CUORE Data Release for ML Applications: Pulse Shape Analysis Dataset

We present a public dataset from the CUORE (Cryogenic Underground Observatory for Rare Events) experiment, designed to support the development and benchmarking of Artificial Intelligence and Machine Learning (AI/ML) algorithms for cryogenic calorimeter data analysis. CUORE uses TeO2 cryogenic calorimeters to measure particle energy depositions as thermal fluctuations. This dataset contains thermal pulses measured during calibration data taking. Each data point is provided as a one-dimensional, time-series array corresponding to a thermal pulse, accompanied by a binary classification label to distinguish between single-pulse events and pile-up events with two or more pulses; pulse normalization parameters and relevant metadata are also included, with all data stored in HDF5 format. This data release enables the testing of supervised learning approaches to pulse shape analysis, pile-up identification, and related tasks in the context of rare-event searches with cryogenic calorimeters.

The CUORE Collaboration has authorized the public release of this dataset, permitting its use for all reasonable purposes. Individuals or groups are permitted to publish results based on this dataset. The CUORE Collaboration maintains ownership rights over this dataset and reserves all associated rights. Users of this dataset
are kindly requested to cite "D. Q. Adams et al. (CUORE Collaboration), Science 390, 1029-1032 (2025)" and "arXiv:2607.02548v1 [physics.ins-det]".