Stellar population properties for 2 million galaxies from SDSS DR14 and DEEP2 DR4 from full spectral fitting
Johan Comparat, Claudia Maraston, Daniel Goddard, Violeta, Gonzalez-Perez, Jianhui Lian, Sofia Meneses-Goytia, Daniel Thomas, Joel R., Brownstein, Rita Tojeiro, Alexis Finoguenov, Andrea Merloni, Francisco Prada,, Mara Salvato, Guangtun B. Zhu, Hu Zou, Jonathan Brinkmann

TL;DR
This study performs full spectral fitting to determine stellar population properties for 2 million galaxies from SDSS DR14 and DEEP2 DR4, providing a comprehensive catalog to support galaxy evolution research.
Contribution
It introduces a large, detailed catalog of stellar population parameters derived from high-resolution spectral fitting, including for DEEP2 galaxies at higher redshift, with assessments of accuracy and consistency.
Findings
Achieved 0.2 dex accuracy in stellar mass at S/N ~20
Found DEEP2 galaxies have a flat stellar mass distribution between 10^9 and 10^11.5 solar masses
Produced a catalog twice as large as previous SDSS data releases
Abstract
We determine the stellar population properties - age, metallicity, dust reddening, stellar mass and the star formation history - for all spectra classified as galaxies that were published by the Sloan Digital Sky Survey (SDSS data release 14) and by the DEEP2 (data release 4) galaxy surveys. We perform full spectral fitting on individual spectra, making use of high spectral resolution stellar population models. Calculations are carried out for several choices of the model input, including three stellar initial mass functions and three input stellar libraries to the models. We study the accuracy of parameter derivation, in particular the stellar mass, as a function of the signal-to-noise of the galaxy spectra. We find that at low redshift, a signal to noise ratio per pixel around 20 (5) allows a statistical accuracy on of 0.2 (0.4) dex, for the Chabrier IMF.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
