The match criteria box allows you to specify what counts as a match
between two rows. The selection you make in this box will determine
which columns you have to fill in for the table(s) being matched
in the rest of the window. In most cases what you are selecting here
is the coordinate space in which rows will be compared against each other,
and a numerical value or values to determine how close two rows have to be
in terms of a metric on that space to count as a match.
The following match types are offered:
-
Sky
- Comparison of positions on the celestial sphere.
In this case you will need to specify columns giving
Right Ascension and Declination
for each table participating in the match.
The Error value you must fill in is the maximum separation of matched
points in around a great circle.
-
Spherical Polar
- Comparison of positions in the sky taking account of radial distance.
In this case you will need to specify columns giving
Right Ascension and Declination in angular units,
and radial distance in arbitrary units
for each table participating in the match.
The Error value is a maximum spatial separation of matched points
in the same units as the radial distance.
-
Exact Value
- Requires exact matching of values.
In this case you will need to specify the column containing the match key
for each table participating in the match;
this might typically be an object name or index number.
Two rows count as matching if they have exactly the same entry in
the specified field, except rows with a null value in that column,
which don't match any other row.
-
N-dimensional Cartesian
- Comparison of positions in an isotropic N-dimensional Cartesian space.
In this case you will need to specify N columns giving
coordinates for each table participating in the match.
The Error value is the maximum spatial separation of matched points.
Currently the highest dimensionality you can select is 3-d -
does anyone want a higher number?
-
N-dimensional Cartesian (anisotropic)
- Comparison of positions in an N-dimensional Cartesian space
with an anisotropic metric.
In this case you will need to specify N columns giving coordinates
for each table participating in the match,
and an error radius for each of these dimensions.
Points P1 and P2 are considered to match if P2 falls within
the ellipsoid defined by the error radii centered on P1.
This kind of match will typically be used for non-'spatial' spaces,
for instance (magnitude,redshift) space, in which the metrics in
different dimensions are not related to each other.
Currently the highest dimensionality you can select is 4-d -
does anyone want a higher number?
-
Sky + X
- Comparison of positions on the celestial sphere with an additional
numeric constraint.
This is a combination of the Sky and
1-d Cartesian matches above, so the columns you need
to supply are RA, Dec and one extra, and the errors are
angular separation on the sky and the error in the extra column.
A match is registered if it matches in both of the constituent tests.
You could use this for instance to match objects which are both close
on the sky and have similar luminosities.
-
Sky + XY
- Comparison of positions on the celestial sphere with an additional
2-d anisotropic Cartesian constraint.
This is a combination of the Sky and 2-d Anisotropic Cartesian
matches above, so the columns you need to supply are
RA, Dec and two extra, and the errors are
angular separation on the sky and the error radii corresponding to
the extra columns.
A match is registered if it matches in both of the constituent tests.
You could use this for instance to match objects which are both close
on the sky and have similar luminosities and redshifts.
Depending on the match type, the units of the error value(s) you enter
may be significant. In this case, there will be a unit selector
displayed alongside the entry box. You must choose units which
are correct for the number you enter.