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Dark matter may induce an event in an Earth-based detector, and its event rate is predicted to show an annual modulation as a result of the Earth’s orbital motion around the Sun. We searched for this modulation signature using the ionization signal of the DarkSide-50 liquid argon time projection chamber. No significant signature compatible with dark matter is observed in the electron recoil equivalent energy range above $40{\mathrm{eV}}_{\mathrm{ee}}$, the lowest threshold ever achieved in such a search. Published by the American Physical Society2024 

Abstract The stability of a dark matter detector on the timescale of a few years is a key requirement due to the large exposure needed to achieve a competitive sensitivity. It is especially crucial to enable the detector to potentially detect any annual event rate modulation, an expected dark matter signature. In this work, we present the performance history of the DarkSide-50 dual-phase argon time projection chamber over its almost three-year low-radioactivity argon run. In particular, we focus on the electroluminescence signal that enables sensitivity to sub-keV energy depositions. The stability of the electroluminescence yield is found to be better than 0.5%. Finally, we show the temporal evolution of the observed event rate around the sub-keV region being consistent to the background prediction. 

Abstract We present a novel approach for the search of dark matter in the DarkSide-50 experiment, relying on Bayesian Networks. This method incorporates the detector response model into the likelihood function, explicitly maintaining the connection with the quantity of interest. No assumptions about the linearity of the problem or the shape of the probability distribution functions are required, and there is no need to morph signal and background spectra as a function of nuisance parameters. By expressing the problem in terms of Bayesian Networks, we have developed an inference algorithm based on a Markov Chain Monte Carlo to calculate the posterior probability. A clever description of the detector response model in terms of parametric matrices allows us to study the impact of systematic variations of any parameter on the final results. Our approach not only provides the desired information on the parameter of interest, but also potential constraints on the response model. Our results are consistent with recent published analyses and further refine the parameters of the detector response model. 

Abstract Cosmogenic radio-nuclei are an important source of background for low-energy neutrino experiments. In Borexino, cosmogenic $$^{11}$$ 11 C decays outnumber solar pep and CNO neutrino events by about ten to one. In order to extract the flux of these two neutrino species, a highly efficient identification of this background is mandatory. We present here the details of the most consolidated strategy, used throughout Borexino solar neutrino measurements. It hinges upon finding the space-time correlations between $$^{11}$$ 11 C decays, the preceding parent muons and the accompanying neutrons. This article describes the working principles and evaluates the performance of this Three-Fold Coincidence (TFC) technique in its two current implementations: a hard-cut and a likelihood-based approach. Both show stable performances throughout Borexino Phases II (2012–2016) and III (2016–2020) data sets, with a $$^{11}$$ 11 C tagging efficiency of $$\sim 90$$ ∼ 90  % and $$\sim $$ ∼  63–66 % of the exposure surviving the tagging. We present also a novel technique that targets specifically $$^{11}$$ 11 C produced in high-multiplicity during major spallation events. Such $$^{11}$$ 11 C appear as a burst of events, whose space-time correlation can be exploited. Burst identification can be combined with the TFC to obtain about the same tagging efficiency of $$\sim 90\%$$ ∼ 90 % but with a higher fraction of the exposure surviving, in the range of $$\sim $$ ∼  66–68 %.