Single parameter galaxy classification: The Principal Curve through the multi-dimensional space of galaxy properties
M. Taghizadeh-Popp, S. Heinis, A. S. Szalay

TL;DR
This paper introduces a novel one-parameter galaxy classification method using a principal curve through multi-dimensional galaxy data, revealing distinct populations and supporting physical models in extragalactic astronomy.
Contribution
It presents a new single-parameter galaxy classification approach based on a principal curve, capturing galaxy diversity and physical processes with dimensionality reduction.
Findings
The principal curve has a 'W' shape with 3 turning points, defining 4 galaxy populations.
Galaxy properties vary systematically along the curve, reflecting different evolutionary stages.
Supports hierarchical merging and star formation quenching models in galaxy evolution.
Abstract
We propose to describe the variety of galaxies from SDSS by using only one affine parameter. To this aim, we build the Principal Curve (P-curve) passing through the spine of the data point cloud, considering the eigenspace derived from Principal Component Analysis of morphological, physical and photometric galaxy properties. Thus, galaxies can be labeled, ranked and classified by a single arc length value of the curve, measured at the unique closest projection of the data points on the P-curve. We find that the P-curve has a "W" letter shape with 3 turning points, defining 4 branches that represent distinct galaxy populations. This behavior is controlled mainly by 2 properties, namely u-r and SFR. We further present the variations of several galaxy properties as a function of arc length. Luminosity functions variate from steep Schechter fits at low arc length, to double power law and…
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