Characterisation of Hamamatsu R11065-20 PMTs for use in the SABRE South NaI(Tl) Crystal Detectors

Date

2025

Authors

Stanley, O.
Melbourne, W.J.D.
Urquijo, P.
Barberio, E.
Bashu, V.U.
Bignell, L.J.
Bolognino, I.
Brooks, G.
Chhun, S.S.
Dastgiri, F.

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Journal Title

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Journal article

Citation

Journal of Instrumentation, 2025; 20(07):P07052-1-P07052-31

Statement of Responsibility

O. Stanley, W.J.D. Melbourne, P. Urquijo, E. Barberio, V.U. Bashu, L.J. Bignell, I. Bolognino, G. Brooks, S.S. Chhun, F. Dastgiri, M.B. Froehlich, T. Fruth, G. Fu, G.C. Hill, R.S. James, K. Janssens, S. Kapoor, G.J. Lane, K.T. Leaver, J. McKenzie, L.J. McKie, P. McGee, P.C. McNamara, M. Mews, L.J. Milligan, K.J. Rule, F. Scutti, Z. Slavkovská, A.E. Stuchbery, B. Suerfu, G.N. Taylor, A.G. Williams, Y. Xing, Y.Y. Zhong

Conference Name

DOI

10.1088/1748-0221/20/07/p07052

Abstract

The SABRE Experiment is a direct detection dark matter experiment using a target composed of multiple NaI(Tl) crystals. The experiment aims to be an independent check of the DAMA/LIBRA results with a detector in the Northern (Laboratori Nazionali Del Gran Sasso, LNGS) and Southern (Stawell Underground Physics Laboratory, SUPL) hemispheres. The SABRE South photomultiplier tubes (PMTs) will be used near the low energy noise threshold and require a detailed calibration of their performance and contributions to the background in the NaI(Tl) dark matter search, prior to installation. We present the development of the pre-calibration procedures for the R11065-20 Hamamatsu PMTs. These PMTs are directly coupled to the NaI(Tl) crystals within the SABRE South experiment. In this paper we present methodologies to characterise the gain, dark rate, and timing properties of the PMTs. We develop a method for in-situ calibration without a light injection source. Additionally we explore the application of machine learning techniques using a Boosted Decision Tree (BDT) trained on the response of single PMTs to understand the information available for background rejection. Finally, we briefly present the simulation tool used to generate digitised PMT data from optical Monte Carlo simulations.

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© 2025 The Author(s). Published by IOP Publishing Ltd on behalf of Sissa Medialab. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

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http://purl.org/au-research/grants/arc/CE200100008
 http://purl.org/au-research/grants/arc/LE190100196
 http://purl.org/au-research/grants/arc/LE170100162
 http://purl.org/au-research/grants/arc/LE160100080
 http://purl.org/au-research/grants/arc/DP190103123
 http://purl.org/au-research/grants/arc/DP170101675
 http://purl.org/au-research/grants/arc/LP150100705

Published Version

https://doi.org/10.1088/1748-0221/20/07/p07052

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Persistent link to this record

https://hdl.handle.net/2440/147814