Extragalactic 1

Tutors: Evanthia HATZIMINAOGLOU, Paolo PADOVANI

Participants

Dubinovska (Linux), Heraudeau (Mac OS X), Marchetti (Linux), Nikolajuk (Linux), Olivares (Windows), Perez-Torres (Mac OS X), Suhada (Mac OS X), Toribio (Linux), Tremou (Linux), Tundo (Linux)

At the beginning of each exercise, launch all the tools that you will be using and make sure they "see" each other.

tip: always launch TOPCAT from the command line as follows:

java -Xmx512m -jar topcat-full.jar -disk

If you haven't installed the jar file, you can grab it from here

Use Case 1

Evanthia Hatziminaoglou

Confirming a supernova candidate, from the AIDA WP5 use cases (uses Aladin, TOPCAT)

• tip: launch Aladin first, then TOPCAT (if you want to know why, ask a tutor!)
• load the local image (ngc6946.fit) taken by the Col Druscie Remote Observatory Supernovae Search (CROSS) programme
• to make the image clearer, modify the pixel distribution ("pixel" button, 3rd from the bottom, vertical tool bar, right next to the display window -> sqrt)
• the image has no astrometric calibration; the calibration can be done from within Aladin
  • select a calibrated image either from the Aladin Image Server (e.g. POSSII) or from allVO, (e.g. 2MASS; do not select large images!)
  • select a reference catalogue from the Catalogue Servers (e.e. 2MASS, USNO)
  • place both images (calibrated and non-calibrated) side by side by splitting the display window in two panels (click on the corresponding option at the bottom left of the display window)
  • select properties right-clicking on the (non-calibrated) image plane
  • in the Astrometric Reduction section select New and select by matching stars
  • activate the cells under "x y" position (by clicking on them) and click on 3 or 4 stars on the uncalibrated image; then select the corresponding stars on the calibrated image after activating the cells under hh mm ss +dd mm ss and then click Create
• the local image is now calibrated and can be superposed on the POSSII (or other) image, in order to identify the Supernova: change the transparency of the POSSII image by dragging the purple bar to the right OR associate the two images (this can be done by clicking on the "assoc" icon, 6th from the bottom, vertical tool bar, right next to the display window)
• for the most courageous: if you have selected 2MASS as a reference image, you can try to identify the supernova by running SExtractor on the 2MASS image (Load -> SExtractor, select the 2MASS image in image reference) and overplot the resulting catalogue on the local image on which you are trying to identify the supernova; tip:the object is outside the bulk of the galaxy and it has not been extracted on the 2MASS image!
• "tag" the supernova
• further steps:
  • select other images taken in other wavebands and different epochs
  • measure the distance from the centre of the galaxy, by clicking on the "dist" icon, 4th from the top of the vertical tool bar: then click on the centre of the galaxy and without releasing the mouse button, drag the pointer all the way to the supernova; the distance is displayed on the main window
  • check for other SNe in the same galaxy:
    • load Simbad from the Server Selector, apply no filter
    • filter the new Simbad plane, advanced mode and define: $[src.class]="SN" {draw red square} (the SNe will appear in red); Apply and/or Export; a new plane with the filtered source has now been created
    • clicking on either of the object, the available information will appear in tabular form at the bottom of the Aladin window, linking directly to the Simbad query results on your browser - try it
    • OR search for SNe in VizieR (and other, using the allVO button) catalogues
  • send the Simbad plane to TOPCAT and create the SN sub-sample as follows:
    • click on Display row subset -> Define new subset using algebraic expression as equals(OTYPE,"SN")
    • OR (if you don't know the syntax for the algebraic expression) display the column metadata; highlight the OTYPE column; rank the table based on the selected column by clicking on one of the yellow arrows at the top of the column metadata window; display the table; select the rows with OTYPE=SN; define a new sub-set including the selected rows only by clicking on the upper left button of the display table window
  • look for e.g. X-ray (or other wavelengths) counterparts: in TOPCAT: Load -> DataSources ->Cone Search
  • in the "Keywords" field type your constraints (e.g. x-rays, radio, gamma, supernovae) and select the resources to be queried
  • put the objects name (NGC 6946) in the "Object Name" field and query
  • cross-correlate the resulting catalogues with the one(s) already loaded in TOPCAT, send them to Aladin, check them against the images, improvise!
• other things to try with Aladin:
  • draw contours on any of the image
  • activate the Simbad automatic pointer (from the "Tools" menu), place the pointer on any object of the image
  • try to create an rgb image from three images of your choice

Use Case 2

Based on the case presented by M. Perez-Torres

Search for ULX sources and X-ray binaries in nearby (e.g. D<10 Mpc) galaxies (uses TOPCAT, Aladin).

ULXs (Ultra-Luminous X-ray sources) are X-ray sources that are less luminous than AGN but more luminous than any known stellar process (Lx > 10^39 erg/sec)

• tip: launch Aladin first, then TOPCAT; launch TOPCAT with a larger memory buffer; try java -Xmx512M -jar topcat-full.jar
• load the NED-1D galaxy catalogue (a .csv (coma-separated values) version of the catalogue can be found here: NED-1D.csv)
• the RA and Dec are in sexadecimals; convert RA, Dec to decimal: select Table Columns and then Add new sky coordinate column based on existing one; get rid of the multiple entries using the option match one
• optional: apply a filter in distance (e.g. D<10 Mpc) using TOPCAT (the stricter the criterion, the smaller the number of objects!) and send the filtered nearby galaxies catalogue to Aladin
• this catalogue does not contain any information about the size of the objets; load the hyperLeda catalogue in Aladin [(VII/237) from All VizieR] (this might take a while as it contains about a million objects; place the cursor on the plane as it loads to get an idea of the number of objects still to be loaded); cross-match the two catalogues and send the match back to TOPCAT; add new column with radius in arcmin: pow(10.,$diameter_column)*0.1/2
• you can now delete the hyperLEDA plane in order to save memory; then load the 2XMMi catalogue (0.2-12 keV band) in Aladin (IX/40), which gives the calibrated fluxes for sources; send it to TOPCAT and cross-correlate (match two; "Sky with Errors"; "1&2"; "All Matches") the 2XMMi with the nearby galaxies catalogue using the new radius and the X-ray position uncertainty (ePOS) as errors
• add new column with the luminosity Lx for the point like sources from the calibrated flux and distance to each galaxy, i.e. Lx = 4*pi*D^2*fx = (do the math!) 50.078+2*log10($distance_column)+log10($fx_column)
• filter those sources with Lx >= 1e39 erg/s (our ULX candidates)
• plot Lx vs cross-correlation separation: most objects are at very low offsets, therefore X-ray emission most probably comes from the nucleus; some objects are clearly off; keep those above a given separation which you can select based on the separation distribution
• send the catalogue to Aladin keeping only the X-ray coordinates
• cross-match with X-ray binaries table(s) to find the non-matches
• cross-match with quasars and/or AGN catalogue(s)
• find images of the galaxies, plot the positions of the AGN and ULX candidates; verify their separation as well as from the galaxy centre
• find existing ULX catalogues to confirm candidates

Use Case 3

Evanthia Hatziminaoglou

Find quasar candidates in the Lockman field, ELAIS N2 or ELAIS S1 (uses VODesktop, TOPCAT, VOSED, VOSpec, Aladin)

1. tip:launch VODesktop first, then Aladin, TOPCAT, and all the other VO tools
2. New Smart List ->Any main field contains SDSS; Create
3. select e.g. the SDSS photometric catalogue, release 6; Query with Astroscope (10:45:00, +58:00:00, try up to 0.4 degrees radius; or 16:36:48,+41:01:45 or 16:11:00, +55:00:00) -> Search
4. Note: you can make the same query using TOPCAT: Load -> DataSources -> Keyword: SDSS DR6, using the same coordinates and search radius
5. send table to TOPCAT; select quasar candidates based on their morphology (cl=6) and u-g vs g-r colours (quasars have a UV excess)
6. create the observed SEDs of the selected quasar candidates using VOSED
7. if the number of your candidates is small, you can try the Single Object Search; unmark the Spectroscopic data; select 2MASS and SDSS from the Photometric Data, select a small search radius (typically 1-2") and Submit query
8. you can then Display SED; this will launch a new window of VOSpec; click on the list at the bottom right of the main VOSpec window and Retrieve
9. compare the observed SED to models SEDs from e.g. the Kurucz library (just click Query and select the Theoretical list of SSAs)
10. UVX quasars have similar colours to O and B stars; select models with Teff>10000K; logg 4.0; metallicity of 0.0 (example values) and overplot the model SEDs; scale model and observed SEDs and compare
11. in case the list of candidates is long select the Multi Object Search (VOSED main window) and repeat the previous steps; the results will come in a .zip file that will contain an xml file per object; you can visualise the individual SEDs by loading them one by one in VOSpec and compare with the pre-selected Kurucz models
12. once you decide on the the quasar candidates, create the correct subsample in TOPCAT and send the table to Aladin; in Aladin, query VizieR for a catalogue of known quasars in the fields (e.g. J/MNRAS/386/1252/qsos) and cross-correlate the two to find out if 1) the quasar candidates are indeed quasars and 2) how complete the selection criteria were

Variant:

• define the colour selection criteria based on a known quasar catalogue (e.g. download the SDSS DR3 or DR5 quasar catalogues using VODesktop and send it to TOPCAT); check their position on the u-g vs g-r diagram, also as a function of redshift (add a third column on the TOPCAT scatter plot); quasars of redshift typically less than 2.3 have a UV excess
• now query the SDSS DR6 photometric catalogue (again using VODesktop) in a random region of the sky (suggested regions: 242.8, 54.25; 163.0, 57.50; 158.4, 57.75; radius up to 0.4deg)
• select only point sources
• from the colour cuts previously established, select quasar candidates based on their UV excess (or other colours, depending on the redshift)
• check for X-ray counterparts (e.g. 2XMMi catalogue)
• use VOSED to plot the SEDs of the candidates (follow steps 6-10 of the first variant)

Use Case 4

Evanthia Hatziminaoglou

Mining the ESO archive using VirGO (uses VirGO, Aladin, SPLAT, TOPCAT)

List of suggested fields, with lots of data, that will allow you to fully explore the capabilities of the tool:

• 30 doradus
• ELAIS ES1 (00h35m00s -43d30m00s)
• XMM-LSS (02h21m00s -04d30m00s)
• CDFS (03h21m00s -28d16m00s); everybody's favourite, try to avoid too large queries!!
• or query around your own favourite field or object - remember VirGO "talks" to the ESO archive, do not select fields or objects in the northern hemisphere!

• Familiarise yourself with the tool; it is a complex interface; to trigger a query:
  • chose the Target Selection tab
  • specify a Simbad resolvable name or coordinates and press Go!
  • click on the "Download Observations from the SIA/SSA" button at the bottom of the screen (or press CTRL+E)

• depending on the field you will find raw and/or reduced images and spectra; some raw WFI also have previews
• launch Aladin, SPLAT, TOPCAT; send selected images to Aladin; visualise reduced spectra with SPLAT, save the list of selected frames as a VOTable and send it to TOPCAT

Use Case 5

Daria Dubinovska

Search for AGNs with X-Ray counterparts in the CDFS

1. create a catalogue of x-ray sources in the chandra deep field south
2. create a catalogue of optically selected sources in several bands
3. crosscorelate two catalogues to identify sources with x-ray counterpart. that will be a catalogue of active and starburst galaxies + x-ray binaries
4. within the catalog of optically selected sources make a selection of AGNs via the color selection method (for example color-color diagrams U-B vs B-V, R-J vs J-K and so on)
5. check where the x-ray selected sources are on this diagram
6. find all available spectra for x-ray selected sources to be able to test how successful was the approach 1)-5)

Use Case 6

Philippe Heraudeau

Derive luminosity function and Star Formation Rate estimates for galaxies in Virgo

1. Select galaxies from the Virgo Cluster in the SDSS and 2MASS
2. Derive number counts and the luminosity function for the different bands
3. Compare to theory prediction
4. Look for galaxies with H_alpha emission and derive SFRs
5. Cross-match with UV, radio and far-infrared surveys
6. Estimate SFRs from the different bands and compare these numbers

Comments, suggestions, problems, etc.

Please list here any comments, suggestions, or problems that you might have had, on the VO tools used. -

Maybe would be nice to have a set of cases covering all VO-tools at the beginning of the school (1st day), extragalactic and galactic groups separately, just to have an overview of what we could include in our science cases. Cheers and thanks for all the teaching, Felipe Olivares.

The same science cases which show how to do things in different ways would be very useful e.g. with topcat + aladin and then with python scripting and aladin scripting. What are the "best", fastest ways for my project?

An introductory talk on "How to add your own data to the VO' would be very welcome since it will be more and more common that astronomers have to do that in the future as the last step of the "data processing" and I think that students would understant better what is is about (VO data, registry, metadata...).

Many thanks to the organizers and the tutors for a very useful workshop, Philippe Heraudeau.

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-- PaoloPadovani - 02 Mar 2009