# Dark matter voids in the SDSS galaxy survey

## Abstract

What do we know about voids in the dark matter distribution given the Sloan Digital Sky Survey (SDSS) and assuming the ΛCDM model? Recent application of the Bayesian inference algorithm BORG to the SDSS Data Release 7 main galaxy sample has generated detailed Eulerian and Lagrangian representations of the large-scale structure as well as the possibility to accurately quantify corresponding uncertainties. Building upon these results, we present constrained catalogs of voids in the Sloan volume, aiming at a physical representation of dark matter underdensities and at the alleviation of the problems due to sparsity and biasing on galaxy void catalogs. To do so, we generate data-constrained reconstructions of the presently observed large-scale structure using a fully non-linear gravitational model. We then find and analyze void candidates using the VIDE toolkit. Our methodology therefore predicts the properties of voids based on fusing prior information from simulations and data constraints. For usual void statistics (number function, ellipticity distribution and radial density profile), all the results obtained are in agreement with dark matter simulations. Our dark matter void candidates probe a deeper void hierarchy than voids directly based on the observed galaxies alone. The use of our catalogs therefore opens the way tomore »

- Authors:

- Institut d'Astrophysique de Paris (IAP), UMR 7095, CNRS - UPMC Université Paris 6, 98bis boulevard Arago, F-75014 Paris (France)

- Publication Date:

- OSTI Identifier:
- 22525925

- Resource Type:
- Journal Article

- Resource Relation:
- Journal Name: Journal of Cosmology and Astroparticle Physics; Journal Volume: 2015; Journal Issue: 03; Other Information: Country of input: International Atomic Energy Agency (IAEA)

- Country of Publication:
- United States

- Language:
- English

- Subject:
- 79 ASTROPHYSICS, COSMOLOGY AND ASTRONOMY; ACCURACY; ALGORITHMS; CATALOGS; COSMOLOGICAL CONSTANT; COSMOLOGICAL MODELS; COSMOLOGY; DENSITY; GALAXIES; LAGRANGIAN FUNCTION; LIMITING VALUES; NONLUMINOUS MATTER; PROBES; STATISTICS; VOIDS

### Citation Formats

```
Leclercq, Florent, Jasche, Jens, Sutter, P.M., Hamaus, Nico, and Wandelt, Benjamin, E-mail: florent.leclercq@polytechnique.org, E-mail: jasche@iap.fr, E-mail: sutter@iap.fr, E-mail: hamaus@iap.fr, E-mail: wandelt@iap.fr.
```*Dark matter voids in the SDSS galaxy survey*. United States: N. p., 2015.
Web. doi:10.1088/1475-7516/2015/03/047.

```
Leclercq, Florent, Jasche, Jens, Sutter, P.M., Hamaus, Nico, & Wandelt, Benjamin, E-mail: florent.leclercq@polytechnique.org, E-mail: jasche@iap.fr, E-mail: sutter@iap.fr, E-mail: hamaus@iap.fr, E-mail: wandelt@iap.fr.
```*Dark matter voids in the SDSS galaxy survey*. United States. doi:10.1088/1475-7516/2015/03/047.

```
Leclercq, Florent, Jasche, Jens, Sutter, P.M., Hamaus, Nico, and Wandelt, Benjamin, E-mail: florent.leclercq@polytechnique.org, E-mail: jasche@iap.fr, E-mail: sutter@iap.fr, E-mail: hamaus@iap.fr, E-mail: wandelt@iap.fr. Sun .
"Dark matter voids in the SDSS galaxy survey". United States.
doi:10.1088/1475-7516/2015/03/047.
```

```
@article{osti_22525925,
```

title = {Dark matter voids in the SDSS galaxy survey},

author = {Leclercq, Florent and Jasche, Jens and Sutter, P.M. and Hamaus, Nico and Wandelt, Benjamin, E-mail: florent.leclercq@polytechnique.org, E-mail: jasche@iap.fr, E-mail: sutter@iap.fr, E-mail: hamaus@iap.fr, E-mail: wandelt@iap.fr},

abstractNote = {What do we know about voids in the dark matter distribution given the Sloan Digital Sky Survey (SDSS) and assuming the ΛCDM model? Recent application of the Bayesian inference algorithm BORG to the SDSS Data Release 7 main galaxy sample has generated detailed Eulerian and Lagrangian representations of the large-scale structure as well as the possibility to accurately quantify corresponding uncertainties. Building upon these results, we present constrained catalogs of voids in the Sloan volume, aiming at a physical representation of dark matter underdensities and at the alleviation of the problems due to sparsity and biasing on galaxy void catalogs. To do so, we generate data-constrained reconstructions of the presently observed large-scale structure using a fully non-linear gravitational model. We then find and analyze void candidates using the VIDE toolkit. Our methodology therefore predicts the properties of voids based on fusing prior information from simulations and data constraints. For usual void statistics (number function, ellipticity distribution and radial density profile), all the results obtained are in agreement with dark matter simulations. Our dark matter void candidates probe a deeper void hierarchy than voids directly based on the observed galaxies alone. The use of our catalogs therefore opens the way to high-precision void cosmology at the level of the dark matter field. We will make the void catalogs used in this work available at http://www.cosmicvoids.net.},

doi = {10.1088/1475-7516/2015/03/047},

journal = {Journal of Cosmology and Astroparticle Physics},

number = 03,

volume = 2015,

place = {United States},

year = {Sun Mar 01 00:00:00 EST 2015},

month = {Sun Mar 01 00:00:00 EST 2015}

}