权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Inverse Modelling Methods for the Characterisation of Exoplanetary Atmospheres

描述系外行星大气特征的逆向建模方法

基本信息

批准号：
1638355
负责人：
金额：
--
依托单位：
University of Cambridge
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2015
资助国家：
英国
起止时间：
2015 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-1638355
关键词：
Inverse Modelling Methods Characterisation Exoplanetary

项目摘要

Since the launch of the Kepler Space Telescope in 2009, results now suggest that 1 in 5 Sun-like stars may have habitable planets (Petigura et al., 2013), which potentially holds startling implications for the field of Astrobiology and the search for life elsewhere in the Universe.In quick succession over the past 20 years, we have gone from planetary detection, to measuring bulk properties (such as density), to, most recently, characterisation of the atmospheres of a selection of these planets. Such atmospheric studies are vital to the long term goal of assessing habitability, as even within our own solar system the case studies of Mars and Venus demonstrate how otherwise 'habitable' planets can prove inhospitable due to their atmospheric makeup. We now face a continual drive to lower mass worlds, bringing the prospect of probing the atmosphere of a true Earth-analogue tantalisingly close to fruition.One of the issues that has plagued many past attempts to truly characterise exoplanet atmospheres is poorly understood degeneracies. For instance, when we observe the light from a transiting planet-star system, certain spectral features that have been interpreted as absorption due to a given molecule can also be explained by a different atmospheric temperature structure. In the past, single models were run until one fitting the data was found, without a throughout investigation of other combinations of atmospheric parameters that could also explain the data. To circumvent this, so called 'atmospheric retrieval' models have been developed (originally by my supervisor, Dr. Madhusudhan), which run millions of models to fully explore all the possible explanations for the observed behaviour. These take in observational data and use it to infer the properties of the atmosphere (often called 'inverse modelling').My current research focuses on theoretical modelling of exoplanet transmission spectra using the aforementioned methodology of atmospheric retrieval. My work involves investigating new physical phenomena that can be included in such models, such that a greater information content can be extracted from existing exoplanet transmission spectra. This will prove increasingly vital in the upcoming era of high-precision exoplanet spectroscopy (for instance, from the James Webb Space Telescope), as the quality of data will be sufficient to characterise such worlds in unprecedented detail. This, however, requires extensive theoretical exploration of previously neglected physical effects to ensure the maximum extraction possibility of potential discoveries.

自2009年开普勒太空望远镜发射以来，研究结果表明，五分之一的类太阳恒星可能拥有可居住的行星（Petigura等人，在过去的20年里，我们已经从行星探测，到测量整体性质（如密度），再到最近的一次，对这些行星的大气层进行了表征。这样的大气研究对于评估可居住性的长期目标至关重要，因为即使在我们自己的太阳系中，火星和金星的案例研究也表明，由于其大气构成，否则“可居住”的行星如何被证明是不适合居住的。我们现在面临着一个不断向低质量世界发展的趋势，这使得探测一个真正的地球类似物的大气层的前景非常接近于实现。过去许多真正探索系外行星大气层的尝试都遇到了一个问题，那就是人们对简并的了解很少。例如，当我们观察来自凌日行星-恒星系统的光时，某些被解释为特定分子吸收的光谱特征也可以用不同的大气温度结构来解释。在过去，运行单个模型，直到找到一个拟合数据，而没有对其他大气参数组合进行全面调查，这些参数也可以解释数据。为了规避这一点，人们开发了所谓的“大气反演”模型（最初是由我的导师Madhusudhan博士开发的），该模型运行了数百万个模型，以充分探索观察到的行为的所有可能解释。这些采取的观测数据，并使用它来推断大气的属性（通常称为“逆建模”）。我目前的研究重点是使用上述大气反演方法的系外行星传输光谱的理论建模。我的工作包括研究可以包含在这种模型中的新物理现象，以便从现有的系外行星传输光谱中提取更多的信息内容。这将在即将到来的高精度系外行星光谱学时代（例如，詹姆斯韦伯太空望远镜）中变得越来越重要，因为数据的质量足以以前所未有的细节来描述这些世界。然而，这需要对以前被忽视的物理效应进行广泛的理论探索，以确保潜在发现的最大提取可能性。