2026A&A...706A.319K

We present a physically interpretable framework to quantify dynamical disturbances in galaxy clusters using projected two-dimensional phase-space information. Based on the TNG-Cluster simulation, we constructed a disturbance score that captures merger-driven asymmetries through features such as velocity dispersion and Gaussian mixture model (GMM) peak fitting, which captures asymmetries indicative of dynamical disturbance. All features were derived from observable quantities and are intended to be measurable in future surveys. To enable observational application, we adopted a simplified estimator using aperture mass map statistics as a mass ratio proxy in TNG300-1, and validated its performance with weak lensing data from The Local Volume Complete Cluster Survey (LoVoCCS). While phase-space diagnostics reveal merger-driven asymmetries, they are not sensitive to whether the secondary progenitor is infalling or receding, and thus cannot distinguish future mergers from past mergers. To address this, we incorporated the star formation rate (SFR) from TNG-Cluster and propose the blue galaxy fraction as a promising observational tracer of merger timing. Finally, we constructed mock Chandra X-ray images of TNG-Cluster halos at redshift z = 0.2, and find that the offset between the X-ray peak and the position of the most massive black hole (used as a proxy for the brightest cluster galaxy) correlates with our disturbance score, serving as a consistency check. We also performed case studies using LoVoCCS observational data, correlating the blue galaxy fraction with disturbance scores derived from the eROSITA morphology catalog.