论文标题
在拟合的法拉第旋转信号中删除非物理结构：非参数Qutting
Removing non-physical structure in fitted Faraday rotated signals: non-parametric QU-fitting
论文作者
论文摘要
下一代光谱宽带调查将使用称为法拉第旋转的磁光效应，将以前所未有的细节探测宇宙磁场。但是，诸如RMCLEAN之类的非参数方法可以将非观察的线性极化通量引入在平方平方的负波长下的拟合模型中。这导致法拉第旋转结构与观察到的数据一致，但不可能或难以测量。我们构建一个凸非参数$ qu $ - 适合算法，以限制平方平方的负波长的通量。这允许算法恢复在波长平方中可观察到的可观察区域的复杂性限制的结构。我们在模拟的宽带数据集上验证了这种方法，在该数据集中我们表明它具有较低的均方根误差，并且可以改变实际观察的科学结论。我们建议在下一代宽带调查中使用此先验，旨在发现复杂的法拉第深度结构。我们在\ url {https://github.com/luke-pratley/faraday-dreams}提供了算法的公共Python实现。
Next-generation spectro-polarimetric broadband surveys will probe cosmic magnetic fields in unprecedented detail, using the magneto-optical effect known as Faraday rotation. However, non-parametric methods such as RMCLEAN can introduce non-observable linearly polarized flux into a fitted model at negative wavelengths squared. This leads to Faraday rotation structures that are consistent with the observed data, but would be impossible or difficult to measure. We construct a convex non-parametric $QU$-fitting algorithm to constrain the flux at negative wavelengths squared to be zero. This allows the algorithm to recover structures that are limited in complexity to the observable region in wavelength squared. We verify this approach on simulated broadband data sets where we show that it has a lower root mean square error and that it can change the scientific conclusions for real observations. We advise using this prior in next-generation broadband surveys that aim to uncover complex Faraday depth structures. We provide a public Python implementation of the algorithm at \url{https://github.com/Luke-Pratley/Faraday-Dreams}.
