User:Jake Mokris: Difference between revisions
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Also, since what we're after in the data is the distance between peaks - i.e., the period - taking the Fourier transform of the data might be a good idea. But I haven't worked on that yet, and I don't know much about the actual implementation of a Fourier transform on a discrete data set (though I could tell you all about Schwartz space (which has nothing to do with ''Spaceballs'')). | Also, since what we're after in the data is the distance between peaks - i.e., the period - taking the Fourier transform of the data might be a good idea. But I haven't worked on that yet, and I don't know much about the actual implementation of a Fourier transform on a discrete data set (though I could tell you all about Schwartz space (which has nothing to do with ''Spaceballs'')). | ||
Finally, here's the link to | Finally, here's the link to [http://www.pha.jhu.edu/~c173_608/franck-hertz/root/Franck_Hertz.C Petar's Franck-Hertz macro] from 2005. | ||
Revision as of 06:50, 20 February 2011
I plan on writing a set of user-friendly classes that use ROOT to conduct the data analysis required in the experiments. Links to the macros are forthcoming... for now, here's the base program: media: bla.txt. Obviously you'll want to change the extension to .C; apparently the Wiki doesn't let us upload .C files. I'm teaching myself C++ as I do this, so I imagine my program could be written a bit better. I'll try to comment as much as I can so that what the program is doing makes sense.
I finished writing a program to fit the Franck-Hertz data; here it is: Media:Franck_Hertz_Analysis.txt. Again, change the extension to .C before running the program. I explain how it works in the comments before the code, so here I'll say what the result was: The fit worked better than I expected; however, as the program fits the data to gaussians, the peaks are a small distance from the actual peaks in the data - which is where the energy levels are. So really, the fit is inherently flawed: it doesn't give a good value for the location of the peaks. A fit to skewed gaussians (perhaps to a lognormal distribution) would work better.
Also, since what we're after in the data is the distance between peaks - i.e., the period - taking the Fourier transform of the data might be a good idea. But I haven't worked on that yet, and I don't know much about the actual implementation of a Fourier transform on a discrete data set (though I could tell you all about Schwartz space (which has nothing to do with Spaceballs)).
Finally, here's the link to Petar's Franck-Hertz macro from 2005.
FIRST WITCH
When shall we three meet again In thunder, lightning, or in rain?
LADY MACBETH
O, never Shall sun that morrow see! Your face, my thane, is as a book where men May read strange matters.
MACBETH
Who can be wise, amazed, temperate and furious, Loyal and neutral, in a moment?
MACBETH
How now, you secret, black, and midnight hags! What is't you do?
ALL
A deed without a name.
MACBETH
Thou comest to use thy tongue; thy story quickly.
MESSENGER
Gracious my lord, I should report that which I say I saw, But know not how to do it.