Analysis of gamma-ray spectrum obtained with CdZnTe-Detectors using the ROOT CERN software framework

Abstract

Semiconductor CdZnTe gamma spectrometers allow the implementation of new radiation monitoring technologies. However, the energy resolution from 5 to 10 keV and the small size of the detector may result in the detector being unable to resolve photopeaks with very close energies. Algorithms deduce the source identity from the spectrum and must rely on a well-established peak separation in cases where multiple sources are involved. Some techniques exist, but they are computationally expensive, both in memory and processor speed. Typically they can lead to critical performance problems when run on single board computers. To solve this problem, spectral deconvolution methods such as Gold or Richardson-Lucy algorithms have been proposed, that somewhat resolve the complex spectrum. The realized functions of spectra processing implemented in the ROOT CERN allow solving the indicated contradictions. The article presents the results of using ROOT CERN on a single-board computer for analyzing the spectra measured with a CdZnTe spectrometer. The results show that the spectral deconvolution methods used have high accuracy and efficiency in the deconvolution of complex spectra.