Isophote shape analysis and the unfortunate subtlety of dwarf galaxy structure

Watkins, A. E., Lazar, I., Sedgwick, T., Martin, G., Kaviraj, S., Kakkad, D., Collins, C. and Bichang'a, B. (2026) Isophote shape analysis and the unfortunate subtlety of dwarf galaxy structure. Monthly Notices of the Royal Astronomical Society (MNRAS), 547 (4). ISSN 0035-8711
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Dwarf galaxies ($M_{*}/M_{\odot} \lesssim 10^{9.5}$), being sensitive to key evolutionary drivers like baryonic feedback and tidal perturbation, are crucial for understanding galaxy evolution as a whole. Their abundance and faintness, however, ensures that most will be studied primarily via broadband imaging for the foreseeable future. It is thus crucial to identify the most informative broadband-derivable quantities in the dwarf regime. As studies of widely used morphological parameters like concentration, asymmetry, and smoothness suggest these lack discriminatory power among dwarfs, we assess alternatives derived from isophotes: position angle twists, ellipticity, deviations from pure ellipses, and residuals to single-Sérsic profile fits. Using these parameters, we compare dwarf populations with massive galaxies of the same morphological class, and among themselves by morphological class. Only dwarf spirals may differ from their massive counterparts, being structurally simpler; dwarf and massive early type galaxy (ETG) isophotal similarity suggests all dwarf ETGs may be triaxial. Among only dwarfs, morphological classes are indistinguishable in this parameter space. A principal component analysis (PCA) using all available morphological, isophotal, and physical parameters expands on this: no PC explains more than $\sim$26% of the population variance, and no clear multimodality appears in any pairwise PC projection. We find similarly moderate spectral clustering, with a silhouette score of only 0.35. Given this self-similarity, parsing dwarf galaxy evolution from photometric parameters alone will likely require detailed statistical analysis of large dwarf populations in a high-dimensional parameter space, a task suitable for up-coming large-scale surveys like the Legacy Survey of Space and Time.


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