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Galaxy Voids

Galaxy Voids. by Chooi Fei Ng and Aron Cooper. This false-color optical map, covering about 4300 square degrees, or 10 percent of the sky, shows the distribution in space of some 2 million galaxies. Void. Voids are the dominant feature and have a typical diameter of ~ 30Mpc.

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Galaxy Voids

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  1. Galaxy Voids by Chooi Fei Ng and Aron Cooper

  2. This false-color optical map, covering about 4300 square degrees, or 10 percent of the sky, shows the distribution in space of some 2 million galaxies.

  3. Void • Voids are the dominant feature and have a typical diameter of ~ 30Mpc. • Voids are very underdense region, δρ/ρ~0.95 • Up to 40% of volume of the universe is occupied by voids • The largest void observed, Bootes void, has a diameter of about 124Mpc.

  4. The Universe within 1 billion Light Years

  5. What is in a void? • A few unusually faint galaxy, void galaxies • Mostly Dark Matter – CDM model Void Boundaries • Rather smooth, defined by galaxies with a broad range of luminosity, especially star forming galaxies

  6. Observation- Redshift surveys • PSCz Redshift Survey • Catalogue of detections with the Infra-Red Astronomical Satellite (IRAS) • 15411 galaxies with redshift • Covers 84% of the sky • UZC(Updated Zwicky Catalog) • Center for Astrophysics (CfA) Optical Redshift survey • 18633 galaxies with redshift

  7. UZC

  8. PSCz Redshift Survey

  9. Void Finding Algorithm • Wall and field galaxies • Categorize each galaxy in the sample as a wall galaxy or a field (void) galaxy • Specify a length ln such that any galaxy that does not have n neighbors within a sphere of radius ln is classified as field galaxy. N = 3 for our choice • Place the wall galaxies onto a three dimensional grid • Beginning from the center of each empty grid cell, grow the largest possible sphere containing no wall galaxies and keep track of the radius of each hole • The largest hole found is automatically a void • Then, we test the second hole and if it overlaps the previous void by F% in volume, then it is a member of the first void rather than a new void. If not, it forms a separate void. • We continue like this for all holes with radii larger than 10h-1 Mpc

  10. Result from Voids Finding Algorithm • Shows the number of voids we find for the PSCz(dashed line) and the UZC(solid line) as a function of the overlap fraction for which the hole is still considered a separate void

  11. Recovering volume of voids • If the voids are highly elliptical, we will not detect them at the corners of the ellipse • Test this by generating data containing mock voids of known elliptical shape • Run the simulated data through our void finding algorithm and compare the volume obtained with the known volume of the void

  12. If voids are spherical in shape we recover 100% of the volume. • The more elongated it becomes, the less of the volume we detect

  13. PSCz UZC • Show the super galactic coordinates (x,y) for different values of z. • Each panel shows a 10h-1Mpc slice • Shaded regions are the voids. • The points are the wall galaxies and the empty squares show the void centers

  14. Results from Surveys

  15. Conclusion • Different samples from the same survey yield the same voids • We detect the same voids in different redshift surveys

  16. Study of Voids Using N-Body Simulations Chooi Fei Ng and Aron Cooper

  17. Outline • Motivation for using simulations • Basic information about simulations used • Void characteristics as determined using a variety of analysis tools • Void Probability Function (VPF) • Nearest Neighbor Distances • Void Finder Algorithm (VF) • Characteristics of Void galaxy populations

  18. Motivation • Why use simulations to study voids? • Compare simulation results with observations • Verify/Constrain cosmological models • Structure formation • Cosmological parameters • Initial conditions • Give some indication of Galaxy formation process • Special void population of galaxies • Better understand galaxy bias • If no bias, galaxy mass distribution is equal to that of DM

  19. N-Body Simulations Used • Three used: GIF, GIF-II, and 5123 • GIF and GIF-II only vary with initial conditions • Use Dark Matter Particles only • Cosmological Parameters Used: • “Special” methods applied to predict galaxy distribution and properties (details omitted)

  20. Void Probability Function (VPF) • VPF: Probability that a random sphere of radius R will have no points/matter within it • Statistic is calculated for: DM, Galaxies, and random distribution of points with # density = n_gal • Results: • DM and galaxies have more larger voids due clustering than the random distribution of points • VPF for large R is much higher for galaxies, than for DM, i.e. more large voids in galaxies due to bias • Selection effects: small DM halos in voids may form galaxies, but they are not bright enough to meet brightness criteria

  21. Comparison to Observation for VPF • For R <~ 8 h^-1MPc: • Galaxy samples match observations • DM produce low VPFs with regards to observations • For R > 8 h^-1MPc: • DM VPF agrees with the observations • Galaxy samples over-predict observed VPF • However, both DM and galaxy VPFs are within the uncertainties of the observed data.

  22. Nearest Neighbor Distribution • Define: • Bright “ordinary” galaxies defined as those brighter than magnitude Mord • Faint “test” galaxies defined as those in a particular, fainter, magnitude range Mtest • Dt0 the distance from a test galaxy to the nearest ordinary galaxy • D00 the distance from an ordinary galaxy to the nearest ordinary galaxy

  23. Results from Nearest Neighbor • D00 distribution shifts to larger average distances for brighter ordinary samples • These type of “ordinary” galaxies are generally found near the centers of massive DM halos (large clusters) • Rarely another galaxy of comparable magnitude found in cluster • Dt0 is generally smaller than D00 in this case. • Dt0 distribution shifts to larger average distances for faintest ordinary samples • Fainter test samples fill in voids defined by ordinary galaxies • Typical Dt0 being ~50% larger than typical D00

  24. Graphical Results from Nearest Neighbor

  25. Variation in Void Sizes from Void Finder 512 survey incomplete • Rapid decline in # density of voids for larger R, as predicted by VPF • Still more larger voids in galaxies than there are in DM • Fractional overdensity in voids 0.1 or less. Prediction by Sheth (2002)

  26. Examination of Void Population using VF • Examine the prevalence of “void” galaxies and structure surrounding VF candidates. • Determine Void Density Profiles: • First, determine number density of galaxies in concentric shells centered on center of void. • Scale all lengths using the void radius so voids of all sizes can be compared. • These number densities are summed for all voids of a particular range of radii

  27. Void Density Contrast Profiles from VF Open circles denote DM • Voids are highly underdense, more so for galaxies than for DM • Outside Threshold, density contrast becomes larger for galaxies than it is for DM. • Clear threshold corresponding to edge of void at about r/Rvoid = 1 • Indicates VF works • Density contrast in voids: • Little variation • Population dependent

  28. Void Galaxies vs. Field Galaxies (VF) • Halo mass function • Much lower for Void galaxies in relation to that of the Field galaxies • Median occupied halo mass • 6 times lower for void galaxies

  29. Specific Star Formation Rate (VF) Open indicates only galaxies at halo centers • Star Formation Rate • Higher towards centers of voids • Outside voids there exist very massive halos w/numerous satellite galaxies • In model used these galaxies have lost their fresh gas • In model specific star formation rate is higher in lower mass (dimmer) stars • See filled squares v. open squares Squares

  30. Void Galaxy Properties • Void galaxies found to have systematically different properties • Fainter • More blue • Tend to be disk-dominated • Higher star formation rates • Reasons for property variation: • Lower DM halo mass function than field galaxies • More clustering of galaxies outside of voids • Less gas available to galaxies that have existed in clusters for a long period of time

  31. Conclusions • A wealth of information about voids can be obtained using simulations • Better data for larger sky surveys needs to be analyzed for an accurate comparison to observations, i.e. SDSS, 2dFGRS • Galaxies in voids tend to have share similar characteristics • It is still unclear if these galaxies constitute their own population

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