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Spatial and Temporal Variations of the Chandra ACIS Particle-Induced Background and Development of a Spectral-Model Generation Tool
- Publication Year :
- 2021
-
Abstract
- In X-ray observations, estimation of the particle-induced background is important especially for faint and/or diffuse sources. Although software exists to generate total (sky and detector) background data suitable for a given Chandra ACIS observation, no public software exists to model the particle-induced background separately. We aim to understand the spatial and temporal variations of the particle-induced background of Chandra ACIS obtained in the two data modes, VFAINT and FAINT. Observations performed with ACIS in the stowed position shielded from the sky and the Chandra Deep Field South data sets are used. The spectra are modeled with a combination of the instrumental lines of Al, Si, Ni, and Au and continuum components. Similar spatial variations of the spectral shape are found in VFAINT and FAINT data, which are mainly due to inappropriate correction of charge transfer inefficiency for events that convert in the frame-store regions as explained by Bartalucci et al. 2014. Temporal variation of the spectral hardness ratio is found to be $\sim 10\%$ at maximum, which seems to be largely due to solar activity. We model this variation by modifying the spectral hardnesses according to the total count rate. Incorporating these properties, we have developed a tool ``mkacispback'' to generate the particle-induced background spectral model corresponding to an arbitrary celestial observation. As an example application, we use the background spectrum produced by the mkacispback tool in an analysis of the Cosmic X-ray Background in the CDF-S observations. We find an intensity of 3.10 (2.98--$3.21)\times 10^{-12}$ erg s$^{-1}$ cm$^{-2}$ deg$^{-2}$ in the 2--8 keV band, consistent with or lower than previous estimates. The tool mkacispback is available at https://github.com/hiromasasuzuki/mkacispback.<br />Comment: 23 pages, 26 figures, accepted for publication in A&A
Details
- Database :
- OAIster
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1312087288
- Document Type :
- Electronic Resource
- Full Text :
- https://doi.org/10.1051.0004-6361.202141458