Year: 2025
Type: article
Abstract: Accurate spectral analysis of high-energy astrophysical sources often relies on comparing observed data to incident spectral models convolved with the instrument response. However, for gamma-ray bursts and other high-energy transient events observed at high count rates, significant distortions (e.g., pile-up, dead time, and large signal trailing) are introduced, complicating this analysis. We present a method framework to address the model dependence problem, especially to solve the problem of energy spectrum distortion caused by instrument signal pile-up due to high counting rate and high-rate effects, applicable to X-ray, gamma-ray, and particle detectors. Our approach combines physics-based Monte Carlo (MC) simulations with a model-independent spectral inversion technique. The MC simulations quantify instrumental effects and enable correction of the distorted spectrum. Subsequently, the inversion step reconstructs the incident spectrum using an inverse response matrix approach, conceptually equivalent to deconvolving the detector response. The inversion employs a convolutional neural network, selected for its numerical stability and effective handling of complex detector responses. Validation using simulations across diverse input spectra demonstrates high fidelity. Specifically, for 27 different parameter sets of the brightest gamma-ray bursts, goodness-of-fit tests confirm the reconstructed spectra are in excellent statistical agreement with the input spectra and residuals are typically within ±2 σ . This method enables precise analysis of intense transients and other high-flux events, overcoming limitations imposed by instrumental effects in traditional analyses.
Source: The Astrophysical Journal
Authors: Zhi-Qiang Ding, Xin-Qiao Li, Da-Li Zhang, Zheng-Hua An, Zhen-Xia Zhang, Roberto Battiston, Roberto Iuppa, Zhuo Li, Yan-Qiu Zhang, Yan Huang, Chao Zheng, Yan-Bing Xu, Xiao-Yun Zhao, Lu Wang, Ping Wang, Hong Lu
Institutions: Chinese Academy of Sciences, Institute of High Energy Physics, University of Chinese Academy of Sciences, National Institute of Natural Hazards, Ministry of Emergency Management of the People's Republic of China, Istituto Nazionale di Fisica Nucleare, University of Trento, Peking University, Anhui University
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $4,499
OpenAlex ID: W7106228077
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