Using Wavelets to reject background in Dark Matter experiments
I.G. Irastorza, A. Morales, S. Cebrian, E. Garcia, J. Morales, A., Ortiz de Solorzano, S.B. Osetrov, J. Puimedon, M.L. Sarsa, J.A. Villar
TL;DR
This paper introduces a wavelet-based method for effectively rejecting background noise in dark matter experiment data, improving the identification of true signals.
Contribution
It presents a novel wavelet technique tailored for background rejection in dark matter experiments, with detailed methodology and application to IGEX data.
Findings
Effective noise rejection demonstrated on IGEX data
Wavelet method distinguishes signal from microphonism
Improved data quality for dark matter detection
Abstract
A method based on wavelet techniques has been developed and applied to background rejection in the data of the IGEX dark matter experiment. The method is presented and described in some detail to show how it efficiently rejects events coming from noise and microphonism through a mathematical inspection of their recorded pulse shape. The result of the application of the method to the last data of IGEX is presented.
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