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Last modified: 30 November 2017

URL: http://cxc.harvard.edu/csc/quick/flux.html

What is the flux of a source in Release 2.0 of the Chandra Source Catalog?


Until the full CSC 2.0 release, expected in February 2018, the results from any search of the Current Database should be considered provisional, since not all the data is available and final statistical checks have not yet been made. The processing status page is regularly updated to indicate the current status.

There are a number of flux measurements included in CSC 2.0, at the master-source level - e.g. aperture photometry, model-energy fluxes, and fluxes from spectral fits - as well as at the stack and observation level. Each type can be measured in two apertures (aper and aper90). For the following example, the broad and wide band master fluxes - namely flux_aper_b and flux_aper_w - will be searched for.

There are two approaches for searching CSC 2.0 described below: using the CSCview application or by writing an ADQL query.


CSCview

The CSCview application provides a quick way to search the catalog by location. A brief run-through of the steps required is provided here, and the CSCview help pages can be read for more information. The following requires that CSCview has been downloaded, Java is installed, and that cscview.jar is in the current working directory (Mac OS users can download a DMG which provides a CSCview application).

  1. Start CSCview with:

    unix% java -jar cscview.jar

    or, for Java 9 users:

    unix% java --add-modules java.se.ee -jar cscview.jar
  2. Select the "Current Database" on the Catalog tab, and then select the Search icon just below the File menu.

    The Query should be selected, a number of "windows" have appeared, and the title changed to "Chandra Source Catalog: Current Database".

  3. A position search can be started by selecting the "Cone" radio button which appears below the label "Position Search:" in the middle of the window. When selected, the area to the right will change to allow a search by name or coordinates. Select the "By Coordinates" button and change from Equatorial to Galactic if necessary. Insert the location - Equatorial coordinates can be given as decimal degrees or in sexagesimal notation - and change the search radius as desired.

    Other searches are possible. For example, if you know the name of the source in CSC 2.0 from the pre-release table then this can be used as a filter by searching for name in the Source Properties area, dragging the entry into the Search Criteria entry, and then adding the name into the newly-created text area.

  4. Once the locaiton has been entered, selecting the Search icon will start the query. The tab will change to the "Results" tab, with a status message displayed at the bottom of the window. The message "Search completed" indicates that the query has finished, and the results will appear in the main area of the GUI. An empty result does not mean that the source is not part of CSC 2.0, as discussed in the coverage section of the "how do I find my source" guide.

  5. The default query in CSCview includes both the broad and wide flux_aper values, along with other basic properties (name and location).

    The source list can be downloaded, or data products for one or more sources can be selected at this stage. The CSCview help documentation can be read for more information on these capabilities.


An ADQL query

The ADQL interface to the catalog can be used. In the following example the curl command-line tool will be used, but any method that can make a HTTP request with parameters can be used. The ADQL command-line interface pages provide more information on the capabilities and syntax of this interface.

The ADQL query used in this example uses a 5 arcsecond search radius (0.083 arcminutes) in the WHERE clause to limit the search around a Right Ascension of 138.9683 degrees and Declination of 29.557 degrees. The columns returned are limited to the angular separation from this position, master-source name, master-source significance, and the broad- and wide- band aperture fluxes.

SELECT DISTINCT top 10 dbo.separation(m.ra, m.dec, 138.9683, 29.557)
as separation, m.name, m.significance, m.flux_aper_b, m.flux_aper_lolim_b, m.flux_aper_hilim_b, m.flux_aper_w, m.flux_aper_lolim_w, m.flux_aper_hilim_w
FROM master_source m
WHERE (dbo.cone_distance(m.ra, m.dec, 138.9683, 29.557) <= 0.083)
ORDER BY separation ASC

However, it must all be one one line otherwise the following call will fail. An example is the file flux.adql, which is "evaluated" using the following call:

unix% curl --form version=cur --form query=@flux.adql http://cda.cfa.harvard.edu/csccli/getProperties
#Column	separation	(E9.6)		(.separation)	[""]	[]
#Column	name	(A22)	Source name in the format '2CXO Jhhmmss.s{+|-}ddmmss[X]'(master_source.name)	[""]	[]
#Column	significance	(F9.2)	Highest flux significance (S/N) across all stacked observations and energy bands	(master_source.significance)	[""]	[]
#Column	flux_aper_b	(E9.3)	Aperture-corrected net energy flux inferred from the source region aperture, best estimate derived from the longest block of a multi-band, flux-ordered Bayesian Block analysis of the contributing observations, and calculated by counting X-ray events; ACIS broad (0.5-7.0 keV) energy band(master_source.flux_aper_b)	["erg/s/cm^2"]	[]
#Column	flux_aper_lolim_b	(E9.3)	Aperture-corrected net energy flux inferred from the source region aperture, best estimate derived from the longest block of a multi-band, flux-ordered Bayesian Block analysis of the contributing observations, and calculated by counting X-ray events (68% lower confidence limit); ACIS broad (0.5-7.0 keV) energy band	(master_source.flux_aper_lolim_b)	["erg/s/cm^2"]	[]
#Column	flux_aper_hilim_b	(E9.3)	Aperture-corrected net energy flux inferred from the source region aperture, best estimate derived from the longest block of a multi-band, flux-ordered Bayesian Block analysis of the contributing observations, and calculated by counting X-ray events (68% upper confidence limit); ACIS broad (0.5-7.0 keV) energy band	(master_source.flux_aper_hilim_b)	["erg/s/cm^2"]	[]
#Column	flux_aper_w	(E9.3)	Aperture-corrected net energy flux inferred from the source region aperture, best estimate derived from the longest block of a multi-band, flux-ordered Bayesian Block analysis of the contributing observations, and calculated by counting X-ray events; HRC wide (~0.1-10.0 keV) energy band(master_source.flux_aper_w)	["erg/s/cm^2"]	[]
#Column	flux_aper_lolim_w	(E9.3)	Aperture-corrected net energy flux inferred from the source region aperture, best estimate derived from the longest block of a multi-band, flux-ordered Bayesian Block analysis of the contributing observations, and calculated by counting X-ray events (68% lower confidence limit); HRC wide (~0.1-10.0 keV) energy band	(master_source.flux_aper_lolim_w)	["erg/s/cm^2"]	[]
#Column	flux_aper_hilim_w	(E9.3)	Aperture-corrected net energy flux inferred from the source region aperture, best estimate derived from the longest block of a multi-band, flux-ordered Bayesian Block analysis of the contributing observations, and calculated by counting X-ray events (68% upper confidence limit); HRC wide (~0.1-10.0 keV) energy band	(master_source.flux_aper_hilim_w)	["erg/s/cm^2"]	[]
separation	name	significance	flux_aper_b	flux_aper_lolim_b	flux_aper_hilim_b	flux_aper_w	flux_aper_lolim_w	flux_aper_hilim_w
1.361043e+00	 2CXO J091552.3+293323	    54.79	1.339e-12	1.310e-12	1.369e-12	         	         	         

The results are - by default - written out in as an ASCII column format, where the columns are tab separated. If written to a file - e.g. flux.tsv - rather than displayed on screen, the CIAO Data Model can be used to process the output. For example:

unix% dmlist "flux.tsv[opt kernel=text/tsv]" cols
 
--------------------------------------------------------------------------------
Columns for Table Block flux.tsv
--------------------------------------------------------------------------------
 
ColNo  Name                 Unit        Type             Range
   1   separation                        Real4          -Inf:+Inf            
   2   name                              String[22]                          Source name in the format '2CXO Jhhmmss.s{+|-}ddmmss[X]'
   3   significance                      Real4          -Inf:+Inf            Highest flux significance (S/N) across all stacked observations and energy bands
   4   flux_aper_b          erg/s/cm^2   Real4          -Inf:+Inf            Aperture-corrected net energy flux inferred from the source region aperture, bes
   5   flux_aper_lolim_b    erg/s/cm^2   Real4          -Inf:+Inf            Aperture-corrected net energy flux inferred from the source region aperture, bes
   6   flux_aper_hilim_b    erg/s/cm^2   Real4          -Inf:+Inf            Aperture-corrected net energy flux inferred from the source region aperture, bes
   7   flux_aper_w          erg/s/cm^2   Real4          -Inf:+Inf            Aperture-corrected net energy flux inferred from the source region aperture, bes
   8   flux_aper_lolim_w    erg/s/cm^2   Real4          -Inf:+Inf            Aperture-corrected net energy flux inferred from the source region aperture, bes
   9   flux_aper_hilim_w    erg/s/cm^2   Real4          -Inf:+Inf            Aperture-corrected net energy flux inferred from the source region aperture, bes

These queries can also be made from Python; for example (using the six module included with CIAO to support both Python 2.7 and 3.5 users). In this example the ADQL query is read from an extrnal file but it can also be created directly in Python.

>>> from six.moves.urllib import parse, request
>>> qry = open(flux.adql', 'r').read().strip()
>>> data = parse.urlencode({'version': 'cur', 'query': qry})
>>> req = request.urlopen("http://cda.cfa.harvard.edu/csccli/getProperties", data)
>>> answer = req.read()
>>> print(answer)
#Column	separation	(E9.6)		(.separation)	[""]	[]
#Column	name	(A22)	Source name in the format '2CXO Jhhmmss.s{+|-}ddmmss[X]'(master_source.name)	[""]	[]
#Column	significance	(F9.2)	Highest flux significance (S/N) across all stacked observations and energy bands	(master_source.significance)	[""]	[]
#Column	flux_aper_b	(E9.3)	Aperture-corrected net energy flux inferred from the source region aperture, best estimate derived from the longest block of a multi-band, flux-ordered Bayesian Block analysis of the contributing observations, and calculated by counting X-ray events; ACIS broad (0.5-7.0 keV) energy band(master_source.flux_aper_b)	["erg/s/cm^2"]	[]
#Column	flux_aper_lolim_b	(E9.3)	Aperture-corrected net energy flux inferred from the source region aperture, best estimate derived from the longest block of a multi-band, flux-ordered Bayesian Block analysis of the contributing observations, and calculated by counting X-ray events (68% lower confidence limit); ACIS broad (0.5-7.0 keV) energy band	(master_source.flux_aper_lolim_b)	["erg/s/cm^2"]	[]
#Column	flux_aper_hilim_b	(E9.3)	Aperture-corrected net energy flux inferred from the source region aperture, best estimate derived from the longest block of a multi-band, flux-ordered Bayesian Block analysis of the contributing observations, and calculated by counting X-ray events (68% upper confidence limit); ACIS broad (0.5-7.0 keV) energy band	(master_source.flux_aper_hilim_b)	["erg/s/cm^2"]	[]
#Column	flux_aper_w	(E9.3)	Aperture-corrected net energy flux inferred from the source region aperture, best estimate derived from the longest block of a multi-band, flux-ordered Bayesian Block analysis of the contributing observations, and calculated by counting X-ray events; HRC wide (~0.1-10.0 keV) energy band(master_source.flux_aper_w)	["erg/s/cm^2"]	[]
#Column	flux_aper_lolim_w	(E9.3)	Aperture-corrected net energy flux inferred from the source region aperture, best estimate derived from the longest block of a multi-band, flux-ordered Bayesian Block analysis of the contributing observations, and calculated by counting X-ray events (68% lower confidence limit); HRC wide (~0.1-10.0 keV) energy band	(master_source.flux_aper_lolim_w)	["erg/s/cm^2"]	[]
#Column	flux_aper_hilim_w	(E9.3)	Aperture-corrected net energy flux inferred from the source region aperture, best estimate derived from the longest block of a multi-band, flux-ordered Bayesian Block analysis of the contributing observations, and calculated by counting X-ray events (68% upper confidence limit); HRC wide (~0.1-10.0 keV) energy band	(master_source.flux_aper_hilim_w)	["erg/s/cm^2"]	[]
separation	name	significance	flux_aper_b	flux_aper_lolim_b	flux_aper_hilim_b	flux_aper_w	flux_aper_lolim_w	flux_aper_hilim_w
1.361043e+00	 2CXO J091552.3+293323	    54.79	1.339e-12	1.310e-12	1.369e-12	         	         	         
Changing the ADQL query

The command-line interface page describes in more detail the functionality available (e.g. how to change output format) and more information on ADQL. One easy way to create a new query is to use CSCview to set up the query but to then use the Query sub-menu from the View menu, which displays the ADQL form of the query. This can be copied, or saved to a file, for use with the command-line interface.


Last modified: 30 November 2017
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The Chandra X-Ray Center (CXC) is operated for NASA by the Smithsonian Astrophysical Observatory. 60 Garden Street, Cambridge, MA 02138 USA.   Email:   cxchelp@head.cfa.harvard.edu Smithsonian Institution, Copyright © 1998-2017. All rights reserved.