Synthesis models in a probabilistic framework: metrics of fitting

Details Synthesis models in a probabilistic framework: metrics of fitting Synthesis models in a probabilistic framework: metrics of fitting

2007-11-08

arxiv.org/abs/0711.1355v1

Astronomy and Astrophysics

Astrophysics

Invited talk in "New Quests in stellar astrophysics II. Ultraviolet properties of evolved stellar populations" in press. 8 pag

Scientific paper

In general, synthesis models provide the mean value of the distribution of possible integrated luminosities, this distribution (and not only its mean value) being the actual description of the integrated luminosity. Therefore, to obtain the closest model to an observation only provides confi- dence about the precision of such a fit, but not information about the accuracy of the result. In this contribution we show how to overcome this drawback and we propose the use of the theoretical mean-averaged dispersion that can be produced by synthesis models as a metric of fitting to infer accurate physical parameters of observed systems.

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