Brown Dwarfs are Violet: Python Tools for the Estimation of Human-eye Colors of Stars and Substellar Objects

The accompanying files include a Python Jupyter notebook (and associated data files read in by the Python code) that carry out the calculations described by Cranmer (2023), talk 246.05 presented at the 241st Meeting of the American Astronomical Society (AAS) in Seattle, Washington. The abstract of the talk is provided here:

There has always been interest in the perceived colors of the stars.  They were key to the development of the H-R diagram, and they are also used widely in educational and public-outreach imagery.  Thus, it is useful to develop software tools to compute these colors, as accurately as possible, from spectral energy distributions.  This presentation follows up on an RNAAS paper (Cranmer 2021) that presented a collection of objective (CIE coordinate) and subjective (RGB triple) colors for main-sequence stars and brown dwarfs.  A new empirical method of converting from CIE to RGB values is described, and results for various stellar spectra are presented.  Although brown dwarfs over a wide range of effective temperatures (400 to 2000 K) emit most of their flux in the infrared, their visible spectra often exhibit a local maximum around a strong dip in the Na I cross section at 0.4-0.5 microns.  Thus, they may appear purple to human eyes.  Also, the hottest (O-type) main-sequence stars may appear even "bluer than the blue sky" because of Paschen continuum absorption.  This presentation will update earlier stellar and brown-dwarf color estimates using more recently published synthetic spectra, and it will also investigate the effects of atmospheric absorption, over a range of air-mass values, on these perceived colors.  Python Jupyter notebooks that carry out these calculations will be uploaded to the Zenodo repository for open-access distribution.

NOTE 1: The algorithms described here, for computing RGB triples, ought to be considered as preliminary results in ongoing research; i.e., they need additional testing and validation by comparing to the results of other more established ways of converting astronomical spectra to perceived colors.

NOTE 2: These files follow on from those provided in another Zenodo upload associated with the 2021 RNAAS paper: https://doi.org/10.5281/zenodo.5293307