Density-dependent clustering: I. Pulling back the curtains on motions of the BAO peak

TL;DR

This paper introduces a density-slicing method for the correlation function to analyze large-scale structure, revealing how local density influences BAO peak shifts and motions, which can improve constraints on cosmological models.

Contribution

It presents a novel slicing technique of the correlation function based on local density, providing new insights into BAO peak shifts and large-scale flows beyond traditional reconstruction methods.

Findings

BAO peak location varies with local density.

Slicing on 40 Mpc/h density best reveals BAO shifts.

Curtain plots illustrate particle motions driven by local density.

Abstract

The most common statistic used to analyze large-scale structure surveys is the correlation function, or power spectrum. Here, we show how `slicing' the correlation function on local density brings sensitivity to interesting non-Gaussian features in the large-scale structure, such as the expansion or contraction of baryon acoustic oscillations (BAO) according to the local density. The sliced correlation function measures the large-scale flows that smear out the BAO, instead of just correcting them as reconstruction algorithms do. Thus, we expect the sliced correlation function to be useful in constraining the growth factor, and modified gravity theories that involve the local density. Out of the studied cases, we find that the run of the BAO peak location with density is best revealed when slicing on a $\sim 40$ Mpc/$h$ filtered density. But slicing on a $\sim100$ Mpc/$h$ filtered density may be most useful in distinguishing between underdense and overdense regions, whose BAO peaks are separated by a substantial $\sim 5$ Mpc/$h$ at $z=0$. We also introduce `curtain plots' showing how local densities drive particle motions toward or away from each other over the course of an $N$-body simulation.