Sparse matrices in astronomical data reduction

Details Sparse matrices in astronomical data reduction Sparse matrices in astronomical data reduction

Oct 1992

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1992aj....104.1658b&link_type=abstract

Astronomical Journal (ISSN 0004-6256), vol. 104, no. 4, p. 1658-1661.

Mathematics

2

Astrometry, Data Reduction, Matrices (Mathematics), Covariance, Least Squares Method

Scientific paper

Sparse matrices occur frequently in astronomical data adjustment problems. Use of special techniques that take advantage of the sparcity structure can result in substantial saving of computer memory and execution time. In astrometry, for example, when one uses minor planets, or other objects, to determine parameters common to all of the observations, memory and execution time are saved by storing only the nonzero elements of the matrix in a vector and deriving an index function to locate them uniquely. Although the indexing of elements and the solution of the linear system become complicated, the saving of memory compared with an upper triangular matrix is 1-36p(p - 1)/n(n + 1), where p is the number of minor planets and n the number of unknowns. For an example with 413 observations of sixteen minor planets and two common unknowns solved by iteratively reweighted least squares, the executable code for the sparse matrix version of a program is four times faster than code for the nonsparse version.

Affiliated with

Also associated with

No associations

Rating

Sparse matrices in astronomical data reduction does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Sparse matrices in astronomical data reduction, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Sparse matrices in astronomical data reduction will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-1869429