# Presentation: 003379

## Why Study Nothing?Voids and  void galaxies in the Universe

- Fiona Hoyle
- Michael Vogeley
- Randall Rojas – PhD Thesis Work
- David Goldberg
- Drexel University

## Overview

- Finding Voids
- The Voidfinder Algorithm
- Results from the 2dFGRS
- Delaunay Tessellation
- Void Galaxies in the SDSS
- Photometric Properties
- Spectroscopic Properties
- Luminosity Functions
- Mass Functions
- Summary

## The Void Finder Algorithm

- Based on El-Ad and Piran algorithm – some differences
- Classification of galaxies as wall/void galaxies
- Detection of empty cells
- Growth of maximal spheres
- Classification of unique voids
- Enhancement of void volume
- Calculation of void underdensity

## Wall/Void Galaxies

-  Galaxies in very underdense
-    regions are void galaxies
-  If more than three galaxies
-    in sphere of
-    l = d + 1.5 pc
-  ~ 10% of galaxies classed as
-   void galaxies

## The Void Finder AlgorithmHoyle & Vogeley 2002

- Classification of galaxies as wall/void galaxies
- Detection of empty cells
- Growth of maximal spheres
- Classification of unique voids
- Enhancement of void volume
- Calculation of void underdensity

## Voids in the 2dFGRS

- Red – void centers
- Black – wall galaxies
- 289 voids in total (zcrit=0.1)
- Largest void radius =19.85 Mpc
- Average(r > 10) =12.4 +/- 1.9 Mpc
- Similar to PSCz and UZC results

## Void Distributions

- Little difference in size distributions between N and S and with depth
- - Possibly KAOS will detect evolution of voids and q0

## Void Profiles

- Where do the void galaxies lie?
- Centers of voids very empty
- Steep rise at radius of void
- Most of the void galaxies lie
- close to the edges of the voids.

## Void Probability Function

- Probability that a sphere
- radius r contains no galaxies
- VPF can be measured from
- volume-limited samples that
- cover wide range of z, M
- Follow a negative binomial
- distribution (Croton 04)

## VPF and Semi-Analytic Models

- Good agreement between
- semi-analytic models
- and the 2dFGRS VPF’s
- Poor agreement with dark
- matter only simulations –
- as expected
- Reasonable agreement with
- CfA – errors greatly reduced

## Results

- Applied to 2dFGRS (and PSCz and UZC)
- Voids are on average 12 Mpc in radius
- Assuming voids > 10 Mpc in radius
- They fill 30-40 % of the survey volume
- Algorithms including smoothing tend to find larger volumes
- The values of are -0.95
- Very empty at center
- VPF good match with semi-analytic models

## Future Methods: Delaunay Tessellation

- Cover 3D (2D) space with tetrahedra (triangles), with galaxies at vertices
- Delaunay Tessellation is the dual of Voronoi Tesselation (Delaunay vertices are centers of Voronoi cells)
- Similar to SURFGEN
- No free parameters – except density threshold
- Applications for density estimation, computation of topological and morphological statistics (Genus, Minkowski Functionals)

## The Delaunay Tessellation

- Galaxy Distribution

- Delaunay Tessellation

## Using the Delaunay Tessellation

- At each galaxy point the density is
- x = (Dim + 1) /  V
- By interpolating we find the density field at every value of x
- By setting a density threshold we can draw a contour which divides a region into above and below density parts – a void
- Galaxies with low density are void galaxies
- Can also be used in topological analyses

## 2D Density Estimation by Interpolation

## Void Galaxies

## Finding Void Galaxies in the SDSS

- Use volume limited samples to trace the distribution of the voids
- Use 3rd nearest neighbor criterion to find void galaxies
- Mean density contrast around void galaxies is consistent with VoidFinder results
- Use UZC+SSRS2 nearby surveys to help find void galaxies very nearby
- NB cannot yet find 3D voids in SDSS

## Finding Nearby Void Galaxies

- Black=SDSS galaxies
- Red=UZC galaxies
- Blue=SSRS2 galaxies
- Green=Nearby void galaxies

## Void Galaxies

- 194/4000 void galaxies locally
- 1048/12000 void galaxies in the distant sample
- First time sample >103 void galaxies
- Colours
- u-g and g-r
- Morphology
- Sersic index n, exp (-r1/n )
- Concentration index r50/r90
- Emission Lines
- OII, Hstar formation)

## Colours of Void vs. Wall Galaxies

-        M<-19.5                  M>-19.5

-        M<-17.0                  M>-17.0

-   Distant Sample

-  Nearby Sample

- Void galaxies (red lines) **bluer** than wall galaxies (dashed black lines)

## Profiles of Void vs. Wall Galaxies

-   Distant Sample

-  Nearby Sample

-        M<-19.5                  M>-19.5

-        M<-17.0                  M>-17.0

- Bright void galaxies (red lines) **more disklike** than wall galaxies (dashed black lines)

## Bimodal Distribution of Galaxies

- Separation into red early type (E/SO) and blue late type (Sp, Irr) galaxies at Sersic n~1.8
- Are differences between void and wall galaxies simply due to the morphology density relation? (fewer E’s in voids)
- Need to compare colour at fixed morphology

## Not Explained by the Morphology-Density Relation

-        Early type n>1.8

-        Late type n<1.8

- Void galaxies (red lines) **bluer** than wall galaxies (dashed black lines) **of the same ****luminosity AND type**

## Equivalent Widths

- Void galaxies have on
- average  larger EW(H)
- than wall galaxies.
- Same holds for OII, H,
- NII

## Stellar Masses

- Void galaxies have on
- average smaller stellar
- masses than wall galaxies.

- Kauffmann et al. 2003

## Specific Star Formation Rates

- Void galaxies have on
- average  larger S-SFR(H)
- than wall galaxies.

## Void Galaxy Luminosity Function

- Lower amplitude as
- only 1/12th of galaxies
- are void galaxies
- From -15<Mr<-21 due
- to distant and nearby
- samples

## Fitting Schecter Functions

- 

**Mr***

- Very similar values
- of  – faint end slope
- 1 magnitude difference
- in Mr* due to lack of
- big bright galaxies in
- voids

## LF as a Function of Colour

- Void galaxy LF more
- Similar to that of
- Wall galaxies that are
- Blue
- Low sersice indicies
- High equivalent widths

## Luminosity Function Summary

- Void galaxy LF measured over wide range of magnitudes -15<Mr<-21
- The void LF has fainter value of Mr* but similar value of  as the wall sample
- Value ofmuch shallower than predicted by CDM
- Similar shape the LF of blue, low sersic index, high EW(H) wall galaxies

## Mass Function in Voids

- Estimate the masses of the galaxies
- Ellipticals use Padmadaban et al 2003 method to estimate virial mass
- Spirals – invert the Tully Fisher relation
- Compare to Press-Schuster models for the mass in voids

## Mass Function

- Find that galaxies
- are approximately
- unbiased estimators
- of the mass in voids

## Conclusions

-  Presented two methods from which voids can be
-   found
-  Voids are very underdense d<-0.9 and fill 40%
-   of the Universe
-  Void galaxies are fainter, bluer and more diskier than
-    wall galaxies
-     - Not explained by just the morphology-density
-       relation
-  Void galaxies also have higher rates of specific
-    star formation
-  Luminosity function similar  for void/wall galaxies

## Advertisement

- Proposal in to Aspen Center for Physics for Void Workshop next summer
- Michael Vogeley, Rien van de Weygaert, Jim Peebles, Ravi Sheth and Fiona Hoyle
- Aim to bring Theoreticians and Observers together to address all these issues
- Watch your email!