Difference: ClaudiaTang (6 vs. 7)

Revision 72022-07-08 - ClaudiaTang

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  7/7/22: Found out that for the most part, amplitude is just guessed and varied manually until a good fit is found. I used xspec to extract the absorbed and unabsorbed flux values from the data after being fit to a normal con*pow*tbabs model and used one of Sarah's old correction codes to approximate the data before absorption in order to fit the PowerLaw to the data. For some reason, some points had very high flux errors, so assuming that it was just bad data where background was close to dominating/dominated, I removed those data points so I could at least fit the SED to the majority of the points. Earlier in the day I was also playing around with a normal PowerLaw and seeing how the shape would change as different parameters varied. Found out that most likely, a powerlaw by itself would not fit the data as the magnetic field required to match the synchrotron component was below 1 microgauss which is unfeasible as it's below the ISM, so I will have to try applying different broken powerlaw models most likely. The goal is to try to get a good model fit sometime tomorrow or Monday. I also want to check to make sure that the methodology used to convert the .dat files to ecsv files was correct (since I just used the one's Sarah had done for the other telescopes).
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7/8/22: I did more fitting today with the SED for the power law specifically. Most of my time went into trying to do the XMM data extraction properly because a lot of the data had really bad error. Realized that the correction I was doing was incorrect because I was refitting after setting nH to 0 (to represent the unabsorbed flux) which changes the parameters and therefore makes the correction method ineffective and I also learned that when using wdata to extract the binned data from the spectrum, the "NO NO NO NO NO" represented the dividing line between MOS1 and MOS2 data. As I didn't account for this in what I did yesterday, I had to redo the process and replot the data. Next I plan to try to apply the exponential power law model and then learn to use MCMC to check whether a model fits the data well.
 

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