The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: measuring structure growth using passive galaxies
Rita Tojeiro, Will J. Percival, Jon Brinkmann, Joel R. Brownstein,, Danniel J. Eisenstein, Marc Manera, Claudia Maraston, Cameron K. McBride,, Demitri Duna, Beth Reid, Ashley J. Ross, Nicholas P. Ross, Lado Samushia,, Nikhil Padmanabhan, Donald P. Schneider, Ramin Skibba

TL;DR
This study demonstrates that passive galaxy populations can effectively measure the evolution of structure growth, reducing uncertainties and confirming consistency with standard cosmological models.
Contribution
The paper introduces a method using passively evolving galaxies to improve measurements of structure growth and bias evolution, enhancing precision over previous techniques.
Findings
Bias modeling reduces uncertainty in growth rate measurements by up to 50%.
Results align with Lambda Cold Dark Matter and General Relativity.
Improved constraints on sigma_8(z=0) using passive galaxies.
Abstract
We explore the benefits of using a passively evolving population of galaxies to measure the evolution of the rate of structure growth between z=0.25 and z=0.65 by combining data from the SDSS-I/II and SDSS-III surveys. The large-scale linear bias of a population of dynamically passive galaxies, which we select from both surveys, is easily modeled. Knowing the bias evolution breaks degeneracies inherent to other methodologies, and decreases the uncertainty in measurements of the rate of structure growth and the normalization of the galaxy power-spectrum by up to a factor of two. If we translate our measurements into a constraint on sigma_8(z=0) assuming a concordance cosmological model and General Relativity (GR), we find that using a bias model improves our uncertainty by a factor of nearly 1.5. Our results are consistent with a flat Lambda Cold Dark Matter model and with GR.
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.
