BayeSED-GALAXIES II. 基于贝叶斯的完整光谱分析及在CSST宽视场无 slit 光谱学调查中的应用
BayeSED-GALAXIES II. Bayesian full spectrum analysis of galaxies and application in the CSST wide-field slitless spectroscopy survey
AI总结：
本文提出BayeSED3方法，通过贝叶斯完整光谱分析实现高精度红移和星系参数恢复，应用于CSST宽视场无 slit 光谱学调查。
摘要：
中国空间站望远镜（CSST）将开展宽视场多波段测光和无 slit 光谱学调查，推动宇宙学和星系演化研究。实现CSST的宇宙学目标需要从低分辨率（R≈200）且可能混叠的无 slit 光谱中获得精确的红移（σ_NMAD≈0.002-0.005）。我们提出了BayeSED3，扩展了基于贝叶斯的完整光谱分析，包括星云发射模型（通过Cloudy）和对模型缩放因子的贝叶斯处理，提高了低信噪比光谱的可靠性。在使用CESS模拟器生成的现实模拟数据（中位数信噪比=1.65，包括仪器和自混叠效应）上验证，我们的方法在三波段（GU+GV+GI）光谱学中实现了出色的红移精度：恒星形成星系的σ_NMAD=0.0008（约80%成功），静止星系的σ_NMAD=0.0015（约50%成功）。恒星质量（σ_NMAD≈0.015 dex for SF，≈0.016 dex for quiescent）和恒星形成率（σ_NMAD≈0.05 dex for SF，尤其在SNR>1时）能够可靠地恢复。自混叠效应使散射增加超过30%，但结合光谱学与CSST的七波段测光显著提高准确性，特别是对静止星系和数据受限情况。单波段光谱学加测光可获得合理红移：GU+测光受限，GI+测光在σ_NMAD≈0.002时给出>60%（SF）和>40%（静止星系）的成功率，GV+测光在相似精度下给出>35%（SF）和约40%（静止星系）的成功率。贝叶斯框架为准确的星系表征提供了一种强大方法，即使在无 slit 光谱学的挑战下也增强了CSST的科学成果。
英文摘要：
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 ($σ_{\rm NMAD}\lesssim 0.002-0.005$) from low-resolution ($R\sim200$) and potentially blended slitless spectra. We present BayeSED3, extended for Bayesian full-spectrum analysis, including nebular emission modeling (via \textsc{Cloudy}) 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: $σ_{\rm NMAD}=0.0008$ ($\sim$80% success) for star-forming and $σ_{\rm NMAD}=0.0015$ ($\sim$50% success) for quiescent galaxies. Stellar mass ($σ_{\rm NMAD}\approx0.015$ dex for SF, $\approx0.016$ dex for quiescent) and SFR ($σ_{\rm NMAD}\approx0.05$ dex for SF, especially at SNR>1) are reliably recovered. Self-blending increases scatter by $\gtrsim30%$, 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 $σ_{\rm NMAD}\lesssim0.002$, GV+photometry gives >35% (SF) and $\sim$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.
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