Galaxy interactions in IllustrisTNG-100, I: The power and limitations of visual identification
Kelly Blumenthal, Jorge Moreno, Joshua E. Barnes, Lars Hernquist, Paul, Torrey, Zachary Claytor, Vicente Rodriguez-Gomez, Federico Marinacci, Mark, Vogelsberger

TL;DR
This study assesses the effectiveness of visual classification in identifying galaxy interactions using simulated images, revealing significant biases towards massive, recently interacting pairs and highlighting limitations in current observational methods.
Contribution
It demonstrates that visual indicators only correctly identify galaxy interactions about 45% of the time and shows biases toward massive, recent interactions, informing future observational strategies.
Findings
Visual classification correctly identifies ~45% of interacting galaxies.
Massive, recently close pairs are more likely to be visually identified.
Biases in merger rate estimates favor massive, recently interacting galaxies.
Abstract
We present a sample of 446 galaxy pairs constructed using the cosmological simulation IllustrisTNG-100 at z = 0, with M = 10-10 M. We produce ideal mock SDSS g-band images of all pairs to test the reliability of visual classification schema employed to produce samples of interacting galaxies. We visually classify each image as interacting or not based on the presence of a close neighbour, the presence of stellar debris fields, disturbed discs, and/or tidal features. By inspecting the trajectories of the pairs, we determine that these indicators correctly identify interacting galaxies of the time. We subsequently split the sample into the visually identified interacting pairs (VIP; 38 pairs) and those which are interacting but are not visually identified (nonVIP; 47 pairs). We find that VIP have undergone a close passage nearly twice as…
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