Diagnosing large-scale stellar magnetic fields using PCA on spectropolarimetric data
L. T. Lehmann, J.-F. Donati

TL;DR
This paper introduces a PCA-based method to analyze stellar magnetic fields from spectropolarimetric data, offering a simpler alternative to Zeeman-Doppler Imaging for characterizing magnetic topologies and their evolution.
Contribution
The paper presents a novel PCA approach for diagnosing large-scale stellar magnetic fields directly from spectropolarimetric profiles, reducing reliance on complex imaging techniques.
Findings
Effective for stars with moderate velocities and simple magnetic fields
Can diagnose temporal variability of magnetic topologies
Simplifies analysis compared to Zeeman-Doppler Imaging
Abstract
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~) 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…
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