# Cross Match Catalogs with HEALPix Sky Maps (ligo.skymap.postprocess.crossmatch)¶

Catalog cross matching for HEALPix sky maps.

class ligo.skymap.postprocess.crossmatch.CrossmatchResult(searched_area, searched_prob, offset, searched_modes, contour_areas, area_probs, contour_modes, searched_prob_dist, contour_dists, searched_vol, searched_prob_vol, contour_vols, probdensity, probdensity_vol)

Bases: tuple

Cross match result as returned by crossmatch().

Notes

• All probabilities returned are between 0 and 1.

• All angles returned are in degrees.

• All areas returned are in square degrees.

• All distances are luminosity distances in units of Mpc.

• All volumes are in units of Mpc³. If crossmatch() was run with cosmology=False, then all volumes are Euclidean volumes in luminosity distance. If crossmatch() was run with cosmology=True, then all volumes are comoving volumes.

property area_probs

Probability within the 2D credible regions of the areas specified by the areas argument passed to crossmatch().

property contour_areas

Area within the 2D credible regions of the probabilities specified by the contour argument passed to crossmatch().

property contour_dists

Distance credible interval, marginalized over sky position, Same length as the coordinates argument passed to crossmatch().

property contour_modes

Number of disconnected regions within the 2D credible regions of the probabilities specified by the contour argument passed to crossmatch().

property contour_vols

Volume within the 3D credible regions of the probabilities specified by the contour argument passed to crossmatch().

property offset

Angles on the sky between the target positions and the maximum a posteriori position. Same length as the coordinates argument passed to crossmatch().

property probdensity

2D probability density per steradian at the positions of each of the targets. Same length as the coordinates argument passed to crossmatch().

property probdensity_vol

3D probability density per cubic megaparsec at the positions of each of the targets. Same length as the coordinates argument passed to crossmatch().

property searched_area

Area within the 2D credible region containing each target position. Same length as the coordinates argument passed to crossmatch().

property searched_modes

Number of disconnected regions within the 2D credible regions containing each target position. Same length as the coordinates argument passed to crossmatch().

property searched_prob

Probability within the 2D credible region containing each target position. Same length as the coordinates argument passed to crossmatch().

property searched_prob_dist

Cumulative CDF of distance, marginalized over sky position, at the distance of each of the targets. Same length as the coordinates argument passed to crossmatch().

property searched_prob_vol

Probability within the 3D credible region containing each target position. Same length as the coordinates argument passed to crossmatch().

property searched_vol

Volume within the 3D credible region containing each target position. Same length as the coordinates argument passed to crossmatch().

ligo.skymap.postprocess.crossmatch.crossmatch(sky_map, coordinates=None, contours=(), areas=(), modes=False, cosmology=False)[source] [edit on github]

Cross match a sky map with a catalog of points.

Given a sky map and the true right ascension and declination (in radians), find the smallest area in deg^2 that would have to be searched to find the source, the smallest posterior mass, and the angular offset in degrees from the true location to the maximum (mode) of the posterior. Optionally, also compute the areas of and numbers of modes within the smallest contours containing a given total probability.

Parameters
sky_mapastropy.table.Table

A multiresolution sky map, as returned by ligo.skymap.io.fits.read_sky_map() called with the keyword argument moc=True.

coordinatesastropy.coordinates.SkyCoord, optional

The catalog of target positions to match against.

contourstuple, optional

Credible levels between 0 and 1. If this argument is present, then calculate the areas and volumes of the 2D and 3D credible regions that contain these probabilities. For example, for contours=(0.5, 0.9), then areas and volumes of the 50% and 90% credible regions.

areastuple, optional

Credible areas in square degrees. If this argument is present, then calculate the probability contained in the 2D credible levels that have these areas. For example, for areas=(20, 100), then compute the probability within the smallest credible levels of 20 deg² and 100 deg², respectively.

modesbool, optional

If True, then enable calculation of the number of distinct modes or islands of probability. Note that this option may be computationally expensive.

cosmologybool, optional

If True, then search space by descending probability density per unit comoving volume. If False, then search space by descending probability per luminosity distance cubed.

Returns
resultCrossmatchResult

Notes

This function is also be used for injection finding; see Gather Summary Statistics (ligo-skymap-stats).

Examples

First, some imports:

>>> from astroquery.vizier import VizierClass
>>> from astropy.coordinates import SkyCoord
>>> from ligo.skymap.postprocess import crossmatch


Next, retrieve the GLADE catalog using Astroquery and get the coordinates of all its entries:

>>> vizier = VizierClass(
...     row_limit=-1, columns=['GWGC', '_RAJ2000', '_DEJ2000', 'Dist'])
>>> coordinates = SkyCoord(cat['_RAJ2000'], cat['_DEJ2000'], cat['Dist'])


Load the multiresolution sky map for S190814bv:

>>> url = 'https://gracedb.ligo.org/api/superevents/S190814bv/files/bayestar.multiorder.fits'


Perform the cross match:

>>> result = crossmatch(skymap, coordinates)


Using the cross match results, we can list the galaxies within the 90% credible volume:

>>> print(cat[result.searched_prob_vol < 0.9])
GWGC          _RAJ2000             _DEJ2000               Dist
deg                  deg                  Mpc
---------- -------------------- -------------------- --------------------
NGC0171   9.3396699999999999 -19.9342460000000017    57.56212553960000
---  20.2009090000000064 -31.1146050000000010   137.16022925600001
ESO540-003   8.9144679999999994 -20.1252980000000008    49.07809291930000
---  10.6762720000000009 -21.7740819999999999   276.46938505499998
---  13.5855169999999994 -23.5523850000000010   138.44550704800000
---  20.6362969999999990 -29.9825149999999958   160.23313164900000
---  13.1923879999999993 -22.9750179999999986   236.96795954500001
---  11.7813630000000007 -24.3706470000000017   244.25031189699999
---  19.1711120000000008 -31.4339490000000019   152.13614001400001
---  13.6367060000000002 -23.4948789999999974   141.25162979500001
...                  ...                  ...                  ...
---  11.3517000000000010 -25.8596999999999966   335.73800000000000
---  11.2073999999999998 -25.7149000000000001   309.02999999999997
---  11.1875000000000000 -25.7503999999999991   295.12099999999998
---  10.8608999999999991 -25.6904000000000003   291.07200000000000
---  10.6938999999999975 -25.6778300000000002   323.59399999999999
---  15.4935000000000009 -26.0304999999999964   304.78899999999999
---  15.2794000000000008 -27.0410999999999966   320.62700000000001
---  14.8323999999999980 -27.0459999999999994   320.62700000000001
---  14.5341000000000005 -26.0949000000000026   307.61000000000001
---  23.1280999999999963 -31.1109199999999966   320.62700000000001
Length = 1479 rows