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Description
We present an optimized library of synthetic galaxy spectra that are to be used for the Gaia satellite observations of unresolved galaxies. These galaxy spectral templates are useful for the optimal performance of the unresolved galaxy classifier (UGC) software. The UGC will assign spectral classes to the observed unresolved galaxies by Gaia (classification) and estimate some of their intrinsic astrophysical parameters, which were used to create the synthetic library (parametrization). We present the new optimized synthetic library of galaxy spectra and the classification and parametrization results using the Gaia-simulated version of this library. To optimize our synthetic library, we applied the principal component analysis (PCA) method to our synthetic spectra and studied the influence of the star-formation rate parameters on the spectra, and how these agree with some typical characteristics of the galaxy spectral types. We used support vector machines (SVM) to classify and parametrize the optimal simulated spectra. The library of synthetic galaxy spectra was optimized. In this new set of synthetic spectra, overlaps in spectral energy distributions and colors are highly suppressed, while the results of UGC classification are improved.
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