发表机构
The University of Western Australia（西澳大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究基于GAMA样本，通过SED拟合分析星系在M*-SFR平面上的位置可约束性，发现低sSFR区域不确定性剧增，星暴星系难以稳健识别，绿谷选择不稳定，sSFR截断优于SFS相对截断。
AI 中文摘要
利用 GAMA 巡天中 6,029 个 $z<0.06$ 星系的样本，我们通过光谱能量分布（SED）拟合刻画了星系属性推断在 $M_*$ -- SFR 平面上的散布。我们使用恒星族库代码 \textsc{ProGeny} 和 SED 拟合代码 \textsc{ProSpect} 分析了 24 种不同的模型配置，并量化了建模假设如何影响推断的恒星质量、恒星形成率以及由此产生的星系分类。我们发现，推断星系位置的可重复性强烈依赖于其在 $M_*$ -- SFR 平面内的位置，当 $\log_{10}(\rm{sSFR}/\rm{yr}^{-1}) \sim -11$ 以下时，不确定性急剧增加。这一边界与 SFR 估计是否稳健或约束较差的转变紧密对应，无论 SFR 是来自 SED 拟合还是 H$_{\alpha}$ 测量。我们发现，仅通过 SED 拟合无法稳健地分离星暴星系，而星暴星系与被动星系的区分最一致地是通过 sSFR 的截断，而非相对于弯曲或线性的恒星形成序列（SFS）的 dex 截断。我们进一步表明，使用 SED 拟合的过渡（或绿谷）选择非常不稳定，平均只有约 25% 的样本被重复选中。
英文摘要
Using a sample of 6,029 $z<0.06$ galaxies from the GAMA survey, we characterise the spread of galaxy property inferences on the M$_*$ -- SFR plane via Spectral Energy Distribution (SED) fitting. We analyse 24 different model configurations using the stellar population library code \textsc{ProGeny}, and the SED-fitting code \textsc{ProSpect}, and quantify how modelling assumptions affect inferred stellar masses, star formation rates, and the resulting classification of galaxies. We find that the reproducibility of inferred galaxy positions depends strongly on location within the $M_*$ -- SFR plane, with uncertainties increasing dramatically below $\log_{10}(\rm{sSFR}/\rm{yr}^{-1}) \sim -11$. This boundary closely tracks the transition between robustly and poorly constrained SFR estimates, regardless of whether SFRs are derived from SED fitting or H$_α$ measurements. We find that star-bursting galaxies cannot be robustly isolated from SED fitting alone, while the separation of star-forming and passive galaxies is most consistently conducted by a cut in sSFR, rather than a dex cut relative to either a curved or linear SFS (Star Forming Sequence). We further show that transitioning (or Green Valley) selections using SED fitting are highly unstable, with only $\sim$25\% of the sample being repeatedly selected, on average.
Comments24 pages, 20 figures, submitted for publication to MNRAS. Comments welcome
