The limitations (and potential) of non-parametric morphology statistics for post-merger identification

Understand

Non-parametric morphology statistics have been used for decades to classify galaxies into morphological types and identify mergers in an automated way.

• In this work, we assess how reliably we can identify galaxy post-mergers with non-parametric morphology statistics.
• Low-redshift (z<0.2), recent (t_post-merger < 200 Myr), and isolated (r > 100 kpc) post-merger galaxies are drawn from the IllustrisTNG100-1 cosmological simulation.
• Synthetic r-band images of the mergers are generated with SKIRT9 and degraded to various image qualities, adding observational effects such as sky noise and atmospheric blurring.