$\begin{figure} \center \epsfig{file=9880f01a.eps,height=3.7cm,width=5.9cm,clip}\... ...5.9cm,clip}\epsfig{file=9880f01c.eps,height=3.7cm,width=5.9cm,clip} \end{figure}$ Figure 1: Distribution of the $\chi ^2$ values from the Minkowski Gaussianity analysis for the Archeops 143K03-143K04 map at $N_{\rm side}=32$ , $N_{\rm side}=64$ , and $N_{\rm side}=128$ . The vertical lines show data, the histograms are obtained from a set of 10³ simulations, and the solid lines are the expected $\chi ^2$ distributions for $3n_{\rm th}$ degrees of freedom.
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In the text

$\begin{figure} \center \epsfig{file=9880f02a.eps,height=3.7cm,width=5.9cm,clip}... ...5.9cm,clip}\epsfig{file=9880f02c.eps,height=3.7cm,width=5.9cm,clip} \end{figure}$ Figure 2: Distribution of the $\chi ^2$ values from the Minkowski Gaussianity analysis for the Archeops 143K03 noise map at $N_{\rm side}=32$ , $N_{\rm side}=64$ , and $N_{\rm side}=128$ . Vertical lines show data, the histograms corresponds to sets of 10³ noise simulations, and the solid lines are the $\chi ^2$ distribution with $3n_{\rm th}$ degrees of freedom.
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In the text

$\begin{figure} \par\epsfig{file=9880f03a.eps,height=3.7cm,width=5.9cm,clip}\epsf... ...5.9cm,clip}\epsfig{file=9880f03c.eps,height=3.7cm,width=5.9cm,clip} \end{figure}$ Figure 3: From left to right, $\chi ^2$ statistic of the 143K03 noise map, its cumulative probability, and the fraction of available area for different values of the minimum number of hits at $N_{\rm side}=128$ . This map becomes compatible with Gaussianity when the minimum number of hits is approximately 90.
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In the text

$\begin{figure} \center \epsfig{file=9880f04a.eps,height=3.5cm,width=5.83cm,clip... ...83cm,clip}\epsfig{file=9880f04i.eps,height=3.5cm,width=5.83cm,clip} \end{figure}$ Figure 4: From left to right, and from top to bottom, the area, contour length, and genus of the data (asterisk *) as a function of threshold for the 143K03 maps with $N_{\rm side}=32$ , $N_{\rm side}=64$ , and $N_{\rm side}=128$ . We also plot the acceptance intervals for the 68% (inner in red), the 95% (middle in green), and 99% (outer in magenta) significance levels given by 10 000 Gaussian simulations of signal and noise.
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In the text

$\begin{figure} \center \epsfig{file=9880f05a.eps,height=3.7cm,width=5.9cm}\epsf... ...psfig{file=9880f05e.eps,height=3.7cm,width=5.9cm}\hspace*{2.95cm}}\end{figure}$ Figure 5: From left to right, and from top to bottom, the Gaussianity analysis of Archeops data maps at resolutions: $N_{\rm side}=32$ , $N_{\rm side}=64$ , $N_{\rm side}=128$ , the combinations $N_{\rm side}=32,64$ , and the combinations $N_{\rm side}=32,64,128$ . The histograms correspond to the $\chi ^2$ of 2000 Gaussian simulations, the vertical lines are the $\chi ^2$ of the data and the solid lines are the expected $\chi ^2$ distribution with $3N_{\rm th}$ degrees of freedom.
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In the text

$\begin{figure} \center \epsfig{file=9880f06a.eps,height=4.5cm,width=8cm}\epsfig{file=9880f06b.eps,height=4.5cm,width=8cm} \end{figure}$ Figure 6: From left to right, $\chi ^2(f_{\rm nl})$ of Archeops data vs. $f_{\rm nl}$ and the best fit value of $f_{\rm nl}$ for a set of 2000 Archeops Gaussian simulations ( s_k03+n_k03) combining the maps at resolutions $N_{\rm side}=32,64,128$ .
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In the text

$\begin{figure} \center \epsfig{file=9880f07a.eps,height=4.5cm,width=8cm}\epsfig{file=9880f07b.eps,height=4.5cm,width=8cm} \end{figure}$ Figure 7: From left to right, the non-Gaussian part of a full sky CMB simulation at low resolution ( $N_{\rm side}=16$ ) and the corresponding Sachs-Wolfe quadratic approximation.
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In the text

$\begin{figure} \center \epsfig{file=9880f01a.eps,height=3.7cm,width=5.9cm,clip}\... ...5.9cm,clip}\epsfig{file=9880f01c.eps,height=3.7cm,width=5.9cm,clip} \end{figure}$	Figure 1: Distribution of the $\chi ^2$ values from the Minkowski Gaussianity analysis for the Archeops 143K03-143K04 map at $N_{\rm side}=32$ , $N_{\rm side}=64$ , and $N_{\rm side}=128$ . The vertical lines show data, the histograms are obtained from a set of 10³ simulations, and the solid lines are the expected $\chi ^2$ distributions for $3n_{\rm th}$ degrees of freedom.
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$\begin{figure} \center \epsfig{file=9880f02a.eps,height=3.7cm,width=5.9cm,clip}... ...5.9cm,clip}\epsfig{file=9880f02c.eps,height=3.7cm,width=5.9cm,clip} \end{figure}$	Figure 2: Distribution of the $\chi ^2$ values from the Minkowski Gaussianity analysis for the Archeops 143K03 noise map at $N_{\rm side}=32$ , $N_{\rm side}=64$ , and $N_{\rm side}=128$ . Vertical lines show data, the histograms corresponds to sets of 10³ noise simulations, and the solid lines are the $\chi ^2$ distribution with $3n_{\rm th}$ degrees of freedom.
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$\begin{figure} \par\epsfig{file=9880f03a.eps,height=3.7cm,width=5.9cm,clip}\epsf... ...5.9cm,clip}\epsfig{file=9880f03c.eps,height=3.7cm,width=5.9cm,clip} \end{figure}$	Figure 3: From left to right, $\chi ^2$ statistic of the 143K03 noise map, its cumulative probability, and the fraction of available area for different values of the minimum number of hits at $N_{\rm side}=128$ . This map becomes compatible with Gaussianity when the minimum number of hits is approximately 90.
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$\begin{figure} \center \epsfig{file=9880f06a.eps,height=4.5cm,width=8cm}\epsfig{file=9880f06b.eps,height=4.5cm,width=8cm} \end{figure}$	Figure 6: From left to right, $\chi ^2(f_{\rm nl})$ of Archeops data vs. $f_{\rm nl}$ and the best fit value of $f_{\rm nl}$ for a set of 2000 Archeops Gaussian simulations ( s_k03+n_k03) combining the maps at resolutions $N_{\rm side}=32,64,128$ .
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$\begin{figure} \center \epsfig{file=9880f07a.eps,height=4.5cm,width=8cm}\epsfig{file=9880f07b.eps,height=4.5cm,width=8cm} \end{figure}$	Figure 7: From left to right, the non-Gaussian part of a full sky CMB simulation at low resolution ( $N_{\rm side}=16$ ) and the corresponding Sachs-Wolfe quadratic approximation.
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