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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@ (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.
        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 

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.


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@ (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.

         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

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 or set host to NDADSA; the user name is XRAY) or request the users' manual from the HEASARC.

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