Automatic Detection and Classification of Variability for the RAO Variable Star Search

Details Automatic Detection and Classification of Variability for the RAO Variable Star Search Automatic Detection and Classification of Variability for the RAO Variable Star Search

Jun 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006aas...208.6701w&link_type=abstract

American Astronomical Society Meeting 208, #67.01; Bulletin of the American Astronomical Society, Vol. 38, p.146

Astronomy and Astrophysics

Astronomy

Scientific paper

The RAO Variable Star Search (RAOVS) can sample on the order of 30000 stars in a single field. With so many light curves it is important to have an automated process for detecting variability and classifying the detections. To detect periodic variations we use an epoch shifting technique, based on an analysis of variance technique, ANOVA, described by S. R. Davis. This technique allows us to increase the signal to noise for periodic signals and requires no assumption about the shape of the intrinsic light curve. As well as automatically detecting variables we have also developed an automatic classification system. This work has been supported in part by Canadian NSERC grants to E. F. Milone.

Affiliated with

Also associated with

No associations

Rating

Automatic Detection and Classification of Variability for the RAO Variable Star Search 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 Automatic Detection and Classification of Variability for the RAO Variable Star Search, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Automatic Detection and Classification of Variability for the RAO Variable Star Search will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-1856934