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The black histograms in the plots are the data and the red curves are the best fit to the data using the multi-Poisson model described in a preceeding section, with two modifications.
 
The black histograms in the plots are the data and the red curves are the best fit to the data using the multi-Poisson model described in a preceeding section, with two modifications.
 
* The Gaussian smearing of the individual pixel pulse-height distribution was replaced with the following function that has an asymmetric tail.
 
* The Gaussian smearing of the individual pixel pulse-height distribution was replaced with the following function that has an asymmetric tail.
<p align="right"><math>
+
{|
f(x;\alpha,\beta,\sigma) = \beta\frac{\alpha}{2}\,e^{\alpha x+\frac{\alpha^2\sigma^2}{2}}\left[1-Erf\left(\frac{x+\alpha\sigma^2}{\sqrt{2}\sigma}\right)\right] </math><br>
+
|<math>
<math> + \frac{1-\beta}{\sqrt{2\pi}\sigma}e^{-\frac{x^2}{2\sigma^2}}
+
f(x;\alpha,\beta,\sigma)||=||\beta\frac{\alpha}{2}\,e^{\alpha x+\frac{\alpha^2\sigma^2}{2}}\left[1-Erf\left(\frac{x+\alpha\sigma^2}{\sqrt{2}\sigma}\right)\right] </math>
</math></p>
+
|-
 +
|&nbsp;||&nbsp;||<math> + \frac{1-\beta}{\sqrt{2\pi}\sigma}e^{-\frac{x^2}{2\sigma^2}}
 +
</math>
 +
|}
 
: This function is normalized to unity and is described by two parameters:
 
: This function is normalized to unity and is described by two parameters:
  

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