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Figure 1: A general scheme of our codes. The continuous arrows refer to steps which are performed inside the TRILEGAL main code and subroutines; they lead to the simulation of perfect (i.e. without errors) photometric data. The dashed lines refer to some optional steps, usually performed with external scripts, like e.g. those mentioned in Paper I, to generate catalogues with errors. |
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Figure 2: HR diagram containing all tracks assembled for the solar metallicity. Our database contains similar data for 6 other values of metallicity. In the electronic version of this paper, tracks from different sources are marked with different colours: Girardi et al. (2000, black) for most evolutionary phases of low- and intermediate-mass stars, complemented with the TP-AGB phase from Marigo et al. (2003, and in preparation, magenta), massive stars from Bertelli et al. (1994, green), very-low mass stars and brown dwarfs from Chabrier et al. (2000, red), post-AGB and PNe nuclei from Vassiliadis & Wood (1994) complemented with WD cooling sequences from Benvenuto & Althaus (1999, both in blue). |
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Figure 3:
Intrinsic MV vs. ![]() |
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Figure 4:
The same as Fig. 3
but limited to the disc intrinsic MK vs. ![]() |
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Figure 5:
Distribution of stellar distance moduli in the
simulation corresponding to our initial calibration,
in a conic bean towards the NGP.
This is shown for 11 disc components of increasing age -
at steps of 1 Gyr, as labelled - and for the halo.
The top panel shows all the curves, whereas the
bottom one expands the vertical axis in order
to detail the profiles for ages younger than 5 Gyr.
It can be noticed that younger disc components
are found at lower mean distances (peaking from say
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Figure 6:
Number counts as a function of magnitude.
The histogram with error bars represents
the data from the 7 and 5-passband CDFS stellar
catalogues (Paper I) with poissonian errors.
The dashed and continuous gray vertical lines
indicate the magnitude limits for efficient morphological
classification, MAG_STAR_LIM, and the 90 percent
completeness limit, respectively.
For the J and K plots, at brighter
magnitudes (J<16.5 and K<15, respectively) we add the
histogram corresponding to 2MASS
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Figure 7:
The same as Fig. 6,
but now limiting data and models to the "blue subsample''
with
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Figure 8:
The same as Fig. 6,
but for the several fields of the DMS (Osmer et al. 1998),
whose ![]() ![]() |
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Figure 9:
The same as Fig. 8,
but now limiting data and models to the "blue subsample'' with
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Figure 10: The same as Fig. 6, but for the EIS-deep SGP data (Prandoni et al. 1999). The limits of reliability of the data were located, somewhat arbitrarily this time, at magnitudes 16 and 21.5 for all filters. |
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Figure 11:
The same as Fig. 6,
but for two sample fields of 2MASS data:
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Figure 12:
The same as Fig. 11,
but limited to the H-band and for
a series of fields disposed along the
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Figure 13:
The several panels show our Hipparcos simulation
(grey) versus the real data (dark). On the left panels, we have the
MV vs. ![]() ![]() ![]() ![]() ![]() ![]() |
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Figure 14:
The same as Fig. 13,
but for samples limited to an apparent magnitude of
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Figure A.1: Errors in Hipparcos parallaxes. The data is in the lower panel, our simulations in the upper one. |