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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.

 

DarkSide-50 has demonstrated the high potential of dual-phase liquid argon time projection chambers in exploring interactions of WIMPs in the GeV/c2 mass range. The technique, based on the detection of the ionization signal amplified via electroluminescence in the gas phase, allows to explore recoil energies down to the sub-keV range. We report here on the DarkSide-50 measurement of the ionization yield of electronic recoils down to about 180 eVer, exploiting 37Ar and 39Ar decays, and extrapolated to a few ionization electrons with the Thomas-Imel box model. Moreover, we present the determination of the ionization response to nuclear recoils down to ∼ 500 eVnr , the lowest ever achieved in liquid argon, using in situ neutron calibration sources and external datasets from neutron beam experiments.