演講資訊

摘要：

Despite the fact that galaxies are extended objects, the majority of studies over the past decades have only utilized their integrated light, particularly for SED fitting. The advent of IFS surveys has revolutionized the studies of galaxy evolution. However, the wide-area IFS surveys have been mostly targeting local galaxies. Motivated by the current and future abundance of high spatial resolution and deep multi-band imaging data, we have been developing piXedfit, a Python package that provides tools for deriving spatially resolved properties of galaxies from multi-band imaging data alone or in combination with the IFS data. piXedfit can handle all the tasks in spatially resolved SED fitting, including images (or imaging+IFS data) processing, pixel binning, and SED fitting. We have tested piXedfit in various ways. When tested with mock SEDs of IllustrisTNG, piXedfit can recover properties and SFHs of the simulated galaxies well. We have tested piXedfit using real data consisting of 12-bands imaging data (from GALEX, SDSS, 2MASS, and WISE) and IFS data from MaNGA and CALIFA. piXedfit can spatially-match of the imaging and IFS data. By fitting only photometric SEDs, piXedfit can predict the spectral continuum, Dn4000, H-alpha, and H-beta well. In this talk, I will briefly introduce piXedfit as well as our ongoing works of using this tool for analyzing resolved properties of galaxies from the nearby universe up to high redhifts.