A Comprehensive Bayesian Discrimination of the Simple Stellar Population Model, Star Formation History, and Dust Attenuation Law in the Spectral Energy Distribution Modeling of Galaxies
A Comprehensive Bayesian Discrimination of the Simple Stellar Population Model, Star Formation History, and Dust Attenuation Law in the Spectral Energy Distribution Modeling of Galaxies
复制标题
星系光谱能量分布建模中简单恒星种群模型、恒星形成历史和尘埃衰减规律的综合贝叶斯判别
DOI：
10.3847/1538-4365/aaeffa
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Zhanwen Han
中科院分区：
文献类型：
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作者：
Yunkun Han;Zhanwen Han
在建模和解释星系的光谱能量分布 (SED) 时，简单恒星种群 (SSP) 模型、恒星形成历史 (SFH) 和尘埃衰减定律 (DAL) 是三个最重要的组成部分。然而，它们中的每一个都带有很大的不确定性，严重限制了我们从 SED 分析中可靠地恢复星系物理特性的能力。在本文中，我们提出了一个贝叶斯框架来同时处理这些不确定因素。基于贝叶斯证据（奥卡姆剃刀原理的定量实现），该方法允许对这些不确定成分的不同假设进行更客观和定量的区分。通过 Ks 在 COSMOS/UltraVISTA 领域中选择的 5467 个低红移（大部分为 z1）星系样本，并通过 UVJ 图将其分为被动演化星系（PEG）和恒星形成星系（SFG），我们提出了来自五个研究小组（BC03 和 CB07、 M05、GALEV、Yunnan-II、BPASSV2.0）、SFH的五种形式（Burst、Constant、Exp-dec、Exp-inc、Delayed-τ）和四种DAL（Calzettilaw、MW、LMC、SMC）。我们表明，在恒星/星系物理学的背景下，用该方法获得的结果要么是显而易见的，要么是可以理解的。我们得出结论，贝叶斯模型比较方法，特别是对于星系样本，对于区分星系 SED 建模中的不同假设非常有用。本工作中使用的 BayeSED 代码的新版本可在 https://bitbucket.org/hanyk/bayesed/ 上公开获取。
When modeling and interpreting the spectral energy distributions (SEDs) of galaxies, the simple stellar population (SSP) model, star formation history (SFH), and dust attenuation law (DAL) are three of the most important components. However, each of them carries significant uncertainties that have seriously limited our ability to reliably recover the physical properties of galaxies from the analysis of their SEDs. In this paper, we present a Bayesian framework to deal with these uncertain components simultaneously. Based on the Bayesian evidence, a quantitative implement of the principle of Occam’s razor, the method allows a more objective and quantitative discrimination among the different assumptions about these uncertain components. With a Ks-selected sample of 5467 low-redshift (mostly with z1) galaxies in the COSMOS/UltraVISTA field and classified into passively evolving galaxies (PEGs) and star-forming galaxies (SFGs) with the UVJ diagram, we present a Bayesian discrimination of a set of 16 SSP models from five research groups (BC03 and CB07, M05, GALEV, Yunnan-II, BPASSV2.0), five forms of SFH (Burst, Constant, Exp-dec, Exp-inc, Delayed-τ), and four kinds of DAL (Calzettilaw, MW, LMC, SMC). We show that the results obtained with the method are either obvious or understandable in the context of stellar/galaxy physics. We conclude that the Bayesian model comparison method, especially that for a sample of galaxies, is very useful for discriminating the different assumptions in the SED modeling of galaxies. The new version of the BayeSED code, which is used in this work, is publicly available at https://bitbucket.org/hanyk/bayesed/.