Probabilistic cartography of the large-scale structure

TL;DR

This paper presents the application of the BORG algorithm to real galaxy data, producing probabilistic maps of the universe's large-scale structure with uncertainty quantification, and exploring cosmic web features and CMB effects.

Contribution

It demonstrates how BORG can infer and visualize the universe's structure from galaxy surveys, incorporating uncertainties and analyzing cosmic web components.

Findings

Probabilistic maps of large-scale structure generated from galaxy data.

Analysis of cosmic web elements and secondary CMB effects.

Uncertainty propagation in large-scale structure inference.

Abstract

The BORG algorithm is an inference engine that derives the initial conditions given a cosmological model and galaxy survey data, and produces physical reconstructions of the underlying large-scale structure by assimilating the data into the model. We present the application of BORG to real galaxy catalogs and describe the primordial and late-time large-scale structure in the considered volumes. We then show how these results can be used for building various probabilistic maps of the large-scale structure, with rigorous propagation of uncertainties. In particular, we study dynamic cosmic web elements and secondary effects in the cosmic microwave background.