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Abstract 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. 

Abstract CUPID, the CUORE Upgrade with Particle Identification, is a next-generation experiment to search for neutrinoless double beta decay ($$0\mathrm {\nu \beta \beta }$$ $0\nu \beta \beta$) and other rare events using enriched Li$$_{2}$$ $_2^{}$$$^{100}$$ $_{}^{100}$MoO$$_{4}$$ $_4^{}$scintillating bolometers. It will be hosted by the CUORE cryostat located at the Laboratori Nazionali del Gran Sasso in Italy. The main physics goal of CUPID is to search for$$0\mathrm {\nu \beta \beta }$$ $0\nu \beta \beta$of$$^{100}$$ $_{}^{100}$Mo with a discovery sensitivity covering the full neutrino mass regime in the inverted ordering scenario, as well as the portion of the normal ordering regime with lightest neutrino mass larger than 10 meV. With a conservative background index of 10$$^{-4}$$ $_{}^{-4}$ cts$$/($$ $/($keV$$\cdot $$ $·$kg$$\cdot $$ $·$yr$$)$$ $)$, 240 kg isotope mass, 5 keV FWHM energy resolution at 3 MeV and 10 live-years of data taking, CUPID will have a 90% C.L. half-life exclusion sensitivity of$$1.8\cdot 10^{27}$$ $1.8·{10}^{27}$ yr, corresponding to an effective Majorana neutrino mass ($$m_{\beta \beta }$$ $m_{\beta \beta }$) sensitivity of 9–15 meV, and a$$3\sigma $$ $3\sigma$discovery sensitivity of$$1\cdot 10^{27}$$ $1·{10}^{27}$ yr, corresponding to an$$m_{\beta \beta }$$ $m_{\beta \beta }$range of 12–21 meV. 

The Cryogenic Underground Observatory for Rare Events (CUORE) is a detector array comprised by 988 $5\mathrm{cm}\times 5\mathrm{cm}\times 5\mathrm{cm}$ ${\mathrm{TeO}}_2$crystals held below 20 mK, primarily searching for neutrinoless double-beta decay in ${}^{130}\mathrm{Te}$. Unprecedented in size among cryogenic calorimetric experiments, CUORE provides a promising setting for the study of exotic throughgoing particles. Using the first tonne year of CUORE’s exposure, we perform a search for hypothesized (FCPs), which are well-motivated by various standard model extensions and would have suppressed interactions with matter. Across the searched range of charges $e/24-e/2$no excess of FCP candidate tracks is observed over background, setting leading limits on the underground FCP flux with charges $e/24-e/5$at 90% confidence level. Using the low background environment and segmented geometry of CUORE, we establish the sensitivity of tonne-scale subkelvin detectors to diverse signatures of new physics. Published by the American Physical Society2024 

This Letter reports the first measurement of the oscillation amplitude and frequency of reactor antineutrinos at Daya Bay via neutron capture on hydrogen using 1958 days of data. With over 3.6 million signal candidates, an optimized candidate selection, improved treatment of backgrounds and efficiencies, refined energy calibration, and an energy response model for the capture-on-hydrogen sensitive region, the relative ${\overline{\nu }}_e$rates and energy spectra variation among the near and far detectors gives ${\sin }^{2}2{\theta }_{13}=0.0759_{-0.0049}^{+0.0050}$and $\mathrm{\Delta }{m}_{32}^2=\left(2.72_{-0.15}^{+0.14}\right)\times {10}^{-3}{\mathrm{eV}}^2$assuming the normal neutrino mass ordering, and $\mathrm{\Delta }{m}_{32}^2=(-2.83_{-0.14}^{+0.15})\times {10}^{-3}{\mathrm{eV}}^2$for the inverted neutrino mass ordering. This estimate of ${\sin }^{2}2{\theta }_{13}$is consistent with and essentially independent from the one obtained using the capture-on-gadolinium sample at Daya Bay. The combination of these two results yields ${\sin }^{2}2{\theta }_{13}=0.0833\pm 0.0022$, which represents an 8% relative improvement in precision regarding the Daya Bay full 3158-day capture-on-gadolinium result. Published by the American Physical Society2024