PhD defense by Caroline Heneka

Thesis title: 
Cosmological Structure Formation: From Dawn till Dusk – From Reionization to Galaxy Clusters

David Rapetti, U. of Colorado, Boulder and NASA Ames Research Center
Steen H. Hansen, DARK

PhD Assessment Committee
Committee Chair: Claudio Grillo, University of Milan and DARK
Opponent: Steen Hannestad, Aarhus University
Opponent: Annalisa Pillepich, Max Planck Institute for Astronomy, Heidelberg

Cosmology has entered an era where a plethora data is available on structure formation to constrain astrophysics and underlying cosmology. This thesis strives to both investigate new observables and modeling of the Epoch of Reionization, as well as to constrain dark energy phenomenology with massive galaxy clusters, traveling from the dawn of structure formation, when the first galaxies appear, to its dusk, when a representative part of the mass in the Universe is settled in massive structures. This hunt for accurate constraints on cosmology is complemented with the demonstration of novel Bayesian statistical tools and kinematical constraints on dark energy.

Starting at the dawn of structure formation, we study emission line fluctuations, employing semi-numerical simulations of cosmological volumes of their line emission, in order to cross-correlate fluctuations in brightness. This cross-correlation signal encodes information about the state of the inter-galactic medium, testing neutral versus ionized medium. It thus constrains reionization, crucially depending on the first ionizing sources, as well as the growth of structure and therefore cosmology. The detectability of cross-correlation signals is demonstrated, opening an avenue for a wealth of future observables.

At dusk we employ the abundance of galaxy clusters to constrain both a standard dark energy scenario and dark energy of negligible sound speed. The latter implies significant perturbations and therefore clustering of the dark energy fluid, which we strive to measure. The stage for using non-linear cosmological model information in cluster growth analyses is set, by re-calibrating the halo mass function. Both models are constrained with cluster growth data and jointly with other cosmological probes, to find a shift between them, as well as differing constraints for Fisher matrix forecasts. Therefore, the growth of structure and cosmological parameters are shown to be sensitive to the presence of dark energy perturbations.

Lastly, a novel Bayesian approach is presented, this enables us to enhance the accuracy of our measurements by identifying biased subsets of data and hidden correlation in a model independent way.

Link to thesis ––>> here