An efficient approach to extract parameters from star cluster CMDs: fitCMD. (arXiv:1812.01650v1 [astro-ph.IM])
<a href="http://arxiv.org/find/astro-ph/1/au:+Bonatto_C/0/1/0/all/0/1">Charles Bonatto</a>
This work presents an approach (fitCMD) designed to obtain a comprehensive
set of astrophysical parameters from colour-magnitude diagrams (CMDs) of star
clusters. Based on initial mass function (IMF) properties taken from
isochrones, fitCMD searches for the values of total (or cluster) stellar mass,
age, global metallicity, foreground reddening, distance modulus, and
magnitude-dependent photometric completeness that produce the artificial CMD
that best reproduces the observed one; photometric scatter is also taken into
account in the artificial CMDs. Inclusion of photometric completeness proves to
be an important feature of fitCMD, something that becomes apparent especially
when luminosity functions are considered. These parameters are used to build a
synthetic CMD that also includes photometric scatter. Residual minimization
between the observed and synthetic CMDs leads to the best-fit parameters. When
tested against artificial star clusters, fitCMD shows to be efficient both in
terms of computational time and ability to recover the input values.
This work presents an approach (fitCMD) designed to obtain a comprehensive
set of astrophysical parameters from colour-magnitude diagrams (CMDs) of star
clusters. Based on initial mass function (IMF) properties taken from
isochrones, fitCMD searches for the values of total (or cluster) stellar mass,
age, global metallicity, foreground reddening, distance modulus, and
magnitude-dependent photometric completeness that produce the artificial CMD
that best reproduces the observed one; photometric scatter is also taken into
account in the artificial CMDs. Inclusion of photometric completeness proves to
be an important feature of fitCMD, something that becomes apparent especially
when luminosity functions are considered. These parameters are used to build a
synthetic CMD that also includes photometric scatter. Residual minimization
between the observed and synthetic CMDs leads to the best-fit parameters. When
tested against artificial star clusters, fitCMD shows to be efficient both in
terms of computational time and ability to recover the input values.
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