Download Red Objects in the DFBS

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Lyra wikipedia , lookup

Corona Australis wikipedia , lookup

Aquarius (constellation) wikipedia , lookup

Hipparcos wikipedia , lookup

Corvus (constellation) wikipedia , lookup

Observational astronomy wikipedia , lookup

Ursa Minor wikipedia , lookup

Malmquist bias wikipedia , lookup

Transcript
Data analysis tools for the DFBS
Roberto Nesci
University La Sapienza, Rome Italy
•
•
•
•
•
•
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
Jenam 2007, Yerevan, Armenia
1
A portion of a DFBS plate
Jenam 2007, Yerevan, Armenia
2
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
http://byurakan.phys.uniroma1.it/
Jenam 2007, Yerevan, Armenia
3
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, Armenia
4
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 bluviolet one, and a marked dip in the green.
Jenam 2007, Yerevan, Armenia
5
Typical spectra
Jenam 2007, Yerevan, Armenia
6
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, Armenia
7
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, Armenia
8
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, Armenia
9
B mag calibration plot
Jenam 2007, Yerevan, Armenia
10
R mag calibration plot
• bb
Jenam 2007, Yerevan, Armenia
11
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, Armenia
12
Internal consistency from 6 plates, B band
•
•
•
•
•
•
FBS0150
Fbs0913
Fbs1296
Fbs1366
Fbs1393
Fbs1399
Jenam 2007, Yerevan, Armenia
13
Internal consistency from 6 plates, R band
•
•
•
•
•
•
Fbs0150
Fbs0913
Fbs1296
Fbs1366
Fbs1393
Fbs1399
Jenam 2007, Yerevan, Armenia
14
Reliability Limit
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
• Crosses: USNO-A2
• Line: DFBS
• Only not overlapped
stars are included
Jenam 2007, Yerevan, Armenia
15
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, Armenia
16
How to query the DFBS
•
You can get data from the DFBS with any (recent) browser at
http://byurakan.phys.uniroma1.it/
•
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, Armenia
17
Tools for the DFBS data
•
1.
2.
•
•
•
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:
COMPARE
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, Armenia
18
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, Armenia
19
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, Armenia
20
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, Armenia
21
The sigma-correlation plot
Stars in the
upper right
area are
selected as
candidate
variables.
Jenam 2007, Yerevan, Armenia
22
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, Armenia
23
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, Armenia
24
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, Armenia
25
Spectral response
Average spectra of
stars with B-R=0.5 in
plates of different
emulsions
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.
Jenam 2007, Yerevan, Armenia
26
Spectral shape of templates
• Comparison of templates
of a K-type star and an Atype 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, Armenia
27
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, Armenia
28
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, Armenia
29
Spectral consistency check
The spectrum of the
same object in two
plates with the same
emulsion
DFBSJ063002.4+690503
Emulsion IIaF
Plate fbs1387 (line)
Plate fbs1476 (crosses)
Jenam 2007, Yerevan, Armenia
30
The case of an AGN
Mkn 1502=I-Zw 1
• Low-redshift AGN have some
emission lines (H-beta, Hgamma, H-delta, [OII]3728)
detectable.
• H-alpha is missed in the RedBump
• The UV excess is also
detectable by comparison of a
template with the same B-R
color index.
Line: template
Squares: AGN
Jenam 2007, Yerevan, Armenia
31
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
Jenam 2007, Yerevan, Armenia
32