Inversion of neutron/gamma spectra from scintillator measurements

The Radiation Assessment Detector (RAD) on-board NASA's Mars Science laboratory (MSL) rover will measure charged particles as well as neutron and gamma radiation on the Martian surface. Neutral particles are an important contribution to this radiation environment. RAD measures them with a CsI (TI) and a plastic scintillator, which are both surrounded by an anticoincidence. The incident neutron/gamma spectrum is obtained from the measurements using inversion methods which often fit a functional behavior, e.g., a power law, to the measured data applying the instrument response function and, e.g., a least-squares method. In situations where count rates are small, i.e., where the stochastic nature of the measurement is evident, maximum likelihood estimates with underlying Poissonian statistics improve the resulting spectra. We demonstrate the measurement and inversion of gamma/neutron spectra for a detector concept featuring one high-density scintillator and one high-proton-content scintillator. The applied inversion methods derive the original spectra without any strong assumptions of the functional behavior. Instrument response functions are obtained from Monte-Carlo simulations in matrix form with which the instrument response is treated as a set of linear equations. Using the response matrices we compare a constrained least-squares minimization, a chi-squared minimization and a maximum likelihood method with underlying Poissonian statistics. We make no assumptions about the incident particle spectrum and the methods intrinsically satisfy the constraint of non-negative counts. We analyzed neutron beam measurements made at the Physikalisch Technische Bundesanstalt (PTB) and inverted the measurement data for both neutron and gamma spectra. Monte-Carlo-generated measurements of the expected Martian neutron/gamma spectra were inverted as well, here the maximum likelihood method with underlying Poissonian statistics produces significantly better results. (C) 2011 Elsevier B.V. All rights reserved.