A Bayesian analysis of the spatial dark matter distribution in our Universe
Title: A Bayesian analysis of the spatial dark matter distribution in our Universe
SNIC Project: SNIC 2019/35-36
Project Type: SNIC Medium Storage
Principal Investigator: Jens Jasche <jens.jasche@fysik.su.se>
Affiliation: Stockholms universitet
Duration: 2019-12-02 – 2020-06-01
Classification: 10305
Homepage: https://aquila-consortium.org/
Keywords:

Abstract

The recently established standard model of cosmology provides a successful phenomenological description of observations but falls short in providing physical insights into the origin of cosmic structure, the accelerating cosmic expansion and dark matter. Cosmology now turns to search for observational fingerprints robustly predicted by physical models of these phenomena in the spatial distribution of cosmic matter as traced by galaxies in cosmological surveys. According to current belief, all observable structures originate from tiny primordial quantum fluctuations generated during the early epoch of inflation in a hot big bang scenario at the beginning of the universe. These seed fluctuations grew via gravitational amplification to form a giant cosmic web of dark matter aggregating in massive clusters and filamentary cosmic structures. The detailed spatial configuration and dynamics of the cosmic matter distribution retain memory on the initial conditions and the physical processes that shaped it over 13.8 billion years of cosmic history. Detailed reconstruction of the spatial matter distribution and its dynamics from galaxy surveys provide us with important information to test fundamental physics and study the evolution of the Universe. The proposed project aims at applying a novel data analysis technique, developed by our group, to construct the largest and most detailed map of the spatial matter distribution from galaxies in the SDSS-III's Baryon Oscillation Spectroscopic Survey (BOSS). For the first time, we will be able to reconstruct the initial conditions from which present structures evolved and follow their gravitational formation throughout cosmic history. This is achieved by using our algorithm for Bayesian Origin Reconstruction from Galaxies (BORG), to fit cosmological gravitational N-body simulations in their full generality to the observed galaxy distribution. As a scientific result, we obtain a plausible computer model that resembles the actual universe not only in a statistical sense but on an object by object basis. Our BORG algorithm equips us with the unique capability to study the spatial distribution of cosmological objects and their dynamic properties in data. Now our project enters a new phase. We have recently demonstrated that our approach can yield significantly improved constraints on cosmological parameters. Building upon these results we aim at analyzing the cosmic matter distribution in the BOSS survey, the currently largest spectroscopic galaxy survey, over an unprecedented cosmological volume of (4 Gpc)^3. Obtained results will be used to constrain cosmological parameters, specifically the equation of state of dark energy, which is held responsible for the currently observed accelerating expansion of the Universe. We also aim at cross-analyzing our reconstructed dark matter maps with observations of the cosmic microwave background (CMB). The project is especially timely with respect to coming cosmological surveys. Besides producing significant scientific results, the proposed project also acts as a necessary test for next-generation galaxy surveys, e.g. LSST or Euclid. We will further provide the community with accurate and detailed reconstructions of the cosmic matter distribution and velocity fields, facilitating many secondary research projects with collaborators and multiplying the scientific outcome of the proposed research.