论文标题
使用PCA在光谱数据上诊断大规模恒星磁场
Diagnosing large-scale stellar magnetic fields using PCA on spectropolarimetric data
论文作者
论文摘要
恒星表面大规模磁场拓扑的见解通常是通过将Zeeman-Doppler成像（ZDI）应用于观察到的SpectroPolarimetric时间序列绘制的。但是，ZDI需要达到可靠结果的经验，并且基于许多可能无效的先前假设，例如，当磁性拓扑在与收集观测值的时间范围内相当或短的时间尺度上发展时。在本文中，我们提出了一种基于主要成分分析（PCA）的方法，该方法应用于磁星的循环极化（Stokes〜$ V $）线轮廓，以检索父级大规模磁性拓扑的主要特征，例如，例如，多型和圆环成分的相对强度，以及具有复杂性及其复杂性（及其复杂性）和更复杂的型号（及其复杂程度）（及其复杂程度）。我们表明，该方法也可以用于诊断大规模磁场的时间变异性。对于具有适度投影赤道速度的恒星托管相对简单的磁场拓扑结构，这种新方法比ZDI更简单，这使得迅速诊断非分类恒星大规模领域的主要特征并提供有关田间拓扑的时间演化的洞察力。
Insights on stellar surface large-scale magnetic field topologies are usually drawn by applying Zeeman-Doppler-Imaging (ZDI) to the observed spectropolarimetric time series. However, ZDI requires experience for reliable results to be reached and is based on a number of prior assumptions that may not be valid, e.g., when the magnetic topology is evolving on timescales comparable to or shorter than the time span over which observations are collected. In this paper, we present a method based on Principal Component Analysis (PCA) applied to circularly polarised (Stokes~$V$) line profiles of magnetic stars to retrieve the main characteristics of the parent large-scale magnetic topologies, like for instance, the relative strength of the poloidal and toroidal components, and the degree of axisymmetry of the dominant field component and its complexity (dipolar or more complex). We show that this method can also be used to diagnose the temporal variability of the large-scale magnetic field. Performing best for stars with moderate projected equatorial velocities hosting relatively simple magnetic field topologies, this new method is simpler than ZDI, making it convenient to rapidly diagnose the main characteristics of the large-scale fields of non-degenerate stars and to provide insights into the temporal evolution of the field topology.
