Jenam 2007, Yerevan, Armenia1 Data analysis tools for the DFBS Overview of the DFBS What can be retrieved from the web interface Instrumental spectral response Instrumental magnitudes and calibration COMPARE: a tool for search of variables CLASSIF: a tool for spectral classification Roberto Nesci University La Sapienza, Rome Italy

Jenam 2007, Yerevan, Armenia2 A portion of a DFBS plate

Jenam 2007, Yerevan, Armenia3 Overview of the DFBS The DFBS is the digitized version of the First Byurakan Survey. The plates were taken with the 102/120/240 cm Schmidt telescope of the Byurakan Observatory and a 1.5 degree objective prism, covering 4.1x4.1 degrees. the emulsions used are mostly IIaF and IIF, giving a spectral coverage from 3800 to 7000 A. The emulsion cutoff and the wavelength compression of the prism in the Red produce a sharp Red-Head in the spectra, useful as fiducial mark. For most plates an acceptable S/N is obtained up to B=16.5; stars brighter than B=13 are at least partially saturated. The DFBS fills therefore the magnitude range between the Tycho catalogue and the Sloan Digital Sky Survey The DFBS is presently available on line from the web page

Jenam 2007, Yerevan, Armenia4 What is the DFBS The DFBS is a database containing the digitized plates of the First Byurakan Survey, the individual spectra of the sources and their B and R magnitudes. All these data can be retrieved using a dedicated WEB interface. The spectra of the objects recorded on the plates were extracted using a catalogue driven procedure, based on the USNO-A2, cut at B=17.0 In principle, therefore, no objects fainter than B=17 should be present in the DFBS database, but the accuracy of the USNO magnitudes is about 0.4 mag, so that objects actually fainter than the formal limit may be present, as well as objects actually brighter can be missed.

Jenam 2007, Yerevan, Armenia5 Spectra extraction The extraction software, bSpec, looks for each USNO-A2 object according to its coordinates, finds the position of the Red-Head of the spectrum, compute the local background, finds the spectrum direction and extract the spectrum summing over a 5 pixels wide strip. Due to the sensitivity function of the emulsion, and the variable dispersion of the prism with wavelength, the spectra have a typical “double bump” shape, with the red portion better exposed than the blu- violet one, and a marked dip in the green.

Jenam 2007, Yerevan, Armenia6 Typical spectra

Jenam 2007, Yerevan, Armenia7 Instrumental magnitudes The red side of the spectrum has a sharp cutoff, due to the emulsion sensitivity and compression of the spectrum by the prism at long wavelengths. This cutoff (Red border) is used as fiducial point on the extracted spectrum for wavelength calibration. For a point-like source this cutoff is a few pixels distant from the light baricenter, depending on the seeing. Instrumental Blue and Red magnitudes are computed integrating the spectrum over predefined pixel intervals counted from the cutoff.

Jenam 2007, Yerevan, Armenia8 Calibration of the DFBS magnitudes These instrumental magnitudes are linked to the USNO scale using the objects in the central square degree of the plate: a linear fit is made in the magnitude range 12 to 16 both for the B and R magnitudes. Overlapped objects and most discrepant objects are excluded from the fit and a second iteration gives the final calibration. The typical slope of the fit is nearly 1, indicating that the transformation from plate transparency into intensity is generally good. The rms deviation of this fit is 0.4 mag, mostly due to the intrinsic uncertainties of the USNO magnitudes.

Jenam 2007, Yerevan, Armenia9 Example of calibration plot The calibration plot for each plate is available form the web interface The plot gives also: the coefficients used to transform instrumental magnitudes into B and R (DFBS magnitudes); the peak of the luminosity function from the DFBS magnitudes in B and R

Jenam 2007, Yerevan, Armenia10 B mag calibration plot

Jenam 2007, Yerevan, Armenia11 R mag calibration plot bb

Jenam 2007, Yerevan, Armenia12 Accuracy of the DFBS magnitudes The internal accuracy of the DFBS magnitudes is better than the USNO one. To measure this accuracy we used some sky areas covered by 3 or more plates and made a comparison of the magnitudes for all the stars. Overlapped stars, or stars with a bad determination of the Red-Head, were excluded from the comparison.

Jenam 2007, Yerevan, Armenia13 Internal consistency from 6 plates, B band FBS0150 Fbs0913 Fbs1296 Fbs1366 Fbs1393 Fbs1399

Jenam 2007, Yerevan, Armenia14 Internal consistency from 6 plates, R band Fbs0150 Fbs0913 Fbs1296 Fbs1366 Fbs1393 Fbs1399

Jenam 2007, Yerevan, Armenia15 Reliability Limit Crosses: USNO-A2 Line: DFBS Only not overlapped stars are included The peak of the luminosity function of a plate can be regarded as its photometric reliability limit. Its value is given in the calibration plot for each plate. Typically it is about B=16.2

Jenam 2007, Yerevan, Armenia16 Magnitudes of AGNs For AGNs with detectable host galaxy on the POSS plates, the USNO (or GSC2) magnitudes are largely overestimated because are “isophotal diameter” sensitive. DFBS magnitudes are mainly “core sensitive” and therefore better indicative of the AGN luminosity.

Jenam 2007, Yerevan, Armenia17 How to query the DFBS You can get data from the DFBS with any (recent) browser at You can ask for : A given plate number A given position in the sky A list of object coordinates You can get: A quick look at a sky area, compared to the POSS, and at any spectrum extracted in that area (Explore); A FITS file containing a portion of a plate (GetImage) and all the extracted spectra in that sky area; A text file with a list of extracted objects and their B and R magnitudes derived from their spectra (GetSpectra); A text file with all the spectra in given sky area, from one plate or from all the plates covering that area (GetSpectra).

Jenam 2007, Yerevan, Armenia18 Tools for the DFBS data To help the user (and ourselves!) managing the DFBS data, we prepared some software tools, written in FORTRAN77, which use the data as downloaded from the WEB interface: 1.COMPARE 2.CLASSIF COMPARE is a tool to look for variable sources in a list of sources detected in at least 2 plates. CLASSIF is a tool to perform an automatic spectral classification aimed at finding “peculiar” objects. Both codes can be downloaded from the DFBS web page.

Jenam 2007, Yerevan, Armenia19 Search for Variable Objects the FORTRAN program, COMPARE, has been developed, which uses the output of the DFBS, and makes the following operations: matches the objects by name For each object computes: the average B and R magnitudes, the rms deviation (dev) of the B and R magnitudes, the correlation between B and R magnitude. Then computes, for each magnitude range, the average rms deviation (DEV) and the spread (SIG) around this value For each star computes a variability factor sigma=(dev-DEV)/SIG Stars with sigma > 3 AND with positive (>0.7) correlation between B and R are selected as variable candidates.

Jenam 2007, Yerevan, Armenia20 Trial area We made a search for variable objects using a trial sky area of about 1 square degrees (RA 01h26m, DEC +27d16m), covered by 6 plates (0150, 0913, 1296, 1366, 1393, 1399). Sources where collected from the DFBS web interface (GetSpectra). Two variables are known in this area EH Psc (B = 12, a semiregular Red Star) and BN Psc (B = 16, an eclipse variable).

Jenam 2007, Yerevan, Armenia21 Rms deviation for magnitude bins Dots: average rms deviation for each magnitude bin Line: 3 sigma limit for each magnitude bin Stars must be above the line to be candidate variables

Jenam 2007, Yerevan, Armenia22 The sigma-correlation plot Stars in the upper right area are selected as candidate variables.

Jenam 2007, Yerevan, Armenia23 Results EH Psc showed a variation in B of 0.5 mag, while it was saturated in R. BN Psc was too faint to show reliable variations in B. Two other stars showed variations, but were recognized as plate defects.

Jenam 2007, Yerevan, Armenia24 CLASSIF a FORTAN code, CLASSIF, makes spectral templates from the spectra of a given plate. The following operations are performed: 1.a selection is made of well-exposed spectra both in the Red and the Blue 2.the B-R color index is used to average similar spectra in bins 0.2 mag wide; 3.the most discrepant spectra for each B-R bin are excluded and a new average spectrum is computed; the rms deviation for each bin is computed; 4.each spectrum of the plate is compared with the grid of templates and the best fitting is selected: if the deviation from the template is too large the spectrum is flagged as peculiar.

Jenam 2007, Yerevan, Armenia25 Emulsions and classification Due to differences in the spectral sensitivities of the emulsions used for the FBS plates, separate templates must be made for each emulsion type. The most frequent types of emulsions are: IIaF IIAF 103aF II F

Jenam 2007, Yerevan, Armenia26 Spectral response IIaF and 103aF are very similar. IIF and IIaF are similar, but IIF are more red-sensitive. IIAF emulsions are markedly different in spectral shape. Average spectra of stars with B-R=0.5 in plates of different emulsions

Jenam 2007, Yerevan, Armenia27 Spectral shape of templates Comparison of templates of a K-type star and an A- type star. The most prominent features are due to the spectral sensitivity of the plate, NOT to real stellar features. Narrow band indices must be built “AD HOC” to select a well defined class of object.

Jenam 2007, Yerevan, Armenia28 Check of spectral classification A template is made averaging normalized spectra in a bin of Delta(B-R)=0.2 The rms deviation between the template and each spectrum, used to build it, is about 15% CLASSIF looks for the best fitting template of each spectrum on the plate, trying all the templates. The spread in (B-R) within each class is consistent with the intrinsic spread in color and spectral noise

Jenam 2007, Yerevan, Armenia29 Templates stability Templates for a given color index from different plates of the same emulsion are very similar, but not identical. If the inclination of the spectrum is appreciably different for two plates, the length of the spectra is also different and produces a systematic effect on the templates.

Jenam 2007, Yerevan, Armenia30 Spectral consistency check Emulsion IIaF Plate fbs1387 (line) Plate fbs1476 (crosses) The spectrum of the same object in two plates with the same emulsion DFBSJ

Jenam 2007, Yerevan, Armenia31 The case of an AGN Low-redshift AGN have some emission lines (H-beta, H- gamma, H-delta, [OII]3728) detectable. H-alpha is missed in the Red- Bump The UV excess is also detectable by comparison of a template with the same B-R color index. Line: template Squares: AGN Mkn 1502=I-Zw 1

Jenam 2007, Yerevan, Armenia32 Conclusions The computer codes presented are aimed at helping the general user to manage the data retrieved from the DFBS PHOTOMETRY Large magnitude variations (about 1 mag) can be safely detected for objects < B=16. AGN magnitudes are closer to the real nuclear value than those available from present public POSS-based catalogues. SPECTROSCOPY Very strong emission line objects can be recognized UV excesses can be detected in objective manner Reliable classification can be obtained down to B=15.5