Cluster Cosmology Without Cluster Finding
Enia Xhakaj, Alexie Leauthaud, Johannes Lange, Elisabeth Krause,, Andrew Hearin, Song Huang, Risa H. Wechsler, Sven Heydenreich

TL;DR
This paper suggests that super-massive galaxies can be used as an alternative to cluster counts for cosmological constraints, offering similar or better precision with potentially fewer systematic errors.
Contribution
It introduces the idea of using galaxy observations, especially stellar mass-limited samples, as a new method for cosmology, potentially probing lower halo masses and reducing systematics.
Findings
Massive galaxies provide constraints comparable to clusters at fixed number density.
Galaxy samples can probe lower halo masses than traditional optical clusters.
Stellar mass-limited samples can significantly improve cosmological constraints.
Abstract
We propose that observations of super-massive galaxies contain cosmological constraining power similar to conventional cluster cosmology, and we provide promising indications that the associated systematic errors are comparably easier to control. We consider a fiducial spectroscopic and stellar mass complete sample of galaxies drawn from the Dark Energy Spectroscopic Survey (DESI) and forecast how constraints on Omega_m-sigma_8 from this sample will compare with those from number counts of clusters based on richness. At fixed number density, we find that massive galaxies offer similar constraints to galaxy clusters. However, a mass-complete galaxy sample from DESI has the potential to probe lower halo masses than standard optical cluster samples (which are typically limited to richness above 20 and halo mass above 10^13.5); additionally, it is straightforward to cleanly measure…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGalaxies: Formation, Evolution, Phenomena · Astronomy and Astrophysical Research · Spatial and Panel Data Analysis
