Table Description:
This table is available for ADQL queries and through the TAP endpoint.
Resource Description:
The First Byurakan Survey (FBS) is the largest and the first systematic objective prism survey of the extragalactic sky. It covers 17,000 sq.deg. in the Northern sky together with a high galactic latitudes region in the Southern sky. The FBS has been carried out by B.E. Markarian, V.A. Lipovetski and J.A. Stepanian in 1965-1980 with the Byurakan Observatory 102/132/213 cm (40"/52"/84") Schmidt telescope using 1.5 deg. prism. Each FBS plate contains low-dispersion spectra of some 15,000-20,000 objects; the whole survey consists of about 20,000,000 objects.
For a list of all services and tables belonging to this table's resource, see Information on resource 'Digitized First Byurakan Survey (DFBS) Extracted Spectra'
Note that the spectra are not flux calibrated. Indeed, they were scanned off of different emulsions, and only spectra from compatible emulsions should be compared. The following emulsions occur in the database:
n | emulsion |
---|---|
334409 | 103aF |
18695 | 103aO |
3622 | IF |
13555 | IIAD |
2409058 | IIAF |
16545 | IIAF bkd |
3254370 | IIF |
313287 | IIF bkd |
7871 | IIIAJ bkd |
6645 | IIIF |
18967 | IIIaF |
8122 | IIaD |
3565737 | IIaF |
6735 | IIaO |
16755 | OAF |
8794 | ORWO CP-3 |
8097 | ZP-3 |
23702 | Zu-2 |
Upper- and lowercase versions of the emulsions are actually different (e.g., IIAD was produced in England, IIaD in the US). Their properties are different enough to make mixing spectra for the different emulsions unwise.
Also note the sp_class column. Unless you take great precaution, you probably should only use spectra with sp_class='OK'.
Spectra can be retrieved in VOTable form (via SSA or the accref field from the TAP table), but it will usually be faster to directly pull them from the spectral and flux arrays.
Actually, array indices in the flux arrays correspond to fixed wavelengths. In other words, the spectral column is constant in the database.
The flux arrays are actually of different length. The always start at index 1, corresponding to 690 nm. The blue end depends on how far some signal was suspected.
While ADQL support for array operations is rather weak, you can subscript arrays. Because of the fixed bins, you can therefore select by flux ratios (never use absolute numbers here; they are meaningless). For instance, to select objects with a high (apparent) Halpha emission (656 nm, corresponding to array index 3), you might so something like:
select * from dfbsspec.spectra where flux[3]/(flux[40]+flux[41]+flux[42])>30 and sp_class='OK'
Since the table needs to be sequentially scanned for this, it will take a minute or so. Combine with an object selection (see below) or other criteria if possible.
You cannot currently use the ADQL aggregate function AVG with arrays (which should be fixed at some time in the future). Meanwhile, you can work around this with a clumsy construction like this (this query will give you average spectra by magnitude bin; don't run it just for fun, it'll take a while):
select round(magb) as bin, avg(flux[1]) as col1, avg(flux[2]) as col2, avg(flux[3]) as col3, avg(flux[4]) as col4, avg(flux[5]) as col5, avg(flux[6]) as col6, avg(flux[7]) as col7, avg(flux[8]) as col8, avg(flux[9]) as col9, avg(flux[10]) as col10, avg(flux[11]) as col11, avg(flux[12]) as col12, avg(flux[13]) as col13, avg(flux[14]) as col14, avg(flux[15]) as col15, avg(flux[16]) as col16, avg(flux[17]) as col17, avg(flux[18]) as col18, avg(flux[19]) as col19, avg(flux[20]) as col20, avg(flux[21]) as col21, avg(flux[22]) as col22, avg(flux[23]) as col23, avg(flux[24]) as col24, avg(flux[25]) as col25, avg(flux[26]) as col26, avg(flux[27]) as col27, avg(flux[28]) as col28, avg(flux[29]) as col29, avg(flux[30]) as col30, avg(flux[31]) as col31, avg(flux[32]) as col32, avg(flux[33]) as col33, avg(flux[34]) as col34, avg(flux[35]) as col35, avg(flux[36]) as col36, avg(flux[37]) as col37, avg(flux[38]) as col38, avg(flux[39]) as col39, avg(flux[40]) as col40, avg(flux[41]) as col41, avg(flux[42]) as col42, avg(flux[43]) as col43, avg(flux[44]) as col44, avg(flux[45]) as col45, avg(flux[46]) as col46, avg(flux[47]) as col47, avg(flux[48]) as col48, avg(flux[49]) as col49, avg(flux[50]) as col50, avg(flux[51]) as col51, avg(flux[52]) as col52, avg(flux[53]) as col53, avg(flux[54]) as col54, avg(flux[55]) as col55, avg(flux[56]) as col56, avg(flux[57]) as col57, avg(flux[58]) as col58, avg(flux[59]) as col59 from dfbsspec.spectra where sp_class='OK' group by bin
To map col<n> to wavelenghts, see the contents of (any) spectral column.
To compute an average spectrum for a class of objects, we suggest to pull positions of such objects from SIMBAD and then fetch the associate spectra from this database. Since the response function of the photographic plates had a strong magnitude dependence, restrict the objects to a small magnitude range, for instance:
select otype, ra, dec, flux from basic join flux on (oid=oidref) where otype='HS*' and dec>-15 and filter='G' and flux between 12.5 and 13.5
(to be executed on SIMBAD's TAP service, see also SIMBAD object types).
With the resulting table, go do this service and execute a query like:
SELECT specid, spectral, flux FROM dfbsspec.spectra AS db JOIN TAP_UPLOAD.t1 AS tc ON DISTANCE(tc.ra, tc.dec, db.ra, db.dec)<5./3600. WHERE sp_class='OK'
(adjust t1 according to your client's rules; in TOPCAT, that's t plus the table number from the control window).
The original aim of the First Byurakan Survey was to search for galaxies with UV excess (1986ApJS...62..751M, Markarian et al. 1989,1997- catalogue No. VII/172 at CDS). Successively, the amount of spectral information contained in the plates allowed the development of several other projects concerning the spectral classification of Seyfert Galaxies (Weedman and Kachikian 1971), the first definition of starburst galaxies (Weedman 1977 ), the discovery and investigation of blue stellar objects (Abrahamian and Mickaelian, 1996, Mickaelian et al 2001, 2002, CDS catalogue No II/223) and a survey for late-type stars (Gigoyan et al. 2002). All these results were obtained by eye inspection of the plates performed with the aid of a microscope at the Byurakan Observatory. The number and classes of new objects discovered FBS made clear the need of open access to FBS for the entire astronomical community.
This table has an associated publication. If you use data from it, it may be appropriate to reference 2007A&A...464.1177M (ADS BibTeX entry for the publication) either in addition to or instead of the service reference.
To cite the table as such, we suggest the following BibTeX entry:
@MISC{vo:dfbsspec_ssa, year=2017, title={Digitized First Byurakan Survey ({DFBS}) Extracted Spectra}, author={Markarian, B.E. and N.N.}, url={http://arvo-registry.sci.am/tableinfo/dfbsspec.ssa}, howpublished={{VO} resource provided by the {ArVO} Byurakan} }
Sorted by DB column index. [Sort alphabetically]
Name | Table Head | Description | Unit | UCD |
---|---|---|---|---|
accref | Product key | Access key for the data | N/A | meta.ref.url;meta.dataset |
owner | Owner | Owner of the data | N/A | N/A |
embargo | Embargo ends | Date the data will become/became public | a | N/A |
mime | Type | MIME type of the file served | N/A | meta.code.mime |
accsize | File size | Size of the data in bytes | byte | N/A |
ssa_dstitle | Title | A compact and descriptive designation of the dataset. | N/A | meta.title;meta.dataset |
ssa_creatorDID | C. DID | Dataset identifier assigned by the creator | N/A | meta.id |
ssa_pubDID | P. DID | Dataset identifier assigned by the publisher | N/A | N/A |
ssa_cdate | Proc. Date | Processing/Creation date | N/A | time;meta.dataset |
ssa_pdate | Pub. Date | Date last published. | N/A | N/A |
ssa_bandpass | Bandpass | Bandpass (i.e., rough spectral location) of this dataset; this should be the most appropriate term from the values of VODataService vs:Waveband. | N/A | instr.bandpass |
ssa_cversion | C. Version | Creator assigned version for this dataset (will be incremented when this particular item is changed). | N/A | meta.version;meta.dataset |
ssa_targname | Object | Common name of object observed. | N/A | meta.id;src |
ssa_targclass | Ob. cls | Object class (star, QSO,...; use Simbad object classification http://simbad.u-strasbg.fr/simbad/sim-display?data=otypes if at all possible) | N/A | src.class |
ssa_redshift | z | Redshift of target object | N/A | src.redshift |
ssa_targetpos | Obj. pos | Equatorial (ICRS) position of the target object. | N/A | pos.eq;src |
ssa_snr | SNR | Signal-to-noise ratio estimated for this dataset | N/A | stat.snr |
ssa_location | Location | ICRS location of aperture center | deg | pos.eq |
ssa_aperture | Aperture | Angular diameter of aperture | deg | instr.fov |
ssa_dateObs | Date Obs. | Midpoint of exposure | d | time.epoch |
ssa_timeExt | Exp. Time | Exposure duration | s | time.duration |
ssa_specmid | Mid. Band | Midpoint of region covered in this dataset | m | em.wl;instr.bandpass |
ssa_specext | Bandwidth | Width of the spectrum | m | em.wl;instr.bandwidth |
ssa_specstart | Band start | Lower value of spectral coordinate | m | em.wl;stat.min |
ssa_specend | Band end | Upper value of spectral coordinate | m | em.wl;stat.max |
ssa_length | Length | Number of points in the spectrum | N/A | N/A |
ssa_dstype | Data type | Type of data (spectrum, time series, etc) | N/A | N/A |
ssa_publisher | Publisher | Publisher of the datasets included here. | N/A | N/A |
ssa_creator | Creator | Creator of the datasets included here. | N/A | N/A |
ssa_collection | Collection | A short handle naming the collection this spectrum belongs to. | N/A | N/A |
ssa_instrument | Instrument | Instrument or code used to produce these datasets | N/A | meta.id;instr |
ssa_datasource | Src | Method of generation for the data (one of survey, pointed, theory, custom, artificial). | N/A | N/A |
ssa_creationtype | Using | Process used to produce the data (archival, cutout, filtered, mosaic, projection, spectralExtraction, or catalogExtraction) | N/A | N/A |
ssa_reference | Ref. | URL or bibcode of a publication describing this data. | N/A | N/A |
ssa_fluxStatError | Err. flux | Statistical error in flux | N/A | stat.error;phot.flux.density;em |
ssa_fluxSysError | Sys. Err flux | Systematic error in flux | N/A | stat.error.sys;phot.flux.density;em |
ssa_fluxcalib | Calib Flux | Type of flux calibration (ABSOLUTE, CALIBRATED, RELATIVE, NORMALIZED, or UNCALIBRATED). | N/A | N/A |
ssa_binSize | Spect. Bin | Bin size in wavelength | m | em.wl;spect.binSize |
ssa_spectStatError | Err. Spect | Statistical error in wavelength | m | stat.error;em |
ssa_spectSysError | Sys. Err. Spect | Systematic error in wavelength | m | stat.error.sys;em |
ssa_speccalib | Calib. Spect. | Type of wavelength calibration | N/A | meta.code.qual |
ssa_specres | Spec. Res. | Resolution on the spectral axis | m | spect.resolution;em.wl |
ssa_region | Coverage | Rough coverage based on location and aperture. | N/A | N/A |
magb | mag. B | Source object magnitude in Johnson B | mag | phot.mag;em.opt.B |
magr | mag. R | Source object magnitude in Johnson R | mag | phot.mag;em.opt.R |
plate | Src. Plate | Number of the plate this spectrum was extracted from. Technically, this is a foreign key into dfbs.plates. | N/A | N/A |
ra | RA | ICRS RA of the source of this spectrum. | deg | pos.eq.ra;meta.main |
dec | Dec | ICRS Dec of the source of this spectrum. | deg | pos.eq.dec;meta.main |
Columns that are parts of indices are marked like this.
The following services may use the data contained in this table:
VO nerds may sometimes need VOResource XML for this table.
Note that the spectra are not flux calibrated. Indeed, they were scanned off of different emulsions, and only spectra from compatible emulsions should be compared. The following emulsions occur in the database:
n | emulsion |
---|---|
334409 | 103aF |
18695 | 103aO |
3622 | IF |
13555 | IIAD |
2409058 | IIAF |
16545 | IIAF bkd |
3254370 | IIF |
313287 | IIF bkd |
7871 | IIIAJ bkd |
6645 | IIIF |
18967 | IIIaF |
8122 | IIaD |
3565737 | IIaF |
6735 | IIaO |
16755 | OAF |
8794 | ORWO CP-3 |
8097 | ZP-3 |
23702 | Zu-2 |
Upper- and lowercase versions of the emulsions are actually different (e.g., IIAD was produced in England, IIaD in the US). Their properties are different enough to make mixing spectra for the different emulsions unwise.
Also note the sp_class column. Unless you take great precaution, you probably should only use spectra with sp_class='OK'.
Spectra can be retrieved in VOTable form (via SSA or the accref field from the TAP table), but it will usually be faster to directly pull them from the spectral and flux arrays.
Actually, array indices in the flux arrays correspond to fixed wavelengths. In other words, the spectral column is constant in the database.
The flux arrays are actually of different length. The always start at index 1, corresponding to 690 nm. The blue end depends on how far some signal was suspected.
While ADQL support for array operations is rather weak, you can subscript arrays. Because of the fixed bins, you can therefore select by flux ratios (never use absolute numbers here; they are meaningless). For instance, to select objects with a high (apparent) Halpha emission (656 nm, corresponding to array index 3), you might so something like:
select * from dfbsspec.spectra where flux[3]/(flux[40]+flux[41]+flux[42])>30 and sp_class='OK'
Since the table needs to be sequentially scanned for this, it will take a minute or so. Combine with an object selection (see below) or other criteria if possible.
You cannot currently use the ADQL aggregate function AVG with arrays (which should be fixed at some time in the future). Meanwhile, you can work around this with a clumsy construction like this (this query will give you average spectra by magnitude bin; don't run it just for fun, it'll take a while):
select round(magb) as bin, avg(flux[1]) as col1, avg(flux[2]) as col2, avg(flux[3]) as col3, avg(flux[4]) as col4, avg(flux[5]) as col5, avg(flux[6]) as col6, avg(flux[7]) as col7, avg(flux[8]) as col8, avg(flux[9]) as col9, avg(flux[10]) as col10, avg(flux[11]) as col11, avg(flux[12]) as col12, avg(flux[13]) as col13, avg(flux[14]) as col14, avg(flux[15]) as col15, avg(flux[16]) as col16, avg(flux[17]) as col17, avg(flux[18]) as col18, avg(flux[19]) as col19, avg(flux[20]) as col20, avg(flux[21]) as col21, avg(flux[22]) as col22, avg(flux[23]) as col23, avg(flux[24]) as col24, avg(flux[25]) as col25, avg(flux[26]) as col26, avg(flux[27]) as col27, avg(flux[28]) as col28, avg(flux[29]) as col29, avg(flux[30]) as col30, avg(flux[31]) as col31, avg(flux[32]) as col32, avg(flux[33]) as col33, avg(flux[34]) as col34, avg(flux[35]) as col35, avg(flux[36]) as col36, avg(flux[37]) as col37, avg(flux[38]) as col38, avg(flux[39]) as col39, avg(flux[40]) as col40, avg(flux[41]) as col41, avg(flux[42]) as col42, avg(flux[43]) as col43, avg(flux[44]) as col44, avg(flux[45]) as col45, avg(flux[46]) as col46, avg(flux[47]) as col47, avg(flux[48]) as col48, avg(flux[49]) as col49, avg(flux[50]) as col50, avg(flux[51]) as col51, avg(flux[52]) as col52, avg(flux[53]) as col53, avg(flux[54]) as col54, avg(flux[55]) as col55, avg(flux[56]) as col56, avg(flux[57]) as col57, avg(flux[58]) as col58, avg(flux[59]) as col59 from dfbsspec.spectra where sp_class='OK' group by bin
To map col<n> to wavelenghts, see the contents of (any) spectral column.
To compute an average spectrum for a class of objects, we suggest to pull positions of such objects from SIMBAD and then fetch the associate spectra from this database. Since the response function of the photographic plates had a strong magnitude dependence, restrict the objects to a small magnitude range, for instance:
select otype, ra, dec, flux from basic join flux on (oid=oidref) where otype='HS*' and dec>-15 and filter='G' and flux between 12.5 and 13.5
(to be executed on SIMBAD's TAP service, see also SIMBAD object types).
With the resulting table, go do this service and execute a query like:
SELECT specid, spectral, flux FROM dfbsspec.spectra AS db JOIN TAP_UPLOAD.t1 AS tc ON DISTANCE(tc.ra, tc.dec, db.ra, db.dec)<5./3600. WHERE sp_class='OK'
(adjust t1 according to your client's rules; in TOPCAT, that's t plus the table number from the control window).
The original aim of the First Byurakan Survey was to search for galaxies with UV excess (1986ApJS...62..751M, Markarian et al. 1989,1997- catalogue No. VII/172 at CDS). Successively, the amount of spectral information contained in the plates allowed the development of several other projects concerning the spectral classification of Seyfert Galaxies (Weedman and Kachikian 1971), the first definition of starburst galaxies (Weedman 1977 ), the discovery and investigation of blue stellar objects (Abrahamian and Mickaelian, 1996, Mickaelian et al 2001, 2002, CDS catalogue No II/223) and a survey for late-type stars (Gigoyan et al. 2002). All these results were obtained by eye inspection of the plates performed with the aid of a microscope at the Byurakan Observatory. The number and classes of new objects discovered FBS made clear the need of open access to FBS for the entire astronomical community.