The onion universe: all sky lightcone simulations in spherical shells

TL;DR

This paper introduces a new large-scale N-body simulation and a novel onion-like lightcone map representation of the universe, enabling efficient analysis of large-scale structure and dark energy constraints.

Contribution

The authors develop a high-resolution simulation and create compressed lightcone maps that facilitate large-scale structure analysis and dark energy studies, addressing radial resolution limitations.

Findings

The onion maps are over 1000 times smaller than raw data at arcminute resolution.

Sampling variance on degree scales can cause a 25% bias in variance measurements.

Projection effects can induce significant bias in weak lensing mass reconstruction.

Abstract

Galaxy surveys provide a large-scale view of the universe that typically has a limited line-of-sight or redshift resolution. The lack of radial accuracy in these surveys can be modelled by picturing the universe as a set of concentric radial shells of finite width around the observer, i.e, an onion-like structure. We present a new N-body simulation with 2048^3 particles developed at the Marenostrum supercomputer with the GADGET-2 code. Using the lightcone output we build a set of angular maps that mimic this onion-like representation of the universe. The onion maps are a highly compressed version of the raw data (i.e. a factor >1000 smaller size for arcminute resolution maps) and they provide a new and powerful tool to exploit large scale structure observations. We introduce two basic applications of these maps that are especially useful for constraning dark energy properties: the baryon acoustic oscillations (BAO) in the galaxy power spectrum and all-sky maps of the weak lensing distortion. Using the weak lensing maps, we measure the convergence power spectra and compare it to halo fit predictions. As a further application, we compute the variance and higher-order moments of the maps. We show that sampling variance on scales of few degrees is quite large, resulting in a significant (25% at 10 arminute scales) bias in the variance. We caution that current lensing surveys such as the COSMOS HST should take into account this bias and extra sampling error in their clustering analyses and inferred cosmological parameter constraints. Finally, we test the importance of projection effects in the weak lensing mass reconstruction. On the mean, the mass calibration works well but it exhibits a large non-Gaussian scatter what could induce a large bias in the recovered mass function.