Inversion of stellar spectral radiative properties based on multiple star catalogues
Chuanxin Zhang, Yuan Yuan, Zhaoyang Yu, Fuqiang Wang, Heping Tan

TL;DR
This paper presents a computational model that inverts stellar spectral flux densities to determine physical parameters using multiple star catalogues and an optimization algorithm, aiding star detection and recognition.
Contribution
The study introduces a novel inversion method combining physical modeling and particle swarm optimization across multiple star catalogues.
Findings
Good agreement with MSX and 2MASS catalogues
Inversion accuracy varies across different catalogues
Provides a reliable way to calculate spectral flux density from physical parameters
Abstract
The spectral flux density of stars can indicate their atmospheric physical properties. A detector can obtain any band flux density at the design stage. However, the band flux density is confirmed and fixed in the process of operation because of the restriction of filters. Other band flux densities cannot be obtained through the same detector. In this study, a computational model of stellar spectral flux density is established based on basic physical parameters which are effective temperature and angular parameter. The stochastic particle swarm optimization algorithm is adopted to address this issue with appropriately chosen values of the algorithm parameters. Four star catalogues are studied and consist of the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST), Wide-field Infrared Survey Explorer (WISE), Midcourse Space Experiment (MSX), and Two Micron All Sky Survey…
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