On the bottom of the page there are two rows of six locations within HEASARC to which you can go. The top left option is the W3Browse location where you can search for observations of various objects.
Scroll down the page to the section entitled EXOSAT ME Spectra and Lightcurves (HEASARC_ME) and click on the gray button to the left of the line of the observation with a quality flag (qflag_me) of 4.
The quality flag number corresponds to how good each observation is. 0 is unusable, 1 is very poor, 2 is poor, 3 is acceptable, 4 is very good and 5 is excellent.
Argon 1-15keV Spectrum (FITS, 10 kbytes) s05865.pha.Z
Argon 1-15keV Response Matrix (FITS, 43 kbytes) s05865.rsp.Z
0.8-8.9keV Lightcurve (FITS, 6 kbytes) d05853.lc.Z
0.8-8.9keV Lightcurve (FITS, 6 kbytes) d05865.lc.Z
by clicking on the gray button to the left of the corresponding line.
If you had to re-enter your directory then when you finished typing click on Cancel, then Click on Download TAR file again. This time the correct directory should appear in the Selection box.
Netscape will copy the files you have selected into your directory in the form of a w3browse-.tar file. It is a compressed file and cannot be used until it is opened up properly.
tar -vxf w3browse-.tar
This command produced subdirectory chains in your directory called me/rates/d/ and me/spectra/ where youre files are located.
cd me/rates/d/
d05853.lc.Z d05865.lc.Z should appear.
Notice the files end with .Z. This means they are comrpessed further and still cannot be used.
uncompress *.Z
The * is a wildcard character so that your command above says ``uncompress anything in this directory that ends with .Z''.
Then type ls. The .Z should have disappeared from the filenames making the files usable.
Then change into the me/spectra/ directory and uncompress those files.
rm w3browse-.tar
emacs d05853.lc
The file that comes up contains information such as the date and time of this observation, the telescope and instrument that collected the data, the location of the object as well as its name.
Close emacs.
Go to the me/rates/d/ directory and type lcurve < Enter >
Then enter 1 when asked for the number of time series.
Type: /XW <enter> for the plot device (this is your screen name).
The lightcurve will now be displayed! To proceed further, you need to move the plot off of the xterm window so you can enter more commands. So drag the graph by the header to a convenient place on the screen.
d05853.flc
d05865.flc
Note that the INPUT files to list.con are the .flc files!! Now, when you run lcurve you enter @list.con in place of the filename you used previously. Your other parameters will also change, because you are now dealing with 900+ bins instead of 400+. Then, you can execute powspec on the summed data.
Type cpd /xw < Enter > (change plotting device).
If you type plot ? < Enter > you will get a list off all the things besides your data that you can plot.
It is a good idea, after every data manipulating command that you enter, to plot data < Enter > so that you may see what you have done.
Type ignore 60-** which tell Xspec to ignore the channels 60 and above. The same result can be acheived with the command ignore 60-100.
Plot the data again.
We will attempt to fit our data to three spectral models:
This model represents a spectrum that arises from a source whose radiating electrons are moving within a magnetic field and therefore experience a force perpendicular to their motion. This torque accelerates the electrons and causes them to radiate in a characteristic way. The spectrum produced by this effect has the mathematical form of a powerlaw where the intensity of the radiation energy is proportional to the energy raised to a power.
I(E)=AE
Where:
is a spectral index, and
A is a constant.
A blackbody spectrum is one that is only dependent on the temperature of the radiating source. This model assumes that the radiating photons get their energy solely from the temperature of the object.
I(E)=2E/hc(e -1)
Where:
h is Planck's constant, and
c is speed of light.
This radiation spectrum is caused by the thermal motions of electrons in gasses hot enough to be ionized. The presence of charges from the ions exert electromagnetic forces on the electrons that 'bend' their motion and cause them to radiate. The distribution of the energy emitted from such 'bending' depends on the densities of both electrons and ions as well as the temperature of the gas, and it has the form:
A(E)=CG(E,T) Znn(kT)e
Where:
C is a constant, G(E,T) is a function that varies with temperature and energy, Z is the charge of positive ions in the gas, n and n are electron density and positive ion density, respectively, and T is the temperature.
Be sure to record your results to compare with the results from the ROSAT data.
You will receive a list of parameters that this particular model requires. These parameters are default and we can change them to fit our data with the fit command later. We will accept the default values by pressing < Enter > three times.
The output that follows includes a (Chi-Squared) and a reduced (the original divided by the number of degrees of freedom). If the reduced is near 1 then the fit should be good. The null hypothesis probability is the probability of getting a value of as large or larger than observed if the model is correct. If this probability is small then the model is not a good fit.
Your fit should be very bad. This is because the model is constructed using the initial default values that do not correspond to your data. Notice that the null hypothesis probability is 0 and that the reduced is tens of thousands large. Both of these facts indicate a poor fit.
Type fit < Enter > and after ten iterations, when prompted to continue fitting type y < Enter >.
The model does converge to the data though not exactly. To see where the model departs from the data type plot data residuals < Enter >. At the bottom of the screen, the model is represented by the straight line and the data oscillates above and below. It is only toward the higher energies that the residuals shrink and stop oscillating.
The results in our output shows a reduced around 8. The null hypothesis probability is zero. These results are consistent with the plot since most of the data points do not intersect with the fitted model. This indicates that our model is not good enough to describe this source very well.
In the table (your results may not exactly match but should be close):
--------------------------------------------------------------------------- --------------------------------------------------------------------------- mo = phabs[1]( powerlaw[2] ) Model Fit Model Component Parameter Unit Value par par comp 1 1 1 phabs nH 10^22 23.21 +/- 0.6166 2 2 2 powerlaw PhoIndex 1.106 +/- 0.3817E-01 3 3 2 powerlaw norm 3.2135E-02 +/- 0.2802E-02 --------------------------------------------------------------------------- ---------------------------------------------------------------------------You should make a note of the parameter values that achieved the best fit. This output claims that the column density (nH) for this source is about 2.3210 and the Photon Index is 1.106.
Again this is not a good fit and is around 50 million!
renorm < Enter > and plot data to scale down the model.
The reduced seems to be the same implying an unimproved fit. It seems to be the peak of the curve that won't conform to either model. What is useful from this model is that we can extract a temperature (in units of keV) from the output. With a kT of 3.081 (or close to that) the temperature is around 3.610 Kelvin.
(with k=8.610 keV K).
The column density of the blackbody analysis is smaller 1.3410 but is of the same order of magnitude.
The results give a similar reduced 8.5 and a column density of 2.5510 which is consistent in order of magnitude with the other two models. From this we can conclude that the column density for GK PER is on the order of 10.
The interesting part of this analysis is the extracted kT temperature from the bremsstrahlung fit is 200.0keV or 2.4410. Two orders of magnitude greater than the blackbody temperature!!! (This is probably an error in the running of the Xspec algorithm)