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End-to-End Data Analysis Methods for the CUORE Experiment

D. Q. Adams, C. Alduino, K. Alfonso, A. Armatol, F. T. Avignone, O. Azzolini, G. Bari, F. Bellini, G. Benato, M. Beretta, M. Biassoni, A. Branca, C. Brofferio, C. Bucci, J. Camilleri, A. Caminata, A. Campani, J. Cao, C. Capelli, S. Capelli, L. Cappelli, L. Cardani, P. Carniti, N. Casali, E. Celi, D. Chiesa, M. Clemenza, S. Copello, O. Cremonesi, R. J. Creswick, A. D'Addabbo, I. Dafinei, S. Dell'Oro, S. Di Domizio, S. Di Lorenzo, T. Dixon, D. Q. Fang, M. Faverzani, E. Ferri, F. Ferroni, E. Fiorini, M. A. Franceschi, S. J. Freedman, S. H. Fu, B. K. Fujikawa, S. Ghislandi, A. Giachero, M. Girola, L. Gironi, A. Giuliani, P. Gorla, C. Gotti, P. V. Guillaumon, T. D. Gutierrez, K. Han, E. V. Hansen, K. M. Heeger, D. L. Helis, H. Z. Huang, M. T. Hurst, G. Keppel, Yu. G. Kolomensky, R. Kowalski, R. Liu, L. Ma, Y. G. Ma, L. Marini, R. H. Maruyama, D. Mayer, Y. Mei, M. N. Moore, T. Napolitano, M. Nastasi, C. Nones, E. B. Norman, A. Nucciotti, I. Nutini, T. O'Donnell, M. Olmi, B. T. Oregui, S. Pagan, C. E. Pagliarone, L. Pagnanini, M. Pallavicini, L. Pattavina, M. Pavan, G. Pessina, V. Pettinacci, C. Pira, S. Pirro, E. G. Pottebaum, S. Pozzi, E. Previtali, A. Puiu, S. Quitadamo, A. Ressa, C. Rosenfeld, B. Schmidt, R. Serino, A. Shaikina, V. Sharma, V. Singh, M. Sisti, D. Speller, P. T. Surukuchi, L. Taffarello, C. Tomei, A. Torres, J. A. Torres, K. J. Vetter, M. Vignati, S. L. Wagaarachchi, B. Welliver, J. Wilson, K. Wilson, L. A. Winslow, F. Xie, T. Zhu, S. Zimmermann, S. Zucchelli

TL;DR

The paper presents an end-to-end data analysis framework for the CUORE cryogenic calorimeter array, detailing how each detector is individually optimized and processed to extract high-quality datasets for rare-event searches. It covers trigger strategies (online derivative and offline Optimum Trigger), noise reduction, pulse-shape analysis, and two complementary thermal-gain stabilization methods, all tied together by an energy reconstruction and calibration scheme that accounts for energy-dependent resolution and biases. A rigorous treatment of exposure, efficiency, coincidence tagging, and blinding supports a robust $0\nu\beta\beta$ analysis, leading to the most stringent $^{130}$Te limit to date and a flexible platform for background modeling, low-energy studies, and multi-crystal analyses. The methodology lays a solid foundation for next-generation experiments like CUPID, demonstrating scalable, per-channel optimization and automation across ~1000 channels with precise energy response modeling and comprehensive efficiency quantification.

Abstract

The Cryogenic Underground Observatory for Rare Events (CUORE) experiment set the most stringent limit on the neutrinoless double-beta ($0νββ$) decay half-life of $^{130}$Te with 2 ton yr TeO$_2$ analyzed exposure. In addition to $0νββ$ decay, the CUORE detector -- a ton-scale array of nearly 1000 cryogenic calorimeters operating at $\sim$10 mK -- is capable of searching for other rare decays and interactions over a broad energy range. For our searches, we leverage the available information of each calorimeter by performing its optimization, data acquisition, and analysis independently. We describe the analysis tools and methods developed for CUORE and their application to build high-quality datasets for numerous physics searches. In particular, we describe in detail our evaluation of the energy-dependent detector response and signal efficiency used in the most recent search for $0νββ$ decay.

End-to-End Data Analysis Methods for the CUORE Experiment

TL;DR

The paper presents an end-to-end data analysis framework for the CUORE cryogenic calorimeter array, detailing how each detector is individually optimized and processed to extract high-quality datasets for rare-event searches. It covers trigger strategies (online derivative and offline Optimum Trigger), noise reduction, pulse-shape analysis, and two complementary thermal-gain stabilization methods, all tied together by an energy reconstruction and calibration scheme that accounts for energy-dependent resolution and biases. A rigorous treatment of exposure, efficiency, coincidence tagging, and blinding supports a robust analysis, leading to the most stringent Te limit to date and a flexible platform for background modeling, low-energy studies, and multi-crystal analyses. The methodology lays a solid foundation for next-generation experiments like CUPID, demonstrating scalable, per-channel optimization and automation across ~1000 channels with precise energy response modeling and comprehensive efficiency quantification.

Abstract

The Cryogenic Underground Observatory for Rare Events (CUORE) experiment set the most stringent limit on the neutrinoless double-beta () decay half-life of Te with 2 ton yr TeO analyzed exposure. In addition to decay, the CUORE detector -- a ton-scale array of nearly 1000 cryogenic calorimeters operating at 10 mK -- is capable of searching for other rare decays and interactions over a broad energy range. For our searches, we leverage the available information of each calorimeter by performing its optimization, data acquisition, and analysis independently. We describe the analysis tools and methods developed for CUORE and their application to build high-quality datasets for numerous physics searches. In particular, we describe in detail our evaluation of the energy-dependent detector response and signal efficiency used in the most recent search for decay.

Paper Structure

This paper contains 41 sections, 28 equations, 24 figures, 3 tables.

Table of Contents

  1. Introduction
  2. The CUORE experiment
  3. Data taking campaigns
  4. Data acquisition
  5. Data production and analysis
  6. Reducing the noise in CUORE
  7. Data trigger
  8. Online derivative trigger
  9. Offline Optimum Trigger
  10. Thermal pulse amplitude reconstruction
  11. Thermal pulse basic parameters
  12. Optimum Filter (OF)
  13. Thermal gain stabilization
  14. Heater-based stabilization
  15. Calibration-based stabilization
  16. ...and 26 more sections

Figures (24)

  • Figure 1: Accumulated TeO$_2$ exposure since the beginning of data-taking is shown in blue. Cryogenic improvements for the operational stability and detectors optimization were implemented between 2017 and 2018 Nutini:2020vtdALDUINO:cryo2019. From 2019, the experiment has been in stable data taking at 11 -- 15 mK, with a strikingly high duty cycle ($\sim$90%) for the cryogenic calorimetric technology CUORE:2021ctv. TeO$_2$ exposures after analysis cuts corresponding to major data releases are also shown in yellow and orange.
  • Figure 2: Breakdown of the CUORE run-time by measurement type since the beginning of stable data-taking starting in 2019. Down Time corresponds to periods during which no data is recorded.
  • Figure 3: Noise spectral shape of a single channel-dataset (Ch-DS) before and after the denoising using accelerometers and seismometers.
  • Figure 4: Events flagged by the three trigger types: signal, noise, and pulser. In general, the signal waveforms exhibit rise times (from 10 -- 90% of the pulse height) of 50 -- 200 ms and decay times (from 90 -- 30% of the pulse height) of 500 ms -- 1 s.
  • Figure 5: Example of single pulse and pile-up events. The variables associated with the main event are listed. The 10-s event window begins $\sim$3 s before the main event.
  • ...and 19 more figures