analistica/slides/sections/2.md

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# Landau distribution
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## Landau PDF
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:::: {.columns align=center}
::: {.column width=50%}
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$$
L(x) = \frac{1}{\pi} \int \limits_{0}^{+ \infty}
dt \, e^{-t \ln(t) -xt} \sin (\pi t)
$$
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![](images/landau-pdf.pdf)
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. . .
\begin{center}
No closed form for \alert{ANYTHING}
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\end{center}
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## Landau median
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- The median of $f$ is defined by
$$
F(m) = \int_{-\infty}^m fdx = \frac{1}{2}
$$
- Equivalently
$$
m = F^{-1}\left(\frac{1}{2}\right)
$$
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- PDF Numerical integration up to $1/2$ or QDF is needed
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![](images/median.pdf)
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## Landau median
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- CDF computed by numerical integration
- Mean computed by numerical root-finding
$$
F(x) = \frac{1}{2} \thus m_L\ex = 1.3557804...
$$
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\setbeamercovered{}
\begin{center}
\begin{tikzpicture}[overlay]
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\pause
\node [opacity=0.5, xscale=0.35, yscale=0.25 ] at (2.4,0.95) {\includegraphics{images/high.png}};
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\end{tikzpicture}
\end{center}
\setbeamercovered{transparent}
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## Landau mode
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- Maximum $\hence \partial_x L(\mu) = 0$
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. . .
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\vspace{20pt}
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- Computed by numerical minimization (Brent)
\setbeamercovered{}
\begin{center}
\begin{tikzpicture}[remember picture]
\node at (0,0) (here) {$\mu_L\ex = 0.22278...$};
\pause
\node [opacity=0.5, xscale=0.65, yscale=0.5 ] at (here)
{\includegraphics{images/high.png}};
\end{tikzpicture}
\end{center}
\setbeamercovered{transparent}
::::
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![](images/mode.pdf)
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## Landau FWHM
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$$
\text{FWHM} = w = x_+ - x_-
$$
$$
L(x_{\pm}) = \frac{L_{\text{max}}}{2} = \frac{L(\mu_L)}{2}
$$
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. . .
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\vspace{20pt}
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- Computed by numerical root finding (Brent)
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\setbeamercovered{}
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\begin{center}
\begin{tikzpicture}[remember picture]
\node at (-1,0) (here) {$w_L\ex = 4.018645...$};
\pause
\node [opacity=0.5, xscale=0.65, yscale=0.5 ] at (here)
{\includegraphics{images/high.png}};
\end{tikzpicture}
\end{center}
\setbeamercovered{transparent}
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![](images/fwhm.pdf)
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