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Last modified by rangeadm on 2025/04/23 16:13
From version 9.1
edited by sndueste
on 2020/07/07 16:55
Change comment: There is no comment for this version
To version 7.1
edited by sndueste
on 2020/07/03 11:25
Change comment: There is no comment for this version

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... ... @@ -1,15 +1,11 @@
1 -In order to simulate the temporal and spectral distribution of SASE pulses there is an easy way based random fluctuations filtered spectrally and temporally.
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.
2 2  
3 -The only input parameters are the center wavelength, spectral bandwidth and the pulse duration.
3 +The only input parameters are the spectral bandwidth and the pulse duration.
4 4  
5 -Here you can find a small python script (by (% class="twikiNewLink" %)MartinB(%%)) implementing the partial coherence method as described in:
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 6  
7 -* **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"]]
7 +The pulse shapes in time AND corresponding spectral dstribution can be easily created with:
8 8  
9 -\\
10 -
11 -The pulse shapes in time AND corresponding spectral distribution can be easily created with:
12 -
13 13  * (((
14 14  a python script
15 15  
... ... @@ -29,6 +29,7 @@
29 29  
30 30  EnAxis=np.linspace(0.,20.*CentralEnergy,num=samples)
31 31  EnInput=np.zeros(samples, dtype=np.complex64)
28 +#for i in range(samples):
32 32  EnInput=np.exp(-(EnAxis-CentralEnergy)~*~*2/2./dE~*~*2+2*np.pi*1j*np.random.random(size=samples))
33 33  En_FFT=np.fft.fft(EnInput)
34 34  TAxis=np.fft.fftfreq(samples,d=(20.*CentralEnergy)/samples)*h
... ... @@ -72,28 +72,19 @@
72 72  plt.show()
73 73  {{/expand}}
74 74  )))
75 -* or the same as a Jupyter Notebook** [[attach:GenerateSASE.ipynb]] **
72 +* a Jupyter Notebook** [[attach:GenerateSASE.ipynb]] **
76 76  
77 -==
78 -Some examples: ==
79 79  
80 -//CentralEnergy=80 # in eV//
75 +Some examples of results:
81 81  
82 -//bandwidth=0.5 # bandwidth in %//
77 +\\
83 83  
84 -//dt_FWHM=10, 30., 70  # FWHM of the temporal duration on average//
79 +[[image:attach:partia__coherence2.png]] or: [[image:attach:image2020-2-5_15-14-4.png||width="480"]]
85 85  
81 +\\
86 86  
87 -
88 -
89 - [[image:attach:2020-07-07 16_51_14-Window.png||height="250"]]
90 -
91 91  \\
92 92  
93 -[[image:attach:2020-07-07 16_53_22-Window.png||height="250"]]
94 -
95 -[[image:attach:2020-07-07 16_52_27-Window.png||height="250"]]
96 -
97 97  \\
98 98  
99 99  \\