Other
Scientific paper
Mar 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011ycat..74151061m&link_type=abstract
VizieR On-line Data Catalog: J/MNRAS/415/1061. Originally published in: 2011MNRAS.415.1061M
Other
Blue Objects, Photometry: Photographic, Binaries: Cataclysmic, Stars: White Dwarf
Scientific paper
A new method for combined calculations of magnitudes based on accurate measurements of POSS1 and POSS2 epoch plates is given. The photometric accuracy of various surveys and catalogs has been estimated and established and statistical weights for each of them have been calculated. To achieve the best possible magnitudes, weighted averaging of data from USNO-A2.0, APM, MAPS, USNO-B1.0, and GSC 2.3.2 catalogs have been used. The rms accuracy of magnitudes achieved for POSS1 is 0.184 mag for B and 0.173 mag for R and for POSS2 is 0.138 mag for B and 0.128 mag for R. We have derived the best POSS1 and POSS2 magnitudes for the FBS blue stellar objects. We have refined the transformation formulae between the POSS1 and POSS2 magnitudes and SDSS ones and standard UBV system. Using these accurate magnitudes, we have estimated the variability of the FBS blue stellar objects and revealed probable and possible variables. We have worked out methods to control and exclude accidental errors that appear in any survey. We have compared and combined our results with those given in NSVS database and obtained better candidates for variability. Having excluded variables, we have combined POSS1 and POSS2 data for the rest of objects to achieve even better magnitudes and colors; the rms being smaller than 0.1 mag both in B and R and for the B-R colors. This approach has been applied to the First Byurakan Survey blue stellar objects containing significant number of white dwarfs, cataclysmic variables, as well as extragalactic objects (quasars, Seyferts, BL Lac objects). Altogether 336 variable objects have been revealed with POSS2-POSS1 >= 3σ of the errors. An electronic table of these objects is given.
Candidate variables are divided into 4 classes: extreme, strong, probable and possible variables. For a more reliable sample of variable objects we excluded possible ones from the list and were left with 161 objects. Analyzing radio and X-ray properties of these objects, we have revealed their nature and re-discovered or revealed candidate AGN, CVs, WDs and other objects.
(2 data files).
Mickaelian Areg M.
Mikayelyan Gor A.
Sinamyan Parandzem K.
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