Starlight-polarization-based tomography of the magnetized ISM: PASIPHAE’s line-of-sight inversion method
Starlight-polarization-based tomography of the magnetized ISM: PASIPHAE’s line-of-sight inversion method
复制标题
基于星光偏振的磁化 ISM 断层扫描：PASIPHAE 视线反演方法
DOI：
10.1051/0004-6361/202244625
复制
发表时间：
2023
影响因子：
6.5
通讯作者：
Papadaki, A.
中科院分区：
文献类型：
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作者：
Pelgrims, V.;Panopoulou, G. V.;Tassis, K.;Pavlidou, V.;Basyrov, A.;Blinov, D.;Gjerl∅w, E.;Kiehlmann, S.;Mandarakas, N.;Papadaki, A.
我们提出了第一种贝叶斯方法，用于利用恒星偏振法和距离对磁场的天平面方向进行层析分解。这种独立层析反演方法为在尘埃区域内三维重建磁化星际介质（ISM）迈出了重要的一步。我们建立了一个模型，在这个模型中，来自磁化和尘埃的ISM的极化信号是由不同距离上的薄层描述的，这是一个工作假设，在小角圆孔中应该满足。我们的模型可以推断由单个尘埃云引起的平均极化（振幅和方向），并以一种通用的方式解释湍流引起的散射。我们提出了一个明确地说明偏振和视差不确定性的似然函数。我们开发了一个框架，通过使用嵌套采样方法最大化对数似然来重建磁化的ISM。我们在模拟数据上测试了我们的贝叶斯反演方法，这些模拟数据代表了高银河系纬度的天空，考虑了来自盖亚的现实不确定性，并根据目前计划的观测策略对光学偏振调查PASIPHAE进行了预期。我们证明，对于所采用的巡天曝光时间和系统不确定性水平，只要云对其背景恒星引起的极化高于~0.1%，我们的方法就能有效地恢复云的特性。诱导极化越大，该方法的性能越好，所需的恒星数越少。我们的方法不仅可以恢复平均极化特性，而且可以表征本征散射，从而为表征ISM湍流和磁场强度创造了新的方法。最后，我们将我们的方法应用于已知视距分解的现有星光偏振数据集，证明与先前的结果一致，并且改进了云特性不确定性的量化。
We present the first Bayesian method for tomographic decomposition of the plane-of-sky orientation of the magnetic field with the use of stellar polarimetry and distance. This standalone tomographic inversion method presents an important step forward in reconstructing the magnetized interstellar medium (ISM) in three dimensions within dusty regions. We develop a model in which the polarization signal from the magnetized and dusty ISM is described by thin layers at various distances, a working assumption which should be satisfied in small-angular circular apertures. Our modeling makes it possible to infer the mean polarization (amplitude and orientation) induced by individual dusty clouds and to account for the turbulence-induced scatter in a generic way. We present a likelihood function that explicitly accounts for uncertainties in polarization and parallax. We develop a framework for reconstructing the magnetized ISM through the maximization of the log-likelihood using a nested sampling method. We test our Bayesian inversion method on mock data, representative of the high Galactic latitude sky, taking into account realistic uncertainties fromGaiaand as expected for the optical polarization survey PASIPHAE according to the currently planned observing strategy. We demonstrate that our method is effective at recovering the cloud properties as soon as the polarization induced by a cloud to its background stars is higher than ~0.1% for the adopted survey exposure time and level of systematic uncertainty. The larger the induced polarization is, the better the method’s performance, and the lower the number of required stars. Our method makes it possible to recover not only the mean polarization properties but also to characterize the intrinsic scatter, thus creating new ways to characterize ISM turbulence and the magnetic field strength. Finally, we apply our method to an existing data set of starlight polarization with known line-of-sight decomposition, demonstrating agreement with previous results and an improved quantification of uncertainties in cloud properties.