Description of CRESST-II and CRESST-III pulse shape data
G. Angloher, S. Banik, D. Bartolot, G. Benato, A. Bento, A. Bertolini, R. Breier, C. Bucci, J. Burkhart, L. Canonica, A. D'Addabbo, S. Di Lorenzo, L. Einfalt, A. Erb, F. v. Feilitzsch, N. Ferreiro Iachellini, S. Fichtinger, D. Fuchs, A. Fuss, A. Garai, V.M. Ghete, P. Gorla
TL;DR
This paper details a dataset from the CRESST dark matter search experiment, including how trained classifiers can be used for data cleaning, with data and models publicly available.
Contribution
It provides a comprehensive description of the pulse shape dataset and the application of classifiers for data cleaning in cryogenic detector experiments.
Findings
Dataset from 68 detectors over 6 years described
Models trained for data cleaning are available online
Facilitates improved data analysis in dark matter searches
Abstract
A set of data from 68 cryogenic detectors operated in the CRESST dark matter search experiment between 2013 and 2019 was collected and labeled to train binary classifiers for data cleaning. Here, we describe the data set and how the trained models can be applied to new data. The data and models are available online.
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Taxonomy
TopicsDark Matter and Cosmic Phenomena · Particle physics theoretical and experimental studies · Particle Detector Development and Performance