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Appendix A

Generalized exponential brightness distributions and conversion factors

Assuming circular symmetry, we define a generalized exponential bulge as a surface brightness distribution:
\begin{displaymath}
I(r) = I_0 ~\exp \left[-\left(\frac{r}{r_0}\right)^{1/n}\right]\end{displaymath} (A 1)

where r is the projected radius, I0 the central brightness, r0 the exponential folding length, and n an integer index ($n\geq1$). With the change of variable xn=r/r0, it is easily seen that the total luminosity L is:


\begin{displaymath}
L = \int_{0}^{\infty}I(r)~2 \pi r~{\rm d}r = \pi (2n)!~I_0 r_0^2.\end{displaymath} (A 2)
It is customary to introduce instead of r0 an effective radius $r_{\rm e}$,which encircles half of the luminosity, and instead of I0 an effective brightness $I_{\rm e} = I(r_{\rm e})$. We derive in the following the relations between these quantities in the case of a generalized exponential.

The relation defining $r_{\rm e}$ is:


\begin{displaymath}
\int_{0}^{r_{\rm e}}I(r)~2 \pi r~{\rm d}r = \frac{L}{2}~~ ;\end{displaymath} (A 3)

with the above mentioned change of variable, this integral yields:


\begin{displaymath}
{\rm e}^{-\alpha_n} \sum_{i=0}^{2n-1} \frac 
{\alpha_n^{2n-1...
 ...~~ 
\alpha_n=\left(\frac{r_{\rm e}}{r_0}\right)^{\frac{1}{n}}, \end{displaymath} (A 4)

which we write as:

 
 \begin{displaymath}
{\rm e}^{-\alpha_n} \sum_{i=0}^{m} \frac {\alpha_n^{i}}{i!} = 
\frac{1}{2}\hspace{1.5cm}{\rm with}~~~~m=2n-1.\end{displaymath} (A 5)

The left hand side of this last equation is a cumulative Poisson distribution with parameter $\alpha_n$. This can be written in terms of $\chi^{2}$ probability functions (Abramowitz & Stegun 1971):


\begin{displaymath}
{\rm e}^{-\alpha_n} \sum_{i=0}^{m} \frac {\alpha_n^{i}}{i!} = Q(\chi^2\vert~\nu)\, , \end{displaymath} (A 6)
with $\chi^2=2 \alpha_n$ and $\nu=2(m+1)=4n$.

$\alpha_n$ is therefore easily evaluated from $\chi^{2}$ tables. In any case, for large $\nu$ values, $(\chi^2/\nu)^{1/3}$ is

approximately normally distributed:


\begin{displaymath}
Q\left(\chi^2\vert~\nu\right) \simeq Q(x_2)\, ,\end{displaymath} (A 7)

\begin{displaymath}
{\rm with} \hspace{0.5cm}x_2=\frac{\left(\frac{\chi^2}{\nu}\...
 ...}{3}}
-\left(1-\frac{2}{9\nu}\right)}{\sqrt{\frac{2}{9\nu}}}\,.\end{displaymath} (A 8)

Since in our case $Q(x_2)=\frac{1}{2}$, it follows x2=0 and $\chi^2\simeq\nu(1-\frac{2}{3\nu})$. Then, with the approximations adopted:

 
 \begin{displaymath}
\alpha_n\simeq 2n-\frac{1}{3} , ~~~~~~~{\rm or}~~~~~~~r_{\rm e}\simeq r_0 
\left( 2n-\frac{1}{3}\right)^n
.\end{displaymath} (A 9)
It turns out that the approximation is already quite good for n = 1, with a relative error of 0.7%. Table A1 reports the solution of Eq. (A5) and its approximation with Eq. (A9) for various values of n.

For the effective surface brightness we have:
\begin{displaymath}
I_{\rm e} = I(r_{\rm e})=I_0~\exp\left[-\left(\frac{r_{\rm e}}{r_0}\right)^{\frac{1}{n}}\right] \end{displaymath} (A 10)

\begin{displaymath}
=I_0~{\rm e}^{-\alpha_n}\simeq I_0~\exp~\left(-2n+\frac{1}{3}\right)\, .\end{displaymath}

These results are easily generalized to elliptical distributions and they are found to hold in the same form if $r_{\rm e}$ is the major semiaxis of the ellipse encircling half luminosity.

  
Table 5: $r_{\rm e}$ approximation

\begin{tabular}
{rrrr}
\noalign{\smallskip}
\hline 
\noalign{\smallskip}
$n$\spa...
 ...1.6667 \
10 & 40 & 19.6677 & 19.6667 \
\noalign{\smallskip}
\hline \end{tabular}


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