Measuring Cosmological Distances Using Cluster Edges as a Standard Ruler
arxiv:2010.11324
Published:
Abstract:
The line-of-sight velocity dispersion profile of galaxy clusters exhibits a “kink” corresponding to the spatial extent of orbitinggalaxies. Because the spatial extent of a cluster is correlated with the amplitude of the velocity dispersion profile, we can utilisethis feature as a gravity-calibrated standard ruler. Specifically, the amplitude of the velocity dispersion data allows us to infer thephysical cluster size. Consequently, observations of the angular scale of the “kink” in the profile can be translated into a distancemeasurement to the cluster. Assuming the relation between cluster radius and cluster velocity dispersion can be calibrated fromsimulations, we forecast that with existing data from the Sloan Digital Sky Survey (SDSS) we will be able to measure the Hubbleconstant with3.0 %precision. Implementing our method with data from the Dark Energy Spectroscopic Instrument (DESI)will result in a1.3 %measurement of the Hubble constant. Adding cosmological supernova data improves the uncertainty ofthe DESI measurement to0.7 %. While these error estimates are statistical-only, they provide strong motivation for pursuingthe necessary simulation program required to characterise and calibrate the systematic uncertainties impacting our proposedmeasurement. Whether or not our proposed measurement can in fact result in competitive퐻0constraints will depend on whatthe eventual systematics floor for this method is.
Summary
This is a methods paper introducing a new distance measurement. It makes use of the results in Tomooka et al (2020) as a standard ruler that can be calibrated in simulations. It seems like it should give a competitive measurement of the Hubble contsant with DESI, although that will depend on how well-calibrated the cluster edge radius actually is and how much the measurement depends on other things like the cluster catalog used.
Comments
Accepted for publication in MNRAS (as of 7 April, 2021).
Recommended Citation
Erika L. Wagoner, Eduardo Rozo, Han Aung, Daisuke Nagai.
2020,
arXiv e-prints,
arXiv: 2010.11324
Or export the citation in many forms here.