Application and performance of an ML-EM algorithm in NEXT

NEXT Collaboration: A. Sim\'on , C. Lerche , F. Monrabal , J.J. G\'omez-Cadenas , V. \'Alvarez , C.D.R. Azevedo , J.M. Benlloch-Rodr\'iguez , F.I.G.M. Borges

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A. Botas S. C\'arcel J.V. Carri\'on S. Cebri\'an C.A.N. Conde J. D\'iaz M. Diesburg J. Escada R. Esteve R. Felkai L.M.P. Fernandes P. Ferrario A.L. Ferreira E.D.C. Freitas A. Goldschmidt D. Gonz\'alez-D\'iaz R.M. Guti\'errez J. Hauptman C.A.O. Henriques A.I. Hernandez J.A. Hernando Morata V. Herrero B.J.P. Jones L. Labarga A. Laing P. Lebrun I. Liubarsky N. L\'opez-March M. Losada J. Mart\'in-Albo G. Mart\'inez-Lema A. Mart\'inez A.D. McDonald C.M.B. Monteiro F.J. Mora L.M. Moutinho J. Mu\~noz Vidal M. Musti M. Nebot-Guinot P. Novella D.R. Nygren B. Palmeiro A. Para J. P\'erez M. Querol J. Renner L. Ripoll J. Rodr\'iguez L. Rogers F.P. Santos J.M.F. dos Santos C. Sofka M. Sorel T. Stiegler J.F. Toledo J. Torrent Z. Tsamalaidze J.F.C.A. Veloso R. Webb J.T. White N. Yahlali

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classification ⚛️ physics.ins-det hep-ex

keywords algorithmnextapplieddetectorfullmethodml-emachieves

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The goal of the NEXT experiment is the observation of neutrinoless double beta decay in $^{136}$Xe using a gaseous xenon TPC with electroluminescent amplification and specialized photodetector arrays for calorimetry and tracking. The NEXT Collaboration is exploring a number of reconstruction algorithms to exploit the full potential of the detector. This paper describes one of them: the Maximum Likelihood Expectation Maximization (ML-EM) method, a generic iterative algorithm to find maximum-likelihood estimates of parameters that has been applied to solve many different types of complex inverse problems. In particular, we discuss a bi-dimensional version of the method in which the photosensor signals integrated over time are used to reconstruct a transverse projection of the event. First results show that, when applied to detector simulation data, the algorithm achieves nearly optimal energy resolution (better than 0.5% FWHM at the Q value of $^{136}$Xe) for events distributed over the full active volume of the TPC.

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Application and performance of an ML-EM algorithm in NEXT

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