Finding Match Sets
- Author:
- Serge Monkewitz
Contents | |
Lane Subdivision
The problem of finding a match set
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The specific approach taken by the WAX software is to assign apparitions to small lanes (spatial bins corresponding to a range of declinations and right ascensions), and then determining, given a lane , which other lanes contain apparitions that potentially belong to match sets of apparitions in
. For any single apparition, only a tiny area of the sky is examined to find a match set. This is the key to obtaining good performance in the swiss cheese algorithm.
Specifically, each band is split into lanes
where
,
and
,
. Each lane covers a range of right ascensions :
-
covers right ascensions in the range
-
covers right ascensions in the range
- ...
-
covers right ascensions in the range


Determining the number of lanes per band
The actual number of lanes in a band is determined by picking a minimum lane width
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
Without loss of generality, let (the angle between unit vectors is invariant under rotation). Furthermore, define
. This minimum distance occurs between the positions
and
, expressed in polar coordinates (unless
, in which case this minimum distance is either undefined or zero).
When expressed as vectors in ,
and
. Using the relation
, the following formula is obtained :
To find the number of lanes in a band the actual lane width for each possible value of is computed. The number of lanes is determined from the largest
resulting in a lane width greater than the requested minimum, or
if this is impossible. For example, bands containing a pole have a lane width of zero regardless of
and will therefore contain just a single lane. Since this directly effects the efficiency of the match set finding algorithm, the pole bands should be as skinny as possible.
The WAX application uses a minimum lane width of arcsecond when the -o option is specified, and
arcseconds otherwise.
Mapping positions (apparitions) to lanes
Positions are trivially mapped to lanes: given a right ascension
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Once all apparitions in a band have been retrieved and assigned to the appropriate lanes, the apparitions in each lane are sorted in order of increasing declination.
Finding lane windows
Given an arbitrary apparition

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
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Using the relations derived above, the lane window is the smallest integer satisfying
or if the relation cannot be satisfied.
Finding a match set
To find a match set for an apparition



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
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



Furthermore, if the position has a declination
, then apparitions in the match set
will have declinations in the range
. For each
being searched, the apparitions in this range can be found using a simple binary search (since apparitions within a lane are declination sorted). Each such apparition
is then tested against
, and included in
if and only if
Lane Walks
The density pass and swiss cheese pass of the swiss cheese algorithm involve computing match sets for almost all retrieved apparitions and allow freedom in the order in which match sets are found.Number the apparitions based on their enclosing lane and position within that lane as follows :
where has declination
. Since the apparitions in a lane are declination sorted,
By "walking" up the apparitions within a single lane , finding match sets for
, then
, etc... the match set finding process can be made even more efficient :
-
The lanes
containing potential members of a match set for
need only be computed once
.
-
The range of apparitions
within declination
of
can be used as a starting point for finding the range of apparitions within declination
of
.
This leads to the lane walking algorithm described below.
Finding matches from a single lane
Let

Consider the first apparition . Find the smallest non-negative integer
such that
has declination
(using a binary or linear search).
Now, let . While
:
-
add
to the match set for
if and only if
-
increment
At this point, all apparitions in belonging to the match set for
have been found, so the next apparition in
,
is considered. To find the first apparition in
possibly belonging to the match set for
, increment
until
. Then repeat the steps above, finding all apparitions in
belonging to the match set for
.
Continue in similar fashion until all apparitions in have been considered.
Final match set finding algorithm
The final algorithm for match set finding simply repeats the steps detailed above for each lane potentially containing matches for apparitions in

By walking each lane in this manner, match sets for every apparition in
are found.
Generated on Thu Oct 21 13:19:38 2004 for WAX Version 2.1 by