The China Space Station Telescope (CSST) will conduct wide-field multiband photometric imaging and slitless spectroscopic surveys, advancing cosmology and galaxy evolution studies. Achieving CSST’s cosmological goals requires precise redshifts () from low-resolution () and potentially blended slitless spectra. We present BayeSED3, extended for Bayesian full-spectrum analysis, including nebular emission modeling (via ) and a Bayesian treatment of the model scaling factor, improving reliability over optimization methods for low SNR spectra. Validated on realistic mock data generated with the CESS emulator (median SNR=1.65, including instrumental and self-blending effects), our method achieves excellent redshift precision with three-band (GU+GV+GI) spectroscopy: (80% success) for star-forming and (50% success) for quiescent galaxies. Stellar mass ( dex for SF, dex for quiescent) and SFR ( dex for SF, especially at SNR>1) are reliably recovered. Self-blending increases scatter by , but combining spectroscopy with CSST’s seven-band photometry significantly improves accuracy, especially for quiescent galaxies and data-limited cases. Single-band spectroscopy plus photometry yields reasonable redshifts: GU+photometry is limited, GI+photometry gives >60% (SF) and >40% (quiescent) success at , GV+photometry gives >35% (SF) and 40% (quiescent) at similar precision. The Bayesian framework offers a powerful method for accurate galaxy characterization, enhancing CSST’s scientific outcomes despite the challenges of slitless spectroscopy.

生成讲解博客的中文版本

生成AI智能校验的中文版本