Disentangling redshift-space distortions and nonlinear bias using the 2D power spectrum
Elise Jennings, Risa H. Wechsler, Samuel W. Skillman, Michael S., Warren

TL;DR
This paper introduces a method to analyze the 2D galaxy power spectrum in redshift space, effectively disentangling nonlinear bias and redshift space distortions to improve cosmological parameter constraints.
Contribution
It demonstrates that individual $$ bins of the power spectrum contain richer information than multipole moments, enabling better separation of nonlinear effects and bias.
Findings
Achieved ~5% accuracy in nonlinear bias measurement at $k<0.6 h$Mpc$^{-1}$.
Constrained the growth rate $f$ to ~22-26% accuracy from clustering data.
Identified physical effects and turnaround scales related to galaxy population models.
Abstract
We present the nonlinear 2D galaxy power spectrum, , in redshift space, measured from the Dark Sky simulations, using galaxy catalogs constructed with both halo occupation distribution and subhalo abundance matching methods, chosen to represent an intermediate redshift sample of luminous red galaxies. We find that the information content in individual (cosine of the angle to the line of sight) bins is substantially richer then multipole moments, and show that this can be used to isolate the impact of nonlinear growth and redshift space distortion (RSD) effects. Using the simulation data, which we show is not impacted by RSD effects, we can successfully measure the nonlinear bias to an accuracy of % at Mpc. This use of individual bins to extract the nonlinear bias successfully removes a large parameter degeneracy when constraining…
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