoshuai, Huang Xingtao. 2026-02-16. DCTracks: An Open Dataset for Machine Learning-Based Drift Chamber Track Reconstruction. https://arxiv.org/abs/2602.14571

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