The Byurakan/Hamburg/ROSAT Catalogue (BHRC) of the optical identifications of X-ray sources is presented. The BHRC includes all 2791 sources from the ROSAT-FSC with |b| ≥ 30• , δ ≥ 0 • and ROSAT count rate CR > 0.04 cts s −1 . For the optical identifications, we used the Hamburg Quasar Survey (HQS) digitized spectroscopic plates, the DSS1 and DSS2 (blue, red, and IR) images, the MAPS photometric data, the USNO-B1.0 (for proper motions), the NVSS and FIRST radio, and the IRAS and 2MASS infrared catalogues. From the DSS images we obtained positional, brightness, color, extension, variability, proper motion information, and measured the optical-to-X-ray distance. Based on the DSS images, a morphological classification was made. Available SIMBAD and NED data were used as well. Cross-correlations were made with AGN, white dwarf, and cataclysmic variable catalogues (322/8/7 associations, respectively). We managed to identify 97% of sources (2696 sources) that are associated with 3202 optical objects. 2248 X-ray sources have a single optical counterpart, 144 have a double or multiple optical counterpart (binaries, galaxy groups etc.), and 304 have ambiguous identifications. We find that some of the latest might actually be blends of two X-ray sources that were not resolved by ROSAT. The QSOs and AGN represent the largest group of X-ray counterparts (56.2%); bright stars (including late type stars, but excluding WDs and CVs) are counterparts for 33.2% of sources, and the bright galaxies and groups of galaxies comprise 9.2%. We found a number of close galaxy pairs (possibly interacting/merging galaxies) that are counterparts for X-ray sources (3.0%), as well as 1.0% WDs and 0.4% CVs. The BHRC may be used for selection and for studies of samples of various classes of X-ray emitters.

Optically bright Galactic stars (V 13 mag) having f ν (24 µm) > 1 mJy are identified in Spitzer mid-infrared surveys within 8.2 deg 2 for the Boötes field of the NOAO Deep Wide-Field Survey and within 5.5 deg 2 for the First Look Survey (FLS). 128 stars are identified in Boötes and 140 in the FLS, and their photometry is given. (K-[24]) colors are determined using K magnitudes from the 2MASS survey for all stars in order to search for excess 24 µm luminosity compared to that arising from the stellar photosphere. Of the combined sample of 268 stars, 141 are of spectral types F, G, or K, and 17 of these 141 stars have 24 µm excesses with (K-[24]) > 0.2 mag. Using limits on absolute magnitude derived from proper motions, at least 8 of the FGK stars with excesses are main sequence stars, and estimates derived from the distribution of apparent magnitudes indicate that all 17 are main sequence stars. These estimates lead to the conclusion that between 9% and 17% of the main sequence FGK field stars in these samples have 24 µm infrared excesses. This result is statistically similar to the fraction of stars with debris disks found among previous Spitzer targeted observations of much brighter, main sequence field stars.

Context. The First Byurakan Survey (FBS), also known as the Markarian Survey, is the largest low resolution spectroscopic survey of the sky and led to the discovery of 1500 UV-excess (UVX) galaxies and starburst galaxies. The FBS plates have also been used to search for UVX stellar objects, late-type stars, and for the identification of unusual infrared sources. Aims. The Digitized First Byurakan Survey (DFBS) provides the astronomical community with a digitized version of the FBS images and with the extracted spectra for the objects present in the plates. Methods. Nearly 2000 plates have been scanned and stored and programs were developed to compute the astrometric solution, extract the spectra, and apply wavelength and photometric calibration for the objects present in the plates. Results. The DFBS database and catalog of objects has been assembled. The DFBS database contains data for 20 000 000 objects present in the survey and provides tools for accessing the DFBS.Conclusions. New scientific projects as well as existing surveys will benefit by the digitized images and the ready-to-use extracted spectra which will allow an efficient computer-based analysis of the dataset.

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