On the primordial information available to galaxy redshift surveys
Matthew McQuinn

TL;DR
This paper explores the limits of primordial information recovery from galaxy surveys, showing that existing algorithms extract nearly all accessible data and identifying factors that determine reconstruction noise and accuracy.
Contribution
It introduces a simplified model and linearized limit to analyze the effectiveness of reconstruction algorithms and explains the transition point where correlation drops sharply.
Findings
Reconstruction algorithms match the linear input field cross correlation coefficients.
The transition to no correlation is determined by the number of galaxies, not shot noise.
Linear scales allow mode reconstruction below shot noise levels with sufficient displacement constraints.
Abstract
We investigate the amount of primordial information that can be reconstructed from spectroscopic galaxy surveys, as well as what sets the noise in reconstruction at low wavenumbers, by studying a simplified universe in which galaxies are the Zeldovich displaced Lagrangian peaks in the linear density field. For some of this study, we further take an intuitive linearized limit in which reconstruction is a convex problem but where the solution is also a solution to the full nonlinear problem, a limit that bounds the effectiveness of reconstruction. The linearized reconstruction results in similar cross correlation coefficients with the linear input field as our full nonlinear algorithm. The linearized reconstruction also produces similar cross correlation coefficients to those of reconstruction attempts on cosmological N-body simulations, which suggests that existing reconstruction…
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.
