Application and performance of an ML-EM algorithm in NEXT.

NEXT collaboration

Research output: Contribution to journalArticlepeer-review


The goal of the NEXT experiment is the observation of neutrinoless double beta decay in 136Xe 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.

Original languageEnglish (US)
Article numberP08009
JournalJournal of Instrumentation
Issue number8
StatePublished - Aug 16 2017


  • Gaseous imaging and tracking detectors
  • Image reconstruction in medical imaging
  • Medical-image reconstruction methods and algorithms, computer-aided software
  • Time projection Chambers (TPC)

ASJC Scopus subject areas

  • Instrumentation
  • Mathematical Physics


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