论文标题
在研究JWST的不均匀发射光谱时,了解和减轻偏见
Understanding and Mitigating Biases when Studying Inhomogeneous Emission Spectra with JWST
论文作者
论文摘要
假设观察到的半球是由水平匀浆的气氛很好地表示,则通常对系外星发射光谱进行建模。但是,对于詹姆斯·韦伯(James Webb)太空望远镜(JWST)时代,这种近似值可能会失败,而温度对比度很大,这可能导致对光谱的错误解释。我们首先开发一种分析公式,以量化从半球平均频谱中解散温度不均匀性所需的信噪比和波长覆盖率。我们发现,对于给定的信噪比,较短波长的观察在检测不均匀性的存在方面更好。然后,我们确定为什么在检索过程中假设一个完全同质的行星时,为什么存在不均匀的热结构会导致杂散的分子检测。最后,我们通过建模一组热木星光谱来更准确地量化潜在的偏见,从而改变了热区和冷区的空间贡献,正如JWST/NIRSPEC的不同工具所观察到的那样。然后,我们从合成观测值中检索出丰度和温度曲线。我们发现,在大多数情况下,在检索大气化学时假设具有均匀的热结构会导致偏见的结果和杂种分子检测。使用两个配置文件对数据进行显式建模可以避免这些偏差,并且在波长覆盖范围足够宽的情况下得到统计支持,并且至关重要的是跨越较短的波长。对于此处使用的高对比度,具有稀释因子的单个轮廓和两个PROILE情况,与1-D方法相比,只有一个附加参数。
Exoplanet emission spectra are often modelled assuming that the hemisphere observed is well represented by a horizontally homogenised atmosphere. However this approximation will likely fail for planets with a large temperature contrast in the James Webb Space Telescope (JWST) era, potentially leading to erroneous interpretations of spectra. We first develop an analytic formulation to quantify the signal-to-noise ratio and wavelength coverage necessary to disentangle temperature inhomogeneities from a hemispherically averaged spectrum. We find that for a given signal-to-noise ratio, observations at shorter wavelengths are better at detecting the presence of inhomogeneities. We then determine why the presence of an inhomogeneous thermal structure can lead to spurious molecular detections when assuming a fully homogenised planet in the retrieval process. Finally, we quantify more precisely the potential biases by modelling a suite of hot Jupiter spectra, varying the spatial contributions of a hot and a cold region, as would be observed by the different instruments of JWST/NIRSpec. We then retrieve the abundances and temperature profiles from the synthetic observations. We find that in most cases, assuming a homogeneous thermal structure when retrieving the atmospheric chemistry leads to biased results, and spurious molecular detection. Explicitly modelling the data using two profiles avoids these biases, and is statistically supported provided the wavelength coverage is wide enough, and crucially also spanning shorter wavelengths. For the high contrast used here, a single profile with a dilution factor performs as well as the two-profile case, with only one additional parameter compared to the 1-D approach.