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Application and performance of an ML-EM algorithm in NEXT
2020-06-15T09:36:45+00:002017-11-21T12:27:35+00:00Sergio Pastor Carpi
NEXT Collaboration(Simon, A. et al), Gomez-Cadenas, J. J., Alvarez, V., Benlloch-Rodriguez, J. M., Botas, A., Carcel, S., et al. (2017). Application and performance of an ML-EM algorithm in NEXT. J. Instrum., 12, P08009–22pp.
The goal of the NEXT experiment is the observation of neutrinoless double beta decay in Xe-136 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 136Xe) for events distributed over the full active volume of the TPC.
Application and performance of an ML-EM algorithm in NEXTNEXT Collaboration(Simon, A. et al)Gomez-Cadenas, J.J.Alvarez, V.Benlloch-Rodriguez, J.M.Botas, A.Carcel, S.Carrion, J.V.Diaz, J.Felkai, R.Ferrario, P.Laing, A.Liubarsky, I.Lopez-March, N.Martin-Albo, J.Martinez, A.Muñoz Vidal, J.Musti, M.Nebot-Guinot, M.Novella, P.Palmeiro, B.Perez, J.Querol, M.Renner, J.Rodriguez, J.Sorel, M.Torrent, J.Yahlali, N.info:doi/10.1088/1748-0221/12/08/P08009openurl:?ctx_ver=Z39.88-2004&rfr_id=info%3Asid%2Fhttps%3A%2F%2Freferences.ific.uv.es%2Frefbase%2F&genre=article&atitle=Application%20and%20performance%20of%20an%20ML-EM%20algorithm%20in%20NEXT&title=Journal%20of%20Instrumentation&stitle=J.%20Instrum.&issn=1748-0221&date=2017&volume=12&aulast=NEXT%20Collaboration%20%28Simon&aufirst=A.%20et%20al%29&au=Gomez-Cadenas%2C%20J.%20J.&au=Alvarez%2C%20V.&au=Benlloch-Rodriguez%2C%20J.%20M.&au=Botas%2C%20A.&au=Carcel%2C%20S.&au=Carrion%2C%20J.V.&au=Diaz%2C%20J.&au=Felkai%2C%20R.&au=Ferrario%2C%20P.&au=Laing%2C%20A.&au=Liubarsky%2C%20I.&au=Lopez-March%2C%20N.&au=Martin-Albo%2C%20J.&au=Martinez%2C%20A.&au=Mu%C3%B1oz%20Vidal%2C%20J.&au=Musti%2C%20M.&au=Nebot-Guinot%2C%20M.&au=Novella%2C%20P.&au=Palmeiro%2C%20B.&au=Perez%2C%20J.&au=Querol%2C%20M.&au=Renner%2C%20J.&au=Rodriguez%2C%20J.&au=Sorel%2C%20M.&au=Torrent%2C%20J.&au=Yahlali%2C%20N.&pub=Iop%20Publishing%20Ltd&id=info%3Adoi%2F10.1088%2F1748-0221%2F12%2F08%2FP08009&sid=refbase%3AIFICcitekey:NEXTCollaborationSimon_etal2017NEXT Collaboration(Simon, A. et al), Gomez-Cadenas, J. J., Alvarez, V., Benlloch-Rodriguez, J. M., Botas, A., Carcel, S., et al. (2017). Application and performance of an ML-EM algorithm in NEXT. J. Instrum., 12, P08009-22pp.2017JournalArticletextGaseous imaging and tracking detectorsImage reconstruction in medical imagingTime projection Chambers (TPC)Medical-image reconstruction methods and algorithmscomputer-aided softwareurl:http://arxiv.org/abs/1705.10270Iop Publishing LtdEnglish1748-0221Journal of Instrumentation2017120800922