Using V²

Quick start

A summary checklist for installing and running V².

• Clone the GitHub repository

• Run:

  python setup.py install
  

  See Installation for installation options.

• Navigate to VAST/example_scripts/ and modify DR7_config.ini if appropriate. Fields to edit might include:

  • Input catalog and Survey name

  • Output directory

  • redshift and/or magnitude limits

  • Minimum void radius

  • etc.

• Run vsquared.py from the VAST/example_scripts/ directory on your machine or using a cluster:

  python vsquared.py -c DR7_config.ini
  

  Note

  Include the -v option to produce the output required for VoidRender.

The output file [survey_name]_V2_[pruning_method]_Output.fits will be located in the directory specified by out_directory. See Output for a detailed description of this file.

Example configuration file

Included in the V² repository (VAST/example_scripts/) are a finite selection of example configuration files:

• DR7_config.ini contains the settings to run V² on the SDSS DR7 main galaxy sample. A volume-limited version of this galaxy catalog is provided with the package (VAST/example_scripts/vollim_dr7_cbp_102709.fits).

See Configuration File Options for details on the configuration file options.

Finding voids

Script

The easiest way to use V² is to use the vsquared.py script, located in VAST/example_scripts/. For usage information, run:

python vsquared.py --help

In a Python Shell

Finding voids can also be done in a Python shell, using the vast.vsquared.zobov.Zobov class and its methods:

1. Create a Zobov object using the desired configuration file and additional input parameters:

   newZobov = Zobov("DR7_config.ini")
   

   See Zobov.__init__ for details on the initialization method’s arguments.

2. Apply a void-pruning method to the voids found:

   newZobov.sortVoids()
   

   See Zobov.sortVoids for details on this method’s arguments.

3. Save the results to disk (these methods take no additional arguments):

   newZobov.saveVoids()
   newZobov.saveZones()
   newZobov.preViz() #if intending to visualize results
   

Configuration File Options

Using V² requires a configuration file with the following options:

Configuration file options

Key	Section	Data type	Unit	Comment
Input Catalog	Paths	string		Path to the input data catalog
Survey Name	Paths	string		Survey identifier to use in output file name
Output Directory	Paths	string		Path to the directory where output file will be saved
H_0	Cosmology	float	(km/s)/Mpc	Hubble constant of the desired cosmology
Omega_m	Cosmology	float		Dimensionless matter density parameter of the desired cosmology
redshift_min	Settings	float		The redshift above which void-finding will be applied
redshift_max	Settings	float		The redshift below which void-finding will be applied
rabsmag_min	Settings	float		The minimum magnitude for a galaxy to be used for void-finding
radius_min	Settings	float	Mpc/h	The minimum radius for a void candidate to be considered a true void
nside	Settings	integer		The NSIDE parameter used in the HEALPix pixelization of the survey mask; must be a power of 2
redshift_step	Settings	float		The step size used to create a comoving-distance-to-redshift lookup table

Input

As V² is designed to identify voids in a galaxy distribution, it requires a galaxy catalog (or similar) on which to run.

This input data file is specified by the Input Catalog field in the sample DR7_config.ini configuration file.

File format

Currently supported formats for the input data file include:

• ascii commented header (readable by astropy.table.Table.read)

• .fits or .fit

• .h5

Data columns

Required columns for input file

Column name	Data type	Unit	Comment
ra	float	degrees	Right ascension
dec	float	degrees	Declination
redshift	float		Redshift

Optional columns for input file

Column name	Data type	Unit	Comment
rabsmag	float		Absolute magnitude. Only used if rabsmag_min is not None.

Output

Each void found by V² is a set of Voronoi cells. Within the output file [survey_name]_V2_[pruning_method]_Output.fits, the FITS table HDUs that list the identified voids have the EXTNAMES:

• GALZONE – Identifies the zone to which each galaxy belongs.

• ZONEVOID – Identifies the void to which each zone belongs.

• VOIDS – Identifies the coordinates, effective radius, and ellipticity of

  each void.

Each of these files is described in more detail below.

Additional files that are produced during the process (which may or may not be useful to the user post-void-finding) include

• PRIMARY – Summary information about the void-finding and void catalog.

• TRIANGLE – Identifies the vertices, normal vector, and void membership

  of each triangle making up a void boundary

• GALVIZ – Identifies the voids to which each galaxy and its nearest

  neighbor belong

GALZONE output table HDU

Column name	Data type	Comment
gal	integer	Unique galaxy identifier
zone	integer	Unique identifier of the galaxy’s containing zone
depth	integer	Number of adjacent voronoi cells between the galaxy’s cell and the edge of its zone
edge	integer	1 if the galaxy’s voronoi cell extends outside the survey mask, 0 otherwise
out	integer	1 if the galaxy is located outside the survey mask, 0 otherwise

ZONEVOID output table HDU

Column name	Data type	Comment
zone	integer	Unique zone identifier
void0	integer	Unique identifier of the zone’s smallest containing void; -1 if zone is not part of a void
void1	integer	Unique identifier of the zone’s largest containing void; -1 if zone is not part of a void

VOIDS output table HDU

Column name	Data type	Unit	Comment
x	float	Mpc/h	x-coordinate of the weighted center of the void
y	float	Mpc/h	y-coordinate of the weighted center of the void
z	float	Mpc/h	z-coordinate of the weighted center of the void
redshift	float		redshift of the weighted center of the void
ra	float	degrees	right ascension of the weighted center of the void
dec	float	degrees	declination of the weighted center of the void
radius	float	Mpc/h	effective radius of the void
x1	float		normalized x-component of the void’s first ellipsoid axis
y1	float		normalized y-component of the void’s first ellipsoid axis
z1	float		normalized z-component of the void’s first ellipsoid axis
x2	float		normalized x-component of the void’s second ellipsoid axis
y2	float		normalized y-component of the void’s second ellipsoid axis
z2	float		normalized z-component of the void’s second ellipsoid axis
x3	float		normalized x-component of the void’s third ellipsoid axis
y3	float		normalized y-component of the void’s third ellipsoid axis
z3	float		normalized z-component of the void’s third ellipsoid axis

TRIANGLE output table HDU

Column name	Data type	Unit	Comment
void_id	integer		Unique identifier of the triangle’s containing void
n_x	float		normalized x-component of the triangle’s normal vector
n_y	float		normalized y-component of the triangle’s normal vector
n_z	float		normalized z-component of the triangle’s normal vector
p1_x	float	Mpc/h	x-coordinate of the triangle’s first vertex
p1_y	float	Mpc/h	y-coordinate of the triangle’s first vertex
p1_z	float	Mpc/h	z-coordinate of the triangle’s first vertex
p2_x	float	Mpc/h	x-coordinate of the triangle’s second vertex
p2_y	float	Mpc/h	y-coordinate of the triangle’s second vertex
p2_z	float	Mpc/h	z-coordinate of the triangle’s second vertex
p3_x	float	Mpc/h	x-coordinate of the triangle’s third vertex
p3_y	float	Mpc/h	y-coordinate of the triangle’s third vertex
p3_z	float	Mpc/h	z-coordinate of the triangle’s third vertex

GALVIZ output table HDU

Column name	Data type	Comment
gid	integer	Unique galaxy identifier
g2v	integer	Unique identifier of the galaxy’s containing void
g2v2	integer	Unique identifier of the containing void of the galaxy’s nearest neighbor

Using the output

Is my object in a void?

Because voids found by V² are formed from zones, which are unions of objects’ voronoi cells, each object’s void membership is easily determined from the output. The GALZONE output table (see Output) contains each object’s zone membership, and the ZONEVOID output table contains each zone’s void membership. If the values in the void0 and void1 columns of a zone are -1, the zone does not belong to any void, and any objects contained within that zone are not in a void.

See the jupyter notebook void_analysis.ipynb (found in the VAST/example_scripts/ directory) for an example of how to read information from the output and perform void analysis using the VoidCatalog class. This class offers a convenient method for automatically loading the FITS file output into a collection of Astropy tables. The class can be further used to perform void analysis, including the calculation of void volumes, median and maximum void radii, the total void volume fraction, and void galaxy membership. The notebook also shows how to create a void slice plot using the catalog.