Paper

Majorana Demonstrator Data Release for AI/ML Applications

Vasilyev, S, D Hervas Aguilar, Quenallata, B, Schleich, S J, Guiseppe, V E, P -H Chu, Radford, D C, Reine, A L, Detwiler, J A, Tedeschi, D, Guinn, I S, Watkins, S L, Gruszko, J, Bos, B, Arnquist, I J, Caldwell, T S, Y -D Chan, Kouzes, R T, Meijer, S J, Massarczyk, R, Zhu, B X, Efremenko, Yu, W Xu, Lannen, T E, Bhimani, K H, Kim, I, Avignone, F T, Clark, M L, Christofferson, C D, Oli, T K, Paudel, L S, A Li, Elliott, S R, Hoppe, E W, Wilkerson, J F, Ejiri, H, Busch, M, C -H Yu, Lopez-Castano, J M, Henning, R, Rielage, K, Buuck, M, Blalock, E, Mertens, S, Ruof, N W, Hostiuc, A, Fuad, N, Barton, C J, Varner, R L, Green, M P, Pettus, W, Wiseman, C, Schaper, D C, Cuesta, C, Haufe, C R, Kidd, M F, Poon, A W P, Barabash, A S, Martin, R D, Giovanetti, G K

2023

Overview

The enclosed data release consists of a subset of the calibration data from the Majorana Demonstrator experiment. Each Majorana event is accompanied by raw Germanium detector waveforms, pulse shape discrimination cuts, and calibrated final energies, all shared in an HDF5 file format along with relevant metadata. This release is specifically designed to support the training and testing of Artificial Intelligence (AI) and Machine Learning (ML) algorithms upon our data. This document is structured as follows. Section I provides an overview of the dataset's content and format; Section II outlines the location of this dataset and the method for accessing it; Section III presents the NPML Machine Learning Challenge associated with this dataset; Section IV contains a disclaimer from the Majorana collaboration regarding the use of this dataset; Appendix A contains technical details of this data release. Please direct questions about the material provided within this release to [e-mail] (A. Li).

• Publisher: Cornell University Library, arXiv.org
• Subject: Algorithms / Artificial intelligence / Datasets / Format / Germanium / Machine learning / Pulse shape / Waveforms