Active Noise Cancellation in CUORE Data

The Cryogenic Observatory for Rare Events (CUORE) experiment searches for the neutrinoless double beta decay using tellurium dioxide crystals as a source and detection method. Due to the highly sensitive nature of the detectors, they will experience acoustic noise that will worsen the resolution of the signal. Auxiliary devices such as accelerometers and microphones are currently being used alongside the detectors to measure acoustic noise and actively subtract it out of the data. This is done by analyzing the frequency-dependent coherence between the auxiliary devices and detectors and using this to predict the detector noise. Recent results have shown that an approximation of the stable noise in CUORE can be used to denoise calibration data that have few noise events. Similar methods, combined with machine learning techniques, can be used to increase the resolution of the signals in the detectors.

I will present a brief overview on the denoising algorithm used for CUORE and describe the role of the auxiliary devices for active noise cancellation and how a generic filter has been used to denoise data without the direct use of auxiliary device data.