Detectability of satellite planes in mock observations of isolated L * galaxies
Year: 2026
Type: article
Abstract: ABSTRACT The existence and prevalence of planar, co-rotating distributions of satellite galaxies around $L_*$ host galaxies in the local Universe remains a subject of ongoing debate. Despite numerous observational efforts over the past decade, a statistically robust sample of ‘satellite planes’ across the diversity of host galaxy environments is lacking. To guide future observing strategies, we construct a controlled suite of mock observations of on-sky positions and line-of-sight (LOS) velocities of isolated $L_*$ host galaxies and their satellite systems, based on samples drawn from the illustris tng100-1 cosmological simulation to build a statistical sample. In these mock systems, satellite planes are defined by three key parameters: the number of satellites ($N_{\mathrm{sat}}$), the fraction residing in a thin co-rotating plane ($f_{p}$), and the orientation angle relative to the observer ($\theta _{\mathrm{rot}}$). We evaluate the sensitivity of three observational metrics, $N_{\mathrm{cor}}$ (number of co-rotating satellites), $b/a$ (projected flattening of the satellite distribution), and $v_\mathrm{los}$ (mean absolute LOS velocity), to the presence of such planes. Our results show that detection rates are strongly dependent on $\theta _{\mathrm{rot}}$ and $N_{\mathrm{sat}}$. Satellite planes that are viewed nearly edge-on or face-on, are the most readily detected. In contrast, intermediate orientations and systems with fewer satellites yield low detection success rates. Generally, only satellite planes with $N_{\mathrm{sat}}\gt 20$ have high chances of being detected. These findings provide a practical framework for prioritizing observational targets and designing future surveys aimed at detecting and characterizing satellite planes.
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,046
OpenAlex ID: W7131454082