We compile multi-wavelength data from ultraviolet to infrared(IR) bands as well as redshift and source-type information, for a large sample of 178 341 sources in the Hawaii-Hubble Deep Field-North field. A total of 14...We compile multi-wavelength data from ultraviolet to infrared(IR) bands as well as redshift and source-type information, for a large sample of 178 341 sources in the Hawaii-Hubble Deep Field-North field. A total of 145 635 sources among the full sample are classified/treated as galaxies and have redshift information available. We derive physical properties for these sources utilizing the spectral energy distribution fitting code CIGALE that is based on Bayesian analysis. Through various consistency and robustness checks, we find that our stellar-mass and star-formation rate(SFR) estimates are reliable, which is mainly due to two facts. Firstly, we adopt the most up-to-date and accurate redshifts and point spread functionmatched photometry; and secondly, we make sensible parameter choices with the CIGALE code and take into account the influences of mid-IR/far-IR data, star-formation history models, and AGN contribution. We release our catalog of galaxy properties publicly(including, e.g., redshift, stellar mass, SFR, age, metallicity, dust attenuation). It is the largest of its kind in this field and should facilitate future relevant studies on the formation and evolution of galaxies.展开更多
基金support from the 973 Program (2015CB857004)the National Natural Science Foundation of China (GrantNos. 11890693, 11473026 and 11421303)the CAS Frontier Science Key Research Program (QYZDJ-SSW-SLH006)
文摘We compile multi-wavelength data from ultraviolet to infrared(IR) bands as well as redshift and source-type information, for a large sample of 178 341 sources in the Hawaii-Hubble Deep Field-North field. A total of 145 635 sources among the full sample are classified/treated as galaxies and have redshift information available. We derive physical properties for these sources utilizing the spectral energy distribution fitting code CIGALE that is based on Bayesian analysis. Through various consistency and robustness checks, we find that our stellar-mass and star-formation rate(SFR) estimates are reliable, which is mainly due to two facts. Firstly, we adopt the most up-to-date and accurate redshifts and point spread functionmatched photometry; and secondly, we make sensible parameter choices with the CIGALE code and take into account the influences of mid-IR/far-IR data, star-formation history models, and AGN contribution. We release our catalog of galaxy properties publicly(including, e.g., redshift, stellar mass, SFR, age, metallicity, dust attenuation). It is the largest of its kind in this field and should facilitate future relevant studies on the formation and evolution of galaxies.
