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Modeling cosmic void statistics

Published online by Cambridge University Press:  12 October 2016

Nico Hamaus
Affiliation:
Sorbonne Universités, UPMC Univ Paris 06, Paris, France CNRS, UMR 7095, Institut d'Astrophysique de Paris, Paris, France
P. M. Sutter
Affiliation:
Sorbonne Universités, UPMC Univ Paris 06, Paris, France CNRS, UMR 7095, Institut d'Astrophysique de Paris, Paris, France Center for Cosmology and AstroParticle Physics, Ohio State University, Columbus, USA
Benjamin D. Wandelt
Affiliation:
Sorbonne Universités, UPMC Univ Paris 06, Paris, France CNRS, UMR 7095, Institut d'Astrophysique de Paris, Paris, France Departments of Physics and Astronomy, University of Illinois at Urbana-Champaign, USA
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Abstract

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Understanding the internal structure and spatial distribution of cosmic voids is crucial when considering them as probes of cosmology. We present recent advances in modeling void density- and velocity-profiles in real space, as well as void two-point statistics in redshift space, by examining voids identified via the watershed transform in state-of-the-art ΛCDM n-body simulations and mock galaxy catalogs. The simple and universal characteristics that emerge from these statistics indicate the self-similarity of large-scale structure and suggest cosmic voids to be among the most pristine objects to consider for future studies on the nature of dark energy, dark matter and modified gravity.

Type
Contributed Papers
Copyright
Copyright © International Astronomical Union 2016 

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