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The objective of the cyclotron radiation emission spectroscopy (CRES) technology is to build precise particle energy spectra. This is achieved by identifying the start frequencies of charged particle trajectories which, when exposed to an external magnetic field, leave semi-linear profiles (called tracks) in the time–frequency plane. Due to the need for excellent instrumental energy resolution in application, highly efficient and accurate track reconstruction methods are desired. Deep learning convolutional neural networks (CNNs) - particularly suited to deal with information-sparse data and which offer precise foreground localization—may be utilized to extract track properties from measured CRES signals (called events) with relative computational ease. In this work, we develop a novel machine learning based model which operates a CNN and a support vector machine in tandem to perform this reconstruction. A primary application of our method is shown on simulated CRES signals which mimic those of the Project 8 experiment—a novel effort to extract the unknown absolute neutrino mass value from a precise measurement of tritiumβ⁻-decay energy spectrum. When compared to a point-clustering based technique used as a baseline, we show a relative gain of 24.1% in event reconstruction efficiency and comparable performance in accuracy of track parameter reconstruction.

The Cryogenic Underground Observatory for Rare Events (CUORE) is the first cryogenic experiment searching for$$0\nu \beta \beta $$$0\nu \beta \beta$decay that has been able to reach the one-tonne mass scale. The detector, located at the Laboratori Nazionali del Gran Sasso (LNGS) in Italy, consists of an array of 988$${\mathrm{TeO}}_{2}$$${\mathrm{TeO}}_2$crystals arranged in a compact cylindrical structure of 19 towers. CUORE began its first physics data run in 2017 at a base temperature of about 10 mK and in April 2021 released its$$3{\mathrm{rd}}$$$3\mathrm{rd}$result of the search for$$0\nu \beta \beta $$$0\nu \beta \beta$, corresponding to a tonne-year of$$\mathrm{TeO}_{2}$$${\mathrm{TeO}}_2$exposure. This is the largest amount of data ever acquired with a solid state detector and the most sensitive measurement of$$0\nu \beta \beta $$$0\nu \beta \beta$decay in$${}^{130}\mathrm{Te}$$${}^{130}\mathrm{Te}$ever conducted . We present the current status of CUORE search for$$0\nu \beta \beta $$$0\nu \beta \beta$with the updated statistics of one tonne-yr. We finally give an update of the CUORE background model and the measurement of the$${}^{130}\mathrm{Te}$$${}^{130}\mathrm{Te}$$$2\nu \beta \beta $$$2\nu \beta \beta$decay half-life and decay to excited states of$${}^{130}\mathrm{Xe}$$${}^{130}\mathrm{Xe}$, studies performed using an exposure of 300.7 kg yr.