\(\renewcommand\AA{\unicode{x212B}}\)
IkedaCarpenterConvoluted¶
Description¶
This function is an Ikeda-Carpenter function convolved with a tophat function and a Gaussian function. The Ikeda-Carpenter function is given by:
\[V =  Scale \times \Big\{ (1-R)(\alpha t')^2 e^{-\alpha t'} + 2R\frac{\alpha^2 \beta}{(\alpha-\beta)^3} \times
\big[ e^{-\beta t'} - e^{-\alpha t'}  (1 + (\alpha - \beta)t' + \frac{1}{2}(\alpha-\beta)^2t'^2) \big]    \Big\}\]
This is convolved with a tophat function (of width hatWidth) and a Gaussian function \(exp(-k_{conv} t^2)\).
There are no attributes for this function.
Properties (fitting parameters)¶
| Name | Default | Description | 
|---|---|---|
| A | 0.0 | |
| B | 0.0 | |
| R | 0.0 | |
| T0 | 0.0 | |
| Scale | 0.0 | |
| HatWidth | 0.0 | |
| KConv | 0.0 | 
See Ikeda, S. & Carpenter, J.M. (1985). Nuclear Instruments and Methods in Physics Research Section A 239, 536-544 for additional details on parameters
Usage¶
Here is an example of generating an Ikeda-Carpenter function:
 1import numpy as np
 2import matplotlib.pyplot as plt
 3fICC = IkedaCarpenterConvoluted()
 4fICC['scale'] = 1.0
 5fICC['A'] = 0.1
 6fICC['B'] = 1.e-2
 7fICC['R'] = 0.3
 8fICC['T0'] = 27000.
 9fICC['hatWidth'] = 0.5
10fICC['k_conv'] = 120.
11
12x = np.linspace(26000, 28000,100)
13y = fICC(x)
14plt.plot(x,y)
Categories: FitFunctions | General
Source¶
Python: ICConvoluted.py