Information on Service 'CALIFA DR3'

[Use this service from your browser]

Further access options are discussed below

Split spectra from the CALIFA DR3 cubes. This service serves one spectrum each per pixel in each cube where there is at least one valid spaxel. Where both V500 and COMB data is available, COMB spectra are served. WARNING: The individual spectra are not independent. Also, error estimates over wide spectral ranges based on the error estimates served here are unreliable.

For a list of all services and tables belonging to this service's resource, see Information on resource 'CALIFA (Calar Alto Legacy Integral Field spectroscopy Area) survey DR3'

Service Documentation

A TAP example

The CALIFA cubes are available in database tables at this site. Here's an example for how to solve a little problem using VO tools.

There are two additional examples for how to use TAP to explore the CALIFA data in our TAP examples:

Problem

The idea is to put all cubes at the rest frame. So if you have the velocity recession in the header (MED_VEL; or taken from NED), just have to do:

w_rest = w_obs/(1 + (recvel/c_speed))

Once I have a common wavelength reference, I want to look if I have a certain emission line. Let's say I look for Halpha. An easy way to do it without measuring the line is define a continuum an compare the fluxes. So if:

flux_6563 / [(flux_6540+flux_6700)/2.0] > 3

it's a hint of having Halpha emission. As you see, I use to continuum points at both sides of the line.

Then, I would ask for all spectra in the cubes having this condition.

Solution

There are several ways to solve this problem using VO tools and services, but we will, somewhat unorthodoxly, use TAP, a protocol to exchanges SQL (actually, ADQL) queries and query results with servers. There are several clients that can do this; if you have no other preferences, use TOPCAT. There, open VO/TAP, push the pin in the left upper corner of the window (to keep the window open after sending off a query), and in the TAP URL field below, enter http://dc.g-vo.org/tap. Hit "Enter query", and you are in a dialog that lets you inspect a server's table metadata (look for tables in califadr3) and enter queries.

The targets of the CALIFA survey and their redshifts are in the califadr3.objects table. So, to compute the wavelengths in question you could say:

select
        target_name,
        califaid,
        6563*(1+redshift) as lha,
        6540*(1+redshift) as lri,
        6700*(1+redshift) as lle
from califadr3.objects                                         (1)

The wavelength/fluxes pairs, on the other hand, and in tables califadr3.fluxv500 (or v1200) and califadr3.fluxposv500; in the former, flux is given over lambda, califa id (a small integer; let's use 909, corresponding to UGC 12519, as an example further down) and pixel coordinates, in the latter, it is celestial positions.

Since we cannot usefully compare floats for equality in generally, and in particular not here, to retrieve fluxes for a single wavelength you need to restrict lambda to an interval wide enough. How wide the interval needs to be, you can figure out be determining the spacing of samples. For the V500 data set, this could look like this:

select distinct top 2 lambda
from califadr3.fluxv500
order by lambda (2)

(This is fast although there's dozens of millions of lambdas in this table because there's an index on lambda, and there are not may distinct values). If you try it, you'll see that we have steps of two Ångström, so you'll want the interval to be something like 2.2 Ångström.

To obtain fluxes while while having the redshift available -- as needed here -- you need to join the objects with the flux tables; here, you can use a "NATURAL" join, which means all columns identically names are to be used for joining:

select top 5000 target_name, xindex, yindex, lambda, flux
from
  califadr3.fluxv500
  natural join califadr3.objects
where
  lambda between 6563*(1+redshift)-1.1 and 6563*(1+redshift)+1.1
  and target_name='UGC12519'                                 (3)

The "top 5000" is necessary here to retrieve all fluxes: to protect your nerves, the server inserts a "top 2000" unless you order something else. The restriction on the califaid makes sure we don't retrieve all fluxes between our two wavelengths in the CALIFA tables.

This table has pixel coordinates. The physical positions for each pixel are in a table called califadr3.spectra. To get them into your table, you'll need another join:

select top 5000 target_name, raj2000, dej2000, lambda, flux
from
  califadr3.fluxv500
  natural join califadr3.objects
  natural join califadr3.spectra
where
  lambda between 6563*(1+redshift)-1.1 and 6563*(1+redshift)+1.1
  and target_name='UGC12519'                                 (3)

At this point you could retrieve the flux maps at the three tables and use, for instance, TOPCAT's crossmatch functionality to do the match client-side. However, let's assume we want to keep processing server-side, e.g., because we want to run this on a lot of objects and don't want to download all the layers.

To retrieve fluxes at multiple wavelengths, you can query like this:

select top 5000 target_name, raj2000, dej2000, lambda, flux
from
  califadr3.fluxv500
  natural join califadr3.objects
  natural join califadr3.spectra
where (
  lambda between 6563*(1+redshift)-1.1 and 6563*(1+redshift)+1.1
  or lambda between 6540*(1+redshift)-1.1 and 6540*(1+redshift)+1.1
  or lambda between 6700*(1+redshift)-1.1 and 6700*(1+redshift)+1.1)
  and target_name='UGC12519'                                 (5)

The problem with this is that you cannot compute the criterion for a strong Halpha emission from this as the three fluxes are in three different rows. When you are in that situation, SQL offers grouping -- this means that rows sharing a criterion end up in a bag; you can then use "aggregate functions" on these. Note, that as most things in the relational world, the items in the bag are not sorted.

As a general word of advice: In the SQL world, thinking in array terms is typically going to lead to complicated and slow queries. Try thinking in terms of sets and matters will become manageable.

ADQL's aggregate functions are a bit limited, but for this case they're just enough -- just compare the maximum flux to the average flux:

select top 5000 califaid, xindex, yindex
from
  califadr3.fluxv500
  natural join califadr3.objects
where (
  lambda between 6563*(1+redshift)-1.1 and 6563*(1+redshift)+1.1
  or lambda between 6540*(1+redshift)-1.1 and 6540*(1+redshift)+1.1
  or lambda between 6700*(1+redshift)-1.1 and 6700*(1+redshift)+1.1)
  and target_name='UGC12519'
group by califaid, xindex, yindex
having (max(flux)/avg(flux)>3)                                (6)

We group on pixel coordinates here as that's much more robust (and also somewhat faster) than going by the floating point ra/dec pairs. To turn the pixel coordinates to postitions you can do something with, again do a join with califadr3.spectra as in (4), except this time you turn the entire query so far into a subquery:

select raj2000, dej2000 from (
      select califaid, xindex, yindex
      from
      califadr3.fluxv500
      natural join califadr3.objects
      where (
      lambda between 6563*(1+redshift)-1.1 and 6563*(1+redshift)+1.1
      or lambda between 6540*(1+redshift)-1.1 and 6540*(1+redshift)+1.1
      or lambda between 6700*(1+redshift)-1.1 and 6700*(1+redshift)+1.1)
      and target_name='UGC12519'
      group by califaid, xindex, yindex
      having (max(flux)/avg(flux)>3)) as spots
  natural join califadr3.spectra

Finally, if you want to have all such "interesting" points in CALIFA, drop the constaint on the object name:

select raj2000, dej2000 from (
      select califaid, xindex, yindex
      from
      califadr3.fluxv500
      natural join califadr3.objects
      where (
      lambda between 6563*(1+redshift)-1.1 and 6563*(1+redshift)+1.1
      or lambda between 6540*(1+redshift)-1.1 and 6540*(1+redshift)+1.1
      or lambda between 6700*(1+redshift)-1.1 and 6700*(1+redshift)+1.1)
      group by califaid, xindex, yindex
      having (max(flux)/avg(flux)>3)) as spots
  natural join califadr3.spectra                           (8)

This is a fairly long-running query, which will time out on you on when you enter it through the "synchronous" TAP endpoint that TOPCAT uses by default (because it's simple and has little overhead). To use the "async" endpoint, uncheck "Synchronous" in TOPCAT's TAP dialog (or do the equivalent thing in another client). With this, you can turn off your computer, take it somewhere else, and resume operations when you get back; in this case, the job should be done in 20 minutes or so depending on server load and similar factors.

Once you have the data, try a few of the nice VO features you get. If you used TOPCAT to query, the result is in a table. With this, start Aladin, in TOPCAT, select Interop/Send Table To/Aladin and watch your matches in Aladin. Hit, e.g., "Optical" in Aladin, and you can zoom in on the "interesting" spots and see them overplotted on sky images.

You could now load the corresponding spectrum into a spectral analysis tool like, say Splat. To do that, in Aladin click on one point, go to the load dialog and there the "all VO" tab. Optionally, go to "Detailed List", hit "Uncheck all" and just check the "CALIFA Spectra" service (this is going to speed up your queries significantly).

Then start Splat, in the Aladin load dialog set the search radius to 0.01' (i.e., .6 arcsec) and submit. You should see both the V1200 and the V500 spectra -- right click on the one you want to see, select "Open with", "Splat", and work with your spectrum there.

If you don't want to get Splat, TOPCAT will do as well, although it has much less of built-in knowledge about spectra -- in that case, open TOPCAT's VO/SSA dialog, in the list of SSA services select "califa ssa", make sure "Accept Sky Positions" is checked, in "Diameter" again say something like 0.6 arcsec. If you hover over a point in Aladin, you'll get your positions filled in, and if you hit "Ok", the spectrum will be retrieved. If you, again, use the pushpin to make TOPCAT keep the window open, you have a quick way of downloading spectra that look interesting to you.

Overview

You can access this service using:

This service is published as follows:

local means it is listed on our front page, ivo_managed means it has a record in the VO registry.

Other services provided on the underlying data include:

Input Fields

The following fields are available to provide input to the service (with some renderers, some of these fields may be unavailable):

NameTable Head DescriptionUnitUCD
APERTURE Aperture Angular diameter of aperture deg instr.fov
BAND Band Wavelength (range) of interest (or symbolic bandpass names) m N/A
COLLECTION Collection IOVA id of the originating data collection N/A N/A
COMPRESS Compress? Return compressed results? N/A N/A
CREATORDID C. DID Dataset identifier assigned by the creator N/A meta.id
FLUXCALIB Calib Flux Type of flux calibration N/A N/A
FORMAT Type MIME type of the file served N/A N/A
MAXREC Match limit Maximum number of records returned. Pass 0 to retrieve service parameters. N/A N/A
MTIME Pub. Date Date last published. N/A N/A
POS Pos ICRS position of target object deg N/A
PUBDID P. DID Dataset identifier assigned by the publisher N/A N/A
REDSHIFT z Redshift of target object N/A src.redshift
REQUEST Request type This is queryData for the default operation; some services support getData as well N/A N/A
RESPONSEFORMAT Output Format File format requested for output. N/A meta.code.mime
RUNID Run id An identifier for a certain run. Opaque to the service N/A N/A
SIZE Size Size of the region of interest around POS deg N/A
SNR SNR Signal-to-noise ratio estimated for this dataset N/A stat.snr
SPATRES Res. Spc Spatial resolution of data deg pos.angResolution
SPECRP Spec. Res. Resolution on the spectral axis m spect.resolution;em.wl
TARGETCLASS 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
TARGETNAME Object Common name of object observed. N/A meta.id;src
TIME Date Obs. Midpoint of exposure N/A time.epoch
TOP #Best Only return the TOP "best" records (on this service, this usually is equivalent to MAXREC, so no ranking is implied). N/A N/A
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
WAVECALIB Calib. Spect. Type of wavelength calibration N/A meta.code.qual
WILDTARGET Name Pattern Shell pattern of target observed (case insensitive) N/A N/A
WILDTARGETCASE Name Pattern Shell pattern of target observed (case sensitive) N/A N/A

Default Output Fields

The following fields are contained in the output by default. More fields may be available for selection; these would be given below in the VOTable output fields.

NameTable Head DescriptionUnitUCD
accref Product key Access key for the data N/A meta.ref.url;meta.dataset
accsize File size Size of the data in bytes byte VOX:Image_FileSize
califaid Id CALIFA id number of the target. N/A meta.id
dej2000 Dec Declination of spectrum, ICRS deg pos.eq.dec;meta.main
embargo Embargo ends Date the data will become/became public a N/A
location_arr SSA Pos. Observed position RA and Dec as a 2-real array as required by SSAP. N/A pos.eq
location_dec Dec N/A deg pos.eq.dec;meta.main
location_ra RA N/A deg pos.eq.ra;meta.main
mime Type MIME type of the file served N/A N/A
owner Owner Owner of the data N/A N/A
preview Preview URL of a preview for the dataset, where available. N/A meta.ref.url;datalink.preview
raj2000 RA Right ascension of spectrum, ICRS deg pos.eq.ra;meta.main
ssa_aperture Aperture Angular diameter of aperture deg instr.fov
ssa_bandpass Bandpass Bandpass (i.e., rough spectral location) of this dataset; use something generic like 'Optical' here. N/A instr.bandpass
ssa_cdate Proc. Date Processing/Creation date N/A time;meta.dataset
ssa_creatorDID C. DID Dataset identifier assigned by the creator N/A meta.id
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_dateObs Date Obs. Midpoint of exposure d time.epoch
ssa_dstitle Title Title or the dataset (usually, spectrum) N/A meta.title;meta.dataset
ssa_length Length Number of points in the spectrum N/A N/A
ssa_location Location ICRS location of aperture center deg pos.eq
ssa_pdate Pub. Date Date last published. N/A N/A
ssa_pubDID P. DID Dataset identifier assigned by the publisher N/A N/A
ssa_redshift z Redshift of target object N/A src.redshift
ssa_score Score A measure of how closely the record matches your query. Higher numbers mean better matches. N/A N/A
ssa_snr SNR Signal-to-noise ratio at 500 nm (V500 spectra) or 400 nm (V1200 spectra) N/A stat.snr
ssa_specend Band end Upper value of spectral coordinate m em.wl;stat.max
ssa_specext Bandwidth Width of the spectrum m em.wl;instr.bandwidth
ssa_specmid Mid. Band Midpoint of region covered in this dataset m em.wl;instr.bandpass
ssa_specstart Band start Lower value of spectral coordinate m em.wl;stat.min
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_targetpos Obj. pos Equatorial (ICRS) position of the target object. N/A pos.eq;src
ssa_targname Object Common name of object observed. N/A meta.id;src
ssa_timeExt Exp. Time Exposure duration s time.duration
target_arr SSA Target Pos. Target RA and Dec as a 2-real array as required by SSAP. N/A pos.eq;src
xindex x X index in the CALIFA grid; V1200 indices are pixel+1000. N/A pos.cartesian.x
yindex y Y index in the CALIFA grid; V1200 indexes are pixel+1000 N/A pos.cartesian.y

VOTable Output Fields

The following fields are available in VOTable output. The verbosity level is a number intended to represent the relative importance of the field on a scale of 1 to 30. The services take a VERB argument. A field is included in the output if their verbosity level is less or equal VERB*10.

NameTable Head DescriptionUnitUCD Verb. Level
accref Product key Access key for the data N/A meta.ref.url;meta.dataset 1
ssa_location Location ICRS location of aperture center deg pos.eq 5
ssa_dateObs Date Obs. Midpoint of exposure d time.epoch 5
ssa_timeExt Exp. Time Exposure duration s time.duration 5
ssa_length Length Number of points in the spectrum N/A N/A 5
raj2000 RA Right ascension of spectrum, ICRS deg pos.eq.ra;meta.main 5
dej2000 Dec Declination of spectrum, ICRS deg pos.eq.dec;meta.main 5
accsize File size Size of the data in bytes byte VOX:Image_FileSize 11
ssa_score Score A measure of how closely the record matches your query. Higher numbers mean better matches. N/A N/A 15
location_ra RA N/A deg pos.eq.ra;meta.main 15
location_dec Dec N/A deg pos.eq.dec;meta.main 15
location_arr SSA Pos. Observed position RA and Dec as a 2-real array as required by SSAP. N/A pos.eq 15
target_arr SSA Target Pos. Target RA and Dec as a 2-real array as required by SSAP. N/A pos.eq;src 15
preview Preview URL of a preview for the dataset, where available. N/A meta.ref.url;datalink.preview 15
ssa_dstitle Title Title or the dataset (usually, spectrum) N/A meta.title;meta.dataset 15
ssa_creatorDID C. DID Dataset identifier assigned by the creator N/A meta.id 15
ssa_pubDID P. DID Dataset identifier assigned by the publisher N/A N/A 15
ssa_cdate Proc. Date Processing/Creation date N/A time;meta.dataset 15
ssa_pdate Pub. Date Date last published. N/A N/A 15
ssa_bandpass Bandpass Bandpass (i.e., rough spectral location) of this dataset; use something generic like 'Optical' here. N/A instr.bandpass 15
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 15
ssa_targname Object Common name of object observed. N/A meta.id;src 15
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 15
ssa_redshift z Redshift of target object N/A src.redshift 15
ssa_targetpos Obj. pos Equatorial (ICRS) position of the target object. N/A pos.eq;src 15
ssa_snr SNR Signal-to-noise ratio at 500 nm (V500 spectra) or 400 nm (V1200 spectra) N/A stat.snr 15
ssa_aperture Aperture Angular diameter of aperture deg instr.fov 15
ssa_specmid Mid. Band Midpoint of region covered in this dataset m em.wl;instr.bandpass 15
ssa_specext Bandwidth Width of the spectrum m em.wl;instr.bandwidth 15
ssa_specstart Band start Lower value of spectral coordinate m em.wl;stat.min 15
ssa_specend Band end Upper value of spectral coordinate m em.wl;stat.max 15
mime Type MIME type of the file served N/A N/A 20
yindex y Y index in the CALIFA grid; V1200 indexes are pixel+1000 N/A pos.cartesian.y 20
owner Owner Owner of the data N/A N/A 25
embargo Embargo ends Date the data will become/became public a N/A 25
califaid Id CALIFA id number of the target. N/A meta.id 30
xindex x X index in the CALIFA grid; V1200 indices are pixel+1000. N/A pos.cartesian.x 30

Copyright, License, Acknowledgements

CALIFA asks you to acknowledge:

"This study uses data provided by the Calar Alto Legacy Integral Field Area (CALIFA) survey (http://califa.caha.es/)."

"Based on observations collected at the Centro Astronómico Hispano Alemán (CAHA) at Calar Alto, operated jointly by the Max-Planck-Institut fűr Astronomie and the Instituto de Astrofísica de Andalucía (CSIC)."

and to cite both of :bibcode:2014A&A...569A...1W_ and :bibcode:2012A&A...538A...8S_

VOResource XML (that's something exclusively for VO nerds)