Performance of a convolutional autoencoder designed to remove electronic noise from p-type point contact germanium detector signals.

Autor: Anderson MR; Department of Physics, Engineering Physics and Astronomy, Queen's University, Kingston, ON Canada., Basu V; Department of Physics, Engineering Physics and Astronomy, Queen's University, Kingston, ON Canada., Martin RD; Department of Physics, Engineering Physics and Astronomy, Queen's University, Kingston, ON Canada., Reed CZ; Department of Physics, Engineering Physics and Astronomy, Queen's University, Kingston, ON Canada., Rowe NJ; Department of Physics, Engineering Physics and Astronomy, Queen's University, Kingston, ON Canada., Shafiee M; Department of Physics, Engineering Physics and Astronomy, Queen's University, Kingston, ON Canada.; Department of Electrical and Computer Engineering, Nazarbayev University, Nur-Sultan, Kazakhstan.; Energetic Cosmos Laboratory, Nazarbayev University, Nur-Sultan, Kazakhstan., Ye T; Department of Physics, Engineering Physics and Astronomy, Queen's University, Kingston, ON Canada.
Jazyk: angličtina
Zdroj: The European physical journal. C, Particles and fields [Eur Phys J C Part Fields] 2022; Vol. 82 (12), pp. 1084. Date of Electronic Publication: 2022 Dec 01.
DOI: 10.1140/epjc/s10052-022-11000-w
Abstrakt: We present a convolutional autoencoder to denoise pulses from a p-type point contact high-purity germanium detector similar to those used in several rare event searches. While we focus on training procedures that rely on detailed detector physics simulations, we also present implementations requiring only noisy detector pulses to train the model. We validate our autoencoder on both simulated data and calibration data from an 241 Am source, the latter of which is used to show that the denoised pulses are statistically compatible with data pulses. We demonstrate that our denoising method is able to preserve the underlying shapes of the pulses well, offering improvement over traditional denoising methods. We also show that the shaping time used to calculate energy with a trapezoidal filter can be significantly reduced while maintaining a comparable energy resolution. Under certain circumstances, our denoising method can improve the overall energy resolution. The methods we developed to remove electronic noise are straightforward to extend to other detector technologies. Furthermore, the latent representation from the encoder is also of use in quantifying shape-based characteristics of the signals. Our work has great potential to be used in particle physics experiments and beyond.
Competing Interests: Conflict of interestThe authors have no competing interests to declare that are relevant to the content of this article.
(© The Author(s) 2022.)
Databáze: MEDLINE
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