Paper day for least-model-dependent astrophysics! On today's menu: an old-new mathem. robust galaxy clustering, a clever way to reduce large distance-uncertainties from non-redshift probes & our favourite friendly neighbouring cluster, Coma! 🧶🧶
https://arxiv.org/abs/2504.04135

#astronomy #astrophysics #cosmology #cosmicflows4 #DarkMatter #DarkEnergy

Unveiling the Coma Cluster Structure: From the Core to the Hubble Flow

The Coma cluster, embedded in a cosmic filament, is a complex and dynamically active structure in the local Universe. Applying a density-based member selection (dbscan) to data from the Sloan Digital Sky Survey (SDSS), we identify its virilised core and zero-velocity boundary. Cross-correlating with the Cosmicflows-4 (CF4) catalogue enables a velocity-distance analysis, incorporating radial infall models and redshift-independent distance estimators. This reveals, for the first time, the Hubble flow surrounding Coma, a first step to investigate the entanglement between the dark matter in bound objects and the dark energy driving the expansion of their surroundings. The distance to the Coma centre is determined as $69.959 \pm 0.012 \, h^{-1}~\text{Mpc}$. From dbscan, we infer a virial radius of $r_{\rm vir} = \left(1.95 \pm 0.12\right)\,h^{-1}~\text{Mpc}$ and a turnaround of $r_{\rm ta} \geq 4.87~{h}^{-1}~\mbox{Mpc}$. Combining the SDSS redshifts with the CF4 distances, we estimate the Hubble constant to be $H_0 = (73.10 \pm 0.92)~\mbox{km}/\mbox{s}/\mbox{Mpc}$. However, with different calibrations for the distance moduli, $H_0$ varies between $[72, 80]$ km/s/Mpc. Mass estimates via caustics, the virial theorem, and the Hubble-flow method yield $M = [0.77, 2.0] \times 10^{15}\,h^{-1}\,M_{\odot}$, consistent with prior studies. Our systematic approach maps the structure of Coma into the local Hubble flow and shows the degeneracies between dynamical parameters such as the Hubble constant, the virial radius, and the total mass.

arXiv.org
1) Take SDSS DR17 galaxies in the Coma region and select the Coma cluster in redshift space based on the local maxima and minima positions. (i.e. no cosmological model involved, no assumption how to split velocities along the line of sight)
2) Take this data and perform a density-based clustering on the sky to find the virial and the turnaround radius from the stable regions of the clustering parameters (this algorithm is mathem. more robust than the standard approaches and again involves no further models!)
3) Search for all cluster members that also have Cosmicflows-4 distances to set up a Hubble diagram. Yet, the dists usually has large uncertainties. To alleviate that issue, we anchor the dists at the (precise) cluster centre and Taylor expand around that.
4) For the Hubble flow diagram, we can use caustics to determine masses for our selections. If we use our 212 member gals with CF4 distances, we arrive at the same mass estimates and precision as Rines+2016 who used 1000 gals and a lot of add. model assumptions! 🤩
5) Last but not least, the biggest problem is not the lack of highly precise probes but the stats! We need to synchronise all probes to attain >1000 member gals and a representative sample of the cluster volume but this still causes a huge spread for H0 and absolute dists...

One last question, if someone knows: Turner & Gott 1976 were on the right track with density-based clustering, why was this changed to single-linkage ("friends-of-friends") over the course of time? From what I understand now, it was a change for the worse...

#HistoryOfCosmology #Cosmology #GalaxyCluster