Last modified by rangeadm on 2025/04/23 16:13

From version 3.1
edited by sendels
on 2019/08/23 08:24
Change comment: There is no comment for this version
To version 8.1
edited by sndueste
on 2020/07/06 16:59
Change comment: There is no comment for this version

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1 -XWiki.sendels
1 +XWiki.sndueste
Content
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1 -Here you can find a small python script (by (% class="twikiNewLink" %)[[MartinB>>url:http://hasfweb.desy.de/bin/edit/Setup/MartinB?topicparent=Setup.PartialCoherenceSimulation;nowysiwyg=0||rel="nofollow" shape="rect"]](%%)) implementing the partial coherence methode as described in Thomas Pfeifer, Yuhai Jiang, Stefan Düsterer, Robert Moshammer, and Joachim Ullrich, Partial-coherence method to model experimental free-electron laser pulse statistics, Opt. Lett. 35, 3441-3443 (2010); [[link to the paper>>url:http://dx.doi.org/10.1364/OL.35.003441||shape="rect"]]
2 -\\\\Simulations like this:
1 +In order to simulate the temporal and spectral distribution of SASE pulses there is an easy way based random fluctuations filtered spectraly and temporally.
3 3  
4 -[[image:attach:partia__coherence2.png]]
3 +The only input parameters are the spectral bandwidth and the pulse duration.
5 5  
5 +Here you can find a small python script (by (% class="twikiNewLink" %)MartinB(%%)) implementing the partial coherence methode as described in Thomas Pfeifer et al. //Partial-coherence method to model experimental free-electron laser pulse statistics,// Opt. Lett. 35, 3441-3443 (2010); [[link to the paper>>url:http://dx.doi.org/10.1364/OL.35.003441||shape="rect"]]
6 +
7 +The pulse shapes in time AND corresponding spectral dstribution can be easily created with:
8 +
9 +* (((
10 +a python script
11 +
12 +{{expand title="Click here to expand the script ..."}}
13 +import numpy as np
14 +import matplotlib.pyplot as plt
15 +
16 +def GetSASE(CentralEnergy, dE_FWHM, dt_FWHM, samples=0, Axis=True):
17 +h=4.135667662 #in eV*fs
18 +dE=dE_FWHM/2.355 #in eV, converts to sigma
19 +dt=dt_FWHM/2.355 #in fs, converts to sigma
20 +if samples == 0:
21 +samples=int(400.*dt*CentralEnergy/h)
22 +else:
23 +if (samples < 400.*dt*CentralEnergy/h):
24 +print("Number of samples is a little small, proceeding anyway. Got", samples, "prefer more than",400.*dt*CentralEnergy/h)
25 +
26 +EnAxis=np.linspace(0.,20.*CentralEnergy,num=samples)
27 +EnInput=np.zeros(samples, dtype=np.complex64)
28 +EnInput=np.exp(-(EnAxis-CentralEnergy)~*~*2/2./dE~*~*2+2*np.pi*1j*np.random.random(size=samples))
29 +En_FFT=np.fft.fft(EnInput)
30 +TAxis=np.fft.fftfreq(samples,d=(20.*CentralEnergy)/samples)*h
31 +TOutput=np.exp(-TAxis~*~*2/2./dt~*~*2)*En_FFT
32 +EnOutput=np.fft.ifft(TOutput)
33 +if (Axis):
34 +return EnAxis, EnOutput, TAxis, TOutput
35 +else:
36 +return EnOutput, TOutput
37 +
6 6  \\
7 7  
40 +# set the main parameters here:
41 +CentralEnergy=80. # in eV
42 +bandwidth=0.5 # bandwidth in %
43 +dt_FWHM=30. # FWHM of the temporal duration on average
44 +
45 +dE_FWHM=CentralEnergy/100 *bandwidth # calculate bandwidth of the spectrum in eV
46 +
47 +# calculate 3 SASE pulses
48 +EnAxis, EnOutput, TAxis, TOutput = GetSASE(CentralEnergy=CentralEnergy, dE_FWHM=dE_FWHM, dt_FWHM=dt_FWHM)
49 +EnAxis2, EnOutput2, TAxis2, TOutput2 = GetSASE(CentralEnergy=CentralEnergy, dE_FWHM=dE_FWHM, dt_FWHM=dt_FWHM)
50 +EnAxis3, EnOutput3, TAxis3, TOutput3 = GetSASE(CentralEnergy=CentralEnergy, dE_FWHM=dE_FWHM, dt_FWHM=dt_FWHM)
51 +
52 +
53 +# plot spectrum
54 +ax1 = plt.subplot(1, 2, 1)
55 +plt.plot(EnAxis,np.absolute(EnOutput),EnAxis2,np.absolute(EnOutput2),EnAxis3,np.absolute(EnOutput3) )
56 +plt.xlim(CentralEnergy-2.*dE_FWHM,CentralEnergy+2.*dE_FWHM)
57 +plt.title('Average pulse duration: %.1f fs' % dt_FWHM )
58 +ax1.set_xlabel('Photon energy in eV')
59 +ax1.set_ylabel('spectral intensity')
60 +
61 +# plot time structure
62 +ax1 =plt.subplot(1, 2, 2)
63 +plt.plot(TAxis,np.absolute(TOutput),TAxis2,np.absolute(TOutput2), TAxis3,np.absolute(TOutput3))
64 +plt.xlim(-2.*dt_FWHM,+2.*dt_FWHM)
65 +ax1.set_xlabel('time in fs')
66 +ax1.set_ylabel('pulse amplitude')
67 +
68 +plt.show()
69 +{{/expand}}
70 +)))
71 +* a Jupyter Notebook** [[attach:GenerateSASE.ipynb]] **
72 +
73 +
74 +Some examples of results:
75 +
8 8  \\
9 9  
78 +[[image:attach:partia__coherence2.png]] or: [[image:attach:image2020-2-5_15-14-4.png||width="480"]]
10 10  
11 -
12 -\\can be easily created with the script ( the script can be downloaded in the attachment table below):
80 +\\
13 13  
14 14  \\
15 15  
... ... @@ -19,10 +19,12 @@
19 19  
20 20  \\
21 21  
22 -[[image:attach:partia__coherence1.png]]
90 +\\
23 23  
24 24  \\
25 25  
26 -[[attach:SASEPulseGenV2.ipynb]]
94 +\\
27 27  
28 -Jupyter Notebook
96 +\\
97 +
98 +\\