Development of an Adaptive Noise Canceling Algorithm for CUORE Data

The Cryogenic Observatory for Rare Events (CUORE) is an experiment searching for neutrinoless double beta decay (0νββ). In Italy, the search at the Gran Sasso National Laboratory (LNGS), bolometers are used to detect small heat signals in crystals cooled to 10mK. Seismic, acoustic, and electrical interference riddle the signal with noise affecting the bolometers' resolution. At CUORE we have installed microphones, accelerometers, and antennas to measure the acoustic background noise of the system. We have also implemented an algorithm that denoises a system using those auxiliary devices to measure the coherent noise in the sensors. We determine whether background noise is coherent by analyzing the transfer function between the auxiliary devices and the sensors. The acoustic noise from pulse tubes and turbo pumps that help cool the cryostat down tends to be relatively constant compared to seismic noise from earthquakes. In the frequency domain, the acoustic noise power has a stable bandwidth measured on both devices. My poster will give an overview of how the algorithm uses a snapshot to develop a denoising filter. I will also update the development of an active noise template that uses a transfer function to filter important data for calibration and background measurements.