Smoothing Low Resolution Gamma Spectra

Abstract

The energy spectra of gamma-rays emitted by radioisotopes act as finger prints that enable identification of the source. Such identification from low-resolution NaI detectors over short time periods is challenging for several reasons, including the Poisson fluctuations in the recorded counts. Smoothing the data over neighboring energy bins can reduce the noise in the raw counts, at the cost of introducing a bias that de-emphasizes the peaks and valleys of a spectrum. This paper describes a new two-stage smoothing procedure that uses a multiplicative bias correction (MBC) for adjusting initial smoothed spectra. Applying the MBC to an initial smoother reduces bias of the initial smoother in the peaks and valleys with no or negligible increase in its variance. We illustrate the benefit of this new method on example real and simulated spectra.