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This Legacy journal article was published in Volume 2, November 1992, and has not been
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The Legacy Journal
Club
Using the HEASARC for Research:
An Example
Charles Day (Astro-D GOF)
The ages of data in the HEASARC archives range from one year, in the case of
ROSAT observations, to 13 years in the case of Vela 5B. In most cases, the
data have been examined and published by the original PI, but this does not
mean they are "dead." Far from it. Archival research can often yield important
new results. Moreover, since archival data are "mature," those calibration
problems which cropped up when the data were new have been ironed out and
documented. An additional advantage which the HEASARC offers to archival
researchers is convenient electronic access to the data, the calibrations and
the documentation.
What sort of research projects can be carried out profitably on archival data?
Firstly, there are those projects based on large samples. For instance, it is
nearly always the case that the full sample of objects in a given class
observed by a mission did not originate in a single proposal but in the
aggregate of several different proposals. The archival researcher, interested,
say, in all the old dwarf novae observed by EXOSAT, can simply acquire all the
data in one go without having to forge collaborative alliances with other
investigators. Of course, the proprietary period of the data has to expire,
but the trend of recent missions (ROSAT, Astro-D, XTE) has been for data to
become generally available after only a year. Exemplifying this sort of
project, Grandi et al. (1992) used archival EXOSAT data to compile a
survey of AGN variability from short (minutes) to long (months). At total of
161 observations of 30 AGN were used to show that nearly all the hard X-ray
selected AGN in the Piccinotti sample vary.
Another sort of archival research project is to analyze old data with the
benefit of hindsight gained either from a new theory or from a new observation.
Apart from simply confirming (or refuting) the new theory, the reanalysis of
old data can extend it, if, say, the source was in a different state. The
presence in AGN X-ray spectra of a soft "excess" was discovered in EXOSAT data
by Arnaud et al. (1985, MNRAS, 217, 105). This component
was later sought in a reanalysis of archival Einstein SSS data by Turner et
al. (1991, Ap.J., 371, 85) who found it in just under half
the 25 sources they surveyed. This investigation led Turner et al. to
propose a new explanation - a blend of low energy lines - for the excess.
Finally, an excellent reason to look at archival data is simply for the sake of
it. The original PI often had a very specific project in mind when he or she
wrote the proposal that led to the data. An archival researcher, on the other
hand, not looking for the same things, nor prejudiced in the same way as the
original PI, can make discoveries the PI missed. D. White et al. (1991,
MNRAS, 253, 72) acting on a hunch from a Ginga observation of A478
(Johnstone et al. 1992, MNRAS, 255, 431), reexamined the Einstein
SSS spectra of galaxy clusters and discovered large amounts of intrinsic cold
material.
Aspects of all three sorts of archival research are present in a project I am
currently working on. Ray White of the University of Alabama (the PI), Isamu
Hatsukade of Miyazaki University and I submitted a proposal last year to the
NASA Ginga Visiting Investigator Program to analyze Ginga data from cooling
flow clusters in conjunction with Einstein SSS data in the HEASARC archives.
Our sample is all the clusters observed both by the Ginga LAC and the Einstein
SSS, and the motivation behind the project was to use the Ginga data to
constrain cooling flow models in the SSS domain by performing joint spectral
fits. Quite unexpectedly, we discovered that the cooling flows in some of the
clusters in our sample have metal abundances significantly higher than in the
hot outer part of the cluster. The paper containing this result will be
submitted soon.
Following is exactly how we used the HEASARC to help write the proposal and to
acquire the archival data.
Once we had the idea to perform joint SSS and LAC fits, the first step was to
identify which clusters had spectra from the two instruments. The Ginga sample
was included in the call for proposals; to get the SSS sample, we used BROWSE,
the HEASARC's interactive database interrogation program. Our BROWSE sessions
are reproduced below. What is entered at the keyboard is given in bold face;
comments are given in italics.
HEASARC> browse Starts up browse from DCL.
BROWSE 4.1v: 8-SEP-92 00:01:44 Address=cday@155.148.3.71 (XRAY)
Session initialization, please wait
Database name: sss Specifies the Einstein SSS database.
Typing ? gives the full list of available databases.
For further information type HELP, DBHELP and/or KEYWORDS (to end use EXIT)
Current equinox year: 1950
Plot device not defined, use cpd command
Loading SSS database sample TOTAL indexed on DEC
Einstein SSS database
****************************************************************************
NOTE: The source names in this database are upper case,
and have blanks included (e.g., AR LAC).
****************************************************************************
SSS_TOTAL_DEC > lind Lists the indices through which
the database entries may be accessed and sorted.
For sample TOTAL the following indexes are available:
Index Distinct Nsample Type Date
------------------------------------------------------------
> DEC 290 634 SYS 21-MAY-92
RA 279 634 SYS 21-MAY-92
SEQUENCE NUMBER 260 634 SYS 21-MAY-92
TIME 634 634 SYS 21-MAY-92
EXPOSURE TIME 132 634 SYS 21-MAY-92
NAME 213 634 SYS 21-MAY-92
COUNT RATE 537 634 SYS 21-MAY-92
CLASS 41 634 SYS 21-MAY-92
Of the indexed parameters listed above, the one which will sort out the
cluster observations from the rest is class. In BROWSE, astronomical objects
are given a four-digit class code. Clusters occupy class codes 5000 to
5999.
SSS_TOTAL_DEC > sparm class 5000 5999 The sparm command searches
the indexed parameter class for all
the entries corresponding to clusters.
81
Name Seq Time Expos Count Ice Del ice RA(1950) DEC(1950)
(#) (yy.dd) (s) (rate) (hh mm ) (o '")
------------+-----+-------+-----+-------+----+-------+--------+-------+--------
1 SC 1329-314 3631 79.221 7864 0.09 0.51 0.51 13 29 23 31 25 48
2 VIRGO CLUSTE 1415 79.173 7536 0.38 1.13 0.02 12 27 49 12 42 22
3 VIRGO CLUSTE 1419 78.345 4505 0.25 1.87 0.01 12 27 22 12 44 44
4 VIRGO CLUSTE 1415 78.345 5816 0.61 0.30 2.70 12 27 49 12 42 22
. . . . . . . . . . . . . .
. . . . . . . . . . . . . .
. . . . . . . . . . . . . .
80 NGC 1129 3429 79.050 4915 0.35 1.78 0.01 02 51 35 41 22 48
81 NGC 1275 1402 79.042 10895 3.23 1.82 0.03 03 16 29 41 19 51
81 entries retrieved
SSS_TOTAL_CLA 81>
The prompt gives information on the current sample, e.g., showing that
the total SSS sample has been indexed by class and reduced to a subsample of
81.
After the proposal was accepted and the Ginga data were in hand, we again used
BROWSE to extract the spectra:
SSS_TOTAL_CLA 81> xp/sp This command extracts the spectral, response,
background and correction files from the data
base and writes them to a scratch disk.
Enter start entry number [d/f=1]: 1
Enter end entry number [d/f=81]: 1
For this example, only the first entry is extracted.
Extracting spectrum: 0.5-4.5 keV >> OBSERVER:[CDAY]ssc1329.pha
Creating response and/or background files using VIMAT
OBSERVER:[CDAY]SSC1329.PHA;1 epoch=586.024 : time= 864s : ice= 0.545
epoch=586.038 : time= 608s : ice= 0.573
epoch=586.093 : time= 1056s : ice= 0.662
epoch=586.162 : time= 1280s : ice= 0.722
epoch=586.227 : time= 1312s : ice= 0.765
totalc-goodc = 1.020000
Writing background file: SSC1329.BCK
Writing background correction file: SSC1329.COR
Writing response file: SSC1329.RSP
Odd-even effect applied to response
5 observations : mean_epoch = 586.13 : mean_ice = 0.67
SSS_TOTAL_CLA 81> exit Leave BROWSE after extracting the files.
HEASARC> dir Check the location of the extracted files.
Directory OBSERVER:[CDAY]
SSC1329.BCK;2 SSC1329.COR;2 SSC1329.PHA;1 SSC1329.RSP;2
Total of 4 files.
HEASARC>
Although it is possible to set to work straight away fitting the extracted
spectrum, it is a good idea to learn about the properties of the instrument
beforehand. Our source of information about SSS analysis was Steve Drake's
article in the first issue of Legacy. The article explains how to use
XSPEC to fit the spectra and is recommended to investigators interested in
fitting SSS spectra.
Another use BROWSE was put to was to consult other databases, such as the Abell
catalog or the ROSAT observation log, for background information:
HEASARC> browse
BROWSE 4.1v: 8-SEP-92 00:26:22 Address=cday@155.148.3.71 (XRAY)
Session initialization, please wait
Database name: abell
For further information type HELP, DBHELP and/or KEYWORDS (to end use EXIT)
Current equinox year: 1950
Plot device not defined, use cpd command
Loading ABELL database sample TOTAL indexed on DEC
Catalog: Abell Clusters
ABELL_TOTAL_DEC > sn abell496
The command sn is equivalent to sparm name and is used here to find the
entry in the Abell catalog corresponding to the cooling flow cluster Abell
496.
1
Name RA(1950) DEC(1950 Count BMType Redshift Rich Dist Vmag
(hh mm ) (o ' )
------------+--------+--------+-----+--------+--------+----+----+---
1 ABELL496 04 31 18 -13 21 0 50 I: 0.032 1 3 15.3
ABELL_TOTAL_NAM 1>
For more information about this SSS-Ginga cluster project, please refer to
White, Day, Hatsukade & Hughes (University of Alabama preprint). For more
information about BROWSE, you can login to HEASARC and use the on-line help
files (telnet to ndadsa.gsfc.nasa.gov or set host to NDADSA; the user name is
XRAY) or request the users' manual from the HEASARC.
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