DETAILED DECOMPOSITION OF GALAXY IMAGES. II. BEYOND AXISYMMETRIC MODELS

DETAILED DECOMPOSITION OF GALAXY IMAGES. II. BEYOND AXISYMMETRIC MODELS
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DOI:
10.1088/0004-6256/139/6/2097
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发表时间:
2009-12
期刊:
The Astronomical Journal
影响因子:
--
通讯作者:
C. Peng;L. Ho;C. Impey;H. Rix
C. Peng;L. Ho;C. Impey;H. Rix
中科院分区:
其他
文献类型:
--
作者:
C. Peng;L. Ho;C. Impey;H. Rix

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我们提出了一种二维(2D)拟合算法(Galfit,ver. 3)新的能力,研究星系和其他天文物体的结构组成部分的数字图像。我们的技术改进了以前的2D拟合算法,允许不规则,弯曲,对数和幂律螺旋,环和截断形状,否则传统的参数函数,如Sérsic,Moffat,King,Ferrer等,数据区.人们可以自由地混合和匹配这些新的形状特征,有或没有约束,并将它们应用于任意数量的模型组件的众多配置文件类型,以产生逼真的星系模型图像。然而,尽管有可能极端复杂,但关键参数的含义,如Sérsic指数,有效半径或光度仍然是直观的,基本上没有改变。新的功能有一个有趣的潜力,用于量化的不对称程度的星系,量化低表面亮度潮汐功能下面和以外的发光星系,让更现实的分解的星系子组件中存在的强大的环和螺旋臂,并使方法来衡量分解星系子组件时的不确定性。我们通过几个案例研究来说明这些新功能,这些案例研究显示了不同程度的复杂性。
We present a two-dimensional (2D) fitting algorithm (Galfit, ver. 3) with new capabilities to study the structural components of galaxies and other astronomical objects in digital images. Our technique improves on previous 2D fitting algorithms by allowing for irregular, curved, logarithmic and power-law spirals, ring, and truncated shapes in otherwise traditional parametric functions like the Sérsic, Moffat, King, Ferrer, etc., profiles. One can mix and match these new shape features freely, with or without constraints, and apply them to an arbitrary number of model components of numerous profile types, so as to produce realistic-looking galaxy model images. Yet, despite the potential for extreme complexity, the meaning of the key parameters like the Sérsic index, effective radius, or luminosity remains intuitive and essentially unchanged. The new features have an interesting potential for use to quantify the degree of asymmetry of galaxies, to quantify low surface brightness tidal features beneath and beyond luminous galaxies, to allow more realistic decompositions of galaxy subcomponents in the presence of strong rings and spiral arms, and to enable ways to gauge the uncertainties when decomposing galaxy subcomponents. We illustrate these new features by way of several case studies that display various levels of complexity.