Intrinsic Shapes of Very Flat Elliptical Galaxies

TL;DR

This study combines photometric data with triaxial mass models to statistically infer the intrinsic shapes of very flat elliptical galaxies, revealing shape variations across different radii.

Contribution

It introduces a Bayesian method to derive intrinsic shape distributions of elliptical galaxies using combined photometric data and triaxial models.

Findings

Shape variation is quantified by Bayesian probability distributions.

Best constrained parameters include axial ratios and triaxiality differences.

Method applied to specific galaxies reveals detailed shape characteristics.

Abstract

Photometric data from the literature is combined with triaxial mass models to derive variation in the intrinsic shapes of the light distribution of elliptical galaxies NGC 720, 2768 and 3605. The inferred shape variation in given by a Bayesian probability distribution, assuming a uniform prior. The likelihood of obtaining the data is calculated by using ensemble of triaxial models. We apply the method to infer the shape variation of a galaxy, using the ellipticities and the difference in the position angles at two suitably chosen points from the profiles of the photometric data. Best constrained shape parameters are found to be the short to long axial ratios at small and large radii, and the absolute values of the triaxiallity difference between these radii.