home.md

 # 1.Process     
 ## (1) Adjust amplitude   
-  BBH waveform generated from Bilby can't tell the distance. We adjust its amplitude the same to Korean waveform's, then we can infer BBH waveform's distance(since we know all information of Korean waveform).   
+   For GW and its source, we have:   
+
+```math
+  distance×amplitude=constant  
+```
+
+BBH waveform generated from Bilby can't tell the distance. We can adjust its amplitude the same to Korean waveform's, then infer its distance.   
 ## (2) Make injection   
 ## (3) Plot the Amplitude Spectral Density (ASD)  
 Plotting these data in the Fourier domain gives us an idea of the frequency content of the data. A way to visualize the frequency content of the data is to plot the amplitude spectral density, ASD. The ASDs are the square root of the power spectral densities (PSDs), which are averages of the square of the fast fourier transforms (FFTs) of the data. They are an estimate of the "strain-equivalent noise" of the detectors versus frequency, which limit the ability of the detectors to identify GW signals.   
@@ -52,7 +58,25 @@ The resulting time series no longer has an amplitude between the order of magnit
    
 In terms of the machine learning side of things, the whitening is primarily done to normalise the data for input to the neural network. So long as you give the network signals with similar noise properties and priors as those it was trained on, it should function properly.    
 
-## (5)window...?
+## (5)Generate BBH waveform by Bilby  
+To generate BBH waveform, We first establish a dictionary of waveform parameters that includes masses of the two black holes, spins of both black holes (a, tilt, phi), etc. The waveform will finally be input to VItamin, therefore we set the value of each parameter as the median of its prior's range, which is given to train VItamin.   
+```  
+parameters = dict( mass_1=57.5, mass_2=57.5, a_1=0., a_2=0., tilt_1=0., tilt_2=0., phi_12=0., phi_jl=0.,   
+        luminosity_distance=2000, theta_jn=3.141592653589793/2, psi=3.141592653589793/2, phase=6.283185307179586/2,    
+        geocent_time=0.25, ra=6.283185307179586/2, dec=0.)   
+``` 
+Then We create a waveform generator using the Binary Black Hole source model.  
+``` 
+waveform_generator = bilby.gw.WaveformGenerator( duration=duration, sampling_frequency=sampling_frequency,   
+        frequency_domain_source_model=bilby.gw.source.lal_binary_black_hole,   
+        parameter_conversion=bilby.gw.conversion.convert_to_lal_binary_black_hole_parameters,    
+        waveform_arguments=waveform_arguments)
+``` 
+Finally Bilby will give us BBH waveform.  
+![BBH_waveform](uploads/232ddb941eace9135bd5e09765724208/BBH_waveform.png)   
+In the plot, h_cross looks like a straight line, but it s correct. This is because h_cross has a very small amplitude(~$`10^-39`$) due to those angles's value.
+
+## (5)Window...?
 an overlap and a window to minimizes "spectral leakage" 
 
 
@@ -82,7 +106,9 @@ https://gilsay.physics.gla.ac.uk/gitlab/wei.changfeng/weichangfeng_project/blob/
  https://gilsay.physics.gla.ac.uk/gitlab/wei.changfeng/weichangfeng_project/blob/master/plot_waveform.ipynb  
 ## (4)Whiten signal  
 
-https://gilsay.physics.gla.ac.uk/gitlab/wei.changfeng/weichangfeng_project/blob/master/whiten_signal.ipynb  
+https://gilsay.physics.gla.ac.uk/gitlab/wei.changfeng/weichangfeng_project/blob/master/whiten_signal.ipynb   
+## (5)Generate BBH waveform  
+https://gilsay.physics.gla.ac.uk/gitlab/wei.changfeng/weichangfeng_project/blob/master/generate_bbh_waveform.ipynb
   
 # 4.Issue  
 ## 
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