A Parametric Model to Reproduce the Background of the Insight-HXMT/HE Blind Detector

Abstract

Abstract The estimation of instrumental background is the basis of essentially all data analysis on observations with Insight-HXMT. The current Insight-HXMT/HE background model made by Liao et al. depends on the data from the HE blind detector, i.e., using historical data to make a preliminary estimation of the background spectra and using the real-time data from the blind detector to make a further modification. In order to decouple the dependence of background method on the blind detector, a parametric physical model has been developed to rebuild the light curve and spectrum of the HE blind detector. In this parametric model, several physical processes between the space environment and the satellite are considered to rebuild the prompt and delayed background signals of the HE blind detector. With the genetic algorithm and Markov Chain Monte Carlo procedure, the model parameters are determined by fitting the data from the HE blind detector. For all 62 energy bands in the range 28–334 keV for an exposure of 10 ks, the average systematic error of the background energy spectrum is ∼2.2% and the average total error of spectrum estimation ∼3.4%. It is found that more accurate background can be attained using this model than using the data from the Insight-HXMT/HE blind detector for exposures of less than 2 ks. These results show that the background of the Insight-HXMT/HE blind detector can be reproduced reliably with this parametric model and this method can also be applied to the background estimation of other detectors in principle.