EXPLORE: Fitting Model Spectra Energy Distributions to Multi-Band Photometric Data

Abstract

In this study, the catalogues of the Python Stellar Spectral Energy Distribution (PySSED) code are built upon by incorporating multi-band photometric data from miniJPAS, a narrow-band survey with a 1 deg2 survey field. The methodology employed for the integration of these new data files not native to PySSED is discussed. Data analysis involves a comparison of the stellar parameters derived from the miniJPAS data with those from a control photometric dataset, specifically Gaia. This comparative study extends to using simulated datasets from the Besançon Galaxy Model to validate the derivations made by PySSED both without and with the inclusion of the miniJPAS data. Further applications of the addition of narrow-band data in PySSED are explored, largely regarding white dwarfs. There were several key findings of this study. PySSED has a systematic tendency to under-predict Te f f at lower temperatures (∼ 3000K) and where there was data, overpredict at higher temperatures (∼ 6500K). The addition of the multi-band photometric data appears to make PySSED less accurate at deriving Te f f for main sequence stars when compared with literature sources. In application to white dwarfs, the addition of miniJPAS data appears to have little effect on Te f f derivation, but is a large improvement for log(g) derivation. Reasoning for the performance of PySSED is discussed, with avenues for future improvement suggested.

Date of Award	1 Aug 2024
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Albert Zijlstra (Supervisor) & Iain Mcdonald (Supervisor)