Cluster Infall for Mass Calibration in the Stage-IV Era

Abstract

The outskirts of galaxy clusters present a promising avenue for constraining cluster masses in a way that is robust to the impact of baryonic physics. We assess the accuracy to which the cluster infall regions can be used to for cluster mass calibration. Building on previous work, we parameterize the velocity distribution $P(v_{\rm r},v_{\rm tan}|r,M)$ of dark matter halos on scales $r \geq 5\ h^{-1}\ \rm{Mpc}$ as the product of the marginalized distribution $P(v_{\rm r}|r,M)$ and the conditional distribution $P(v_{\rm tan}|v_{\rm r},r,M)$, calibrating the radial and mass dependence of these distributions in numerical simulations. We then project our model along the line-of-sight to obtain accurate predictions for the distributions of line-of-sight velocities at a given projected radius and cluster mass $P(v_{\rm LOS}|R,M)$, which we can observe with spectroscopic survey data. With our model, we forecast that spectra from the Dark Energy Spectroscopic Instrument (DESI) can constrain cluster masses with sub-percent level precision, comparable to that of Stage IV weak lensing surveys.

Figures (7)

• Figure 1: Marginal distributions of radial velocities in several narrow radial bins and several halo mass bins. For each we show fits to the individual bin using the two parameter JSU model with the dashed curves and the best-fit model accounting for mass dependence outlined in \ref{['sec:rad']} in the solid curves. The vertical lines indicate the peaks of each distribution and ${v_{\rm r}} = 0$.
• Figure 2: Distributions of the marginal tangential velocities in distributions in several narrow radial bins and halo mass bins. For each we show with a smooth curve the result from marginalizing over the best-fit model outlined in Section \ref{['sec:tan']}, and with a dashed curve that from directly fitting the variance of the conditional distributions.
• Figure 3: Comparison of the $68\%$, $95\%$, and $97\%$ intervals of the joint distributions (solid contours) and the smooth model (dashed contours) outlined in Section \ref{['sec:VD']}, smoothed with a gaussian filter. We show the joint distributions for three radial bins (columns) and three halo mass bins (rows). Black dotted lines indicate $v_{\rm r}, v_{\rm t}=0$.
• Figure 4: Top: The halo-galaxy correlation function measured for MDPL2 Rockstar halos and UniverseMachine galaxies in each of our halo mass bins. Uncertainties are computed by jackknifing halos within sub-boxes of the simulation box. The solid curves show our best-fit of the PhysRevD.111.043527 model for total halo-galaxy correlation function. The orbiting and infalling components of this model for the lowest and highest mass bins are shown with dashed curves. Additionally, the corresponding measured orbiting components are shown as points without uncertainties. The minimum radial bin edge used for our analysis of the velocity distributions is indicated by the vertical black dotted line. Bottom: Percent difference between data and model for $\xi_{\rm hg}(r|M)$. The dark and light gray bands indicate differences with $5\%$ and $10\%$, respectively.
• Figure 5: The distribution of peculiar LOS velocities in several bins of projected radius and LOS separation in our lowest, central and highest mass bins, inspired by Fig. 7 of zuweinberg13. Curves show the result of the integration in equation \ref{['eqn:Pvlos_2d']} and vertical dotted lines indicate $v_{\rm r}=0$.