Modeling iterative reconstruction and displacement field in the large scale structure

TL;DR

This paper evaluates the effectiveness of iterative reconstruction in recovering the nonlinear displacement field in large-scale structure, comparing theoretical predictions with N-body simulations and proposing models to improve accuracy.

Contribution

It introduces a third-order Lagrangian perturbation theory model for iterative reconstruction and analyzes its discrepancies with simulations.

Findings

Simulated iterative reconstruction does not fully converge to the nonlinear displacement field.

The 3LPT model predicts convergence to the nonlinear displacement field.

Discrepancies are mainly due to numerical noise and artifacts on small scales.

Abstract

The next generation of galaxy surveys like the Dark Energy Spectroscopic Instrument (DESI) and Euclid will provide datasets orders of magnitude larger than anything available to date. Our ability to model nonlinear effects in late time matter perturbations will be a key to unlock the full potential of these datasets, and the area of initial condition reconstruction is attracting growing attention. Iterative reconstruction developed in Ref. [1] is a technique designed to reconstruct the displacement field from the observed galaxy distribution. The nonlinear displacement field and initial linear density field are highly correlated. Therefore, reconstructing the nonlinear displacement field enables us to extract the primordial cosmological information better than from the late time density field at the level of the two-point statistics. This paper will test to what extent the iterative reconstruction can recover the true displacement field and construct a perturbation theory model for the postreconstructed field. We model the iterative reconstruction process with Lagrangian perturbation theory~(LPT) up to third order for dark matter in real space and compare it with $N$-body simulations. We find that the simulated iterative reconstruction does not converge to the nonlinear displacement field, and the discrepancy mainly appears in the shift term, i.e., the term correlated directly with the linear density field. On the contrary, our 3LPT model predicts that the iterative reconstruction should converge to the nonlinear displacement field. We discuss the sources of discrepancy, including numerical noise/artifacts on small scales, and present an ad hoc phenomenological model that improves the agreement.