For a list of all services and tables belonging to this service'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, except that because the flux arrays are of different length, the blue end of the spectral column is shortened. The spectra always start at to 690 nm. The blue end depends on how far some signal was suspected by the extraction machinery.
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.
You can access this service using:
1.79693 3.96648 eV
1966.11 1980.37
This resource is not (directly) published. This can mean that it was deemed too unimportant, for internal use only, or is just a helper for a published service. Equally likely, however, it is under development, abandoned in development or otherwise unfinished. Exercise some caution.
Other services provided on the underlying data include:
The following fields are available to provide input to the service (with some renderers, some of these fields may be unavailable):
Name | Table Head | Description | Unit | UCD |
---|---|---|---|---|
ID | Id | The publisher DID of the dataset of interest | N/A | meta.id;meta.main |
maxrec | Match limit | Maximum number of records returned. Pass 0 to retrieve service parameters. | N/A | N/A |
responseformat | Output Format | File format requested for output. | N/A | meta.code.mime |
verb | Verbosity | Exhaustiveness of column selection. VERB=1 only returns the most important columns, VERB=2 selects the columns deemed useful to the average user, VERB=3 returns a table with all available columns. | N/A | N/A |
VOResource XML (that's something exclusively for VO nerds)