论文标题
我们如何测量星系的恒星质量:假定的恒星形成历史模型在SED拟合中的影响
How Well Can We Measure the Stellar Mass of a Galaxy: The Impact of the Assumed Star Formation History Model in SED Fitting
论文作者
论文摘要
推断星系的恒星质量($ m _*$)的主要方法是通过光谱能量分布(SED)建模。但是,该技术取决于假设,例如星系恒星形成历史记录和尘埃衰减定律,这些定律可能会严重影响SED建模的物理特性的准确性。在这里,我们研究了假定的恒星形成历史(SFH)对通过接地拟合所推断出的恒星特性的影响,以对抗对高分辨率宇宙学水动力学星系形成模拟的模拟观察。从经典上讲,SFH是用简化的参数化功能形式建模的,但是这些形式不太可能捕获Galaxy SFHS的真实多样性,并可能对结果施加系统性偏见,对结果不确定性。我们证明,灵活的非参数恒星形成历史在捕获星系星形成历史的变化方面优于传统参数形式,因此,导致SED配件中的恒星质量显着改善。对于非参数模型,我们发现平均偏置为0.4 DEX,延迟$τ$模型的平均偏置为偏差略低于0.05 DEX。同样,在拟合中使用非参数恒星形成历史,导致回收的星系恒星形成率(SFRS)和恒星年龄的准确性提高。
The primary method for inferring the stellar mass ($M_*$) of a galaxy is through spectral energy distribution (SED) modeling. However, the technique rests on assumptions such as the galaxy star formation history and dust attenuation law that can severely impact the accuracy of derived physical properties from SED modeling. Here, we examine the effect that the assumed star formation history (SFH) has on the stellar properties inferred from SED fitting by ground truthing them against mock observations of high-resolution cosmological hydrodynamic galaxy formation simulations. Classically, SFHs are modeled with simplified parameterized functional forms, but these forms are unlikely to capture the true diversity of galaxy SFHs and may impose systematic biases with under-reported uncertainties on results. We demonstrate that flexible nonparametric star formation histories outperform traditional parametric forms in capturing variations in galaxy star formation histories, and as a result, lead to significantly improved stellar masses in SED fitting. We find a decrease in the average bias of 0.4 dex with a delayed-$τ$ model to a bias of just under 0.05 dex for the nonparametric model. Similarly, using nonparametric star formation histories in SED fitting result in increased accuracy in recovered galaxy star formation rates (SFRs) and stellar ages.