We present test results on the simultaneous inversion of the Stokes profiles of the He I lines at 587.6 nm (D_3) and 1083.0 nm in prominences (90-deg scattering). We created datasets of synthetic Stokes profiles for the case of quiescent prominences (B<200 G), assuming a conservative value of 10^-3 of the peak intensity for the polarimetric sensitivity of the simulated observations. In this work, we focus on the error analysis for the inference of the magnetic field vector, under the usual assumption that the prominence can be assimilated to a slab of finite optical thickness with uniform magnetic and thermodynamic properties. We find that the simultaneous inversion of the two lines significantly reduces the errors on the inference of the magnetic field vector, with respect to the case of single-line inversion. These results provide a solid justification for current and future instrumental efforts with multi-line capabilities for the observations of solar prominences and filaments.
Spectral line inversion codes are tools used to interpret spectropolarimetric data; in general, their function is to analyze a set of observed Stokes profiles, and infer the physical properties of the line-formation region in which the Stokes profiles were formed. For the SOLIS/VSM 6302v pipeline, the inversion is based on a Milne-Eddington model atmosphere, optimized to reproduce the observed Stokes profiles of both Fe I lines at 6301.5 and 6302.5 Angstroms . This document provides a detailed overview of the SOLIS/VSM remix of the VFISV (Very Fast Inversion of the Stokes Vector) inversion cod…
VFISV: Very Fast Inversion of the Stokes Vector for the Helioseismic and Magnetic Imager
本文详细介绍了一种新的偏振辐射转移方程反演程序（VFISV：Very Fast inversion of the Stokes vector）的实现和主要性质。VFISV将定期分析太阳动力学观测台（SDO）上的日震和磁成像仪（HMI）的管道数据。它将每隔10分钟提供太阳光球层磁场矢量的全磁盘地图（4096 $\times$ 4096像素）。因此，VFISV经过优化以实现反转速度，使其能够每10分钟反转1600万个像素，并且数量适中（约为1000万像素）。50)的CPU。在这里，我们重点描述了一些重要的细节，简化和调整，使我们能够显着加快反演过程。我们还详细介绍了从分光偏振仪板上的日之出航天器的数据进行测试。
Stokes inversion techniques are very powerful methods for obtaining information on the thermodynamic and magnetic properties of solar and stellar atmospheres. In recent years, very sophisticated inversion codes have been developed that are now routinely applied to spectro-polarimetric observations. Most of these inversion codes are designed for finding an optimum solution to the nonlinear inverse problem. However, to obtain the location of potentially multimodal cases (ambiguities), the degeneracies, and the uncertainties of each parameter inferred from the inversions, algorithms such as Marko…
Future ground-based telescopes, such as the 4-metre class facilities DKIST and EST, will dramatically improve on current capabilities for simultaneous multi-line polarimetric observations in a wide range of wavelength bands, from the near-ultraviolet to the near-infrared. As a result, there will be an increasing demand for fast diagnostic tools, i.e., inversion codes, that can infer the physical properties of the solar atmosphere from the vast amount of data these observatories will produce. The advent of substantially larger apertures, with the concomitant increase in polarimetric sensitivity…
Instituto de Astrofísica de Andalucía (CSIC)（安达卢西亚天体物理研究所（西班牙国家研究委员会））；Univ Coimbra（科英布拉大学）；University of Colorado（科罗拉多大学）；Laboratory for Atmospheric and Space Physics（大气与空间物理实验室）；National Solar Observatory（国家太阳天文台）；University of Oslo（奥斯陆大学）；Instituto de Astrofísica de Canarias（加那利群岛天体物理研究所）；Univ. de La Laguna（拉古纳大学）
In this work, we discuss the application of convolutional neural networks (CNNs) as a tool to advantageously initialize Stokes profile inversions. To demonstrate the usefulness of CNNs, we concentrate in this paper on the inversion of LTE Stokes profiles. We use observations taken with the spectropolarimeter onboard the Hinode spacecraft as a test benchmark. First, we carefully analyze the data with the SIR inversion code using a given initial atmospheric model. The code provides a set of atmospheric models that reproduce the observations. These models are then used to train a CNN. Afterwards,…
University of Michigan（密歇根大学）；NASA GSFC（美国国家航空航天局戈达德太空飞行中心）；NorthWest Research Associates（西北研究协会）；Stanford University（斯坦福大学）
The Helioseismic and Magnetic Imager (HMI) onboard NASA's Solar Dynamics Observatory (SDO) produces estimates of the photospheric magnetic field which are a critical input to many space weather modelling and forecasting systems. The magnetogram products produced by HMI and its analysis pipeline are the result of a per-pixel optimization that estimates solar atmospheric parameters and minimizes disagreement between a synthesized and observed Stokes vector. In this paper, we introduce a deep learning-based approach that can emulate the existing HMI pipeline results two orders of magnitude faster…
The inference of the underlying state of the plasma in the solar chromosphere remains extremely challenging because of the nonlocal character of the observed radiation and plasma conditions in this layer. Inversion methods allow us to derive a model atmosphere that can reproduce the observed spectra by undertaking several physical assumptions. The most advanced approaches involve a depth-stratified model atmosphere described by temperature, line-of-sight velocity, turbulent velocity, the three components of the magnetic field vector, and gas and electron pressure. The parameters of the radiati…
The structure of the solar chromosphere is believed to be governed by magnetic fields, even in quiet-Sun regions that have a relatively weak photospheric field. During the past decade inversion methods have emerged as powerful tools for analyzing the chromosphere of active regions. The applicability of inversions to infer the stratification of the physical conditions in a dynamic 3D solar chromosphere has not yet been studied in detail. This study aims to establish the diagnostic capabilities of non-local thermodynamical equilibrium (NLTE) inversion techniques of Stokes profiles induced by the…
New Jersey Institute of Technology（新泽西理工学院）；National University of Singapore（新加坡国立大学）
Obtaining high-quality magnetic and velocity fields through Stokes inversion is crucial in solar physics. In this paper, we present a new deep learning method, named Stacked Deep Neural Networks (SDNN), for inferring line-of-sight (LOS) velocities and Doppler widths from Stokes profiles collected by the Near InfraRed Imaging Spectropolarimeter (NIRIS) on the 1.6 m Goode Solar Telescope (GST) at the Big Bear Solar Observatory (BBSO). The training data of SDNN is prepared by a Milne-Eddington (ME) inversion code used by BBSO. We quantitatively assess SDNN, comparing its inversion results with th…
University of Michigan（密歇根大学）；NASA GSFC（美国国家航空航天局戈达德太空飞行中心）；NorthWest Research Associates（西北研究协会）；Lockheed Martin Solar and Astrophysics Laboratory（洛克希德·马丁太阳与天体物理实验室）；Stanford University（斯坦福大学）
Both NASA's Solar Dynamics Observatory (SDO) and the JAXA/NASA Hinode mission include spectropolarimetric instruments designed to measure the photospheric magnetic field. SDO's Helioseismic and Magnetic Imager (HMI) emphasizes full-disk high-cadence and good spatial resolution data acquisition while Hinode's Solar Optical Telescope Spectro-Polarimeter (SOT-SP) focuses on high spatial resolution and spectral sampling at the cost of a limited field of view and slower temporal cadence. This work introduces a deep-learning system named SynthIA (Synthetic Inversion Approximation), that can enhance …
Magnetic fields are responsible for a multitude of Solar phenomena, including such destructive events as solar flares and coronal mass ejections, with the number of such events rising as we approach the peak of the 11-year solar cycle, in approximately 2025. High-precision spectropolarimetric observations are necessary to understand the variability of the Sun. The field of quantitative inference of magnetic field vectors and related solar atmospheric parameters from such observations has long been investigated. In recent years, very sophisticated codes for spectropolarimetric observations have…
3DSTokesFlow: simulation-based inference for 3D Stokes profiles using flow matching
Instituto de Astrofísica de Canarias (IAC)（加那利天体物理研究所）；Universidad de La Laguna（拉古纳大学）；SETI Institute（SETI研究所）；University of Hawai‘i at Mānoa（夏威夷大学马诺阿分校）
Our knowledge of the lower solar atmosphere is mainly obtained from spectropolarimetric observations, which are often carried out in the red or infrared spectral range and almost always cover only a single or a few spectral lines. Here we compare the quality of Stokes inversions of only a few spectral lines with many-line inversions. We investigate the feasibility of spectropolarimetry in the short-wavelength range, 3000 Å - 4300 Å, where the line density but also the photon noise are considerably higher than in the red, so that many-line inversions could be particularly attractive in that wav…
The method of solar magnetic field calibration for the filter-based magnetograph is normally the linear calibration method under weak-field approximation that cannot generate the strong magnetic field region well due to the magnetic saturation effect. We try to provide a new method to carry out the nonlinear magnetic calibration with the help of neural networks to obtain more accurate magnetic fields. We employed the data from Hinode/SP to construct a training, validation and test dataset. The narrow-band Stokes I, Q, U, and V maps at one wavelength point were selected from all the 112 wavelen…
The magnetic field plays a major role in governing the dynamics of the sun. Many interesting features like sunspots, flares, prominences, and Coronal Mass Ejections (CMEs) occur on its surface due to the dynamics associated with the magnetic fields. The magnetic activity exhibits spatial scales ranging from very fine scale (below the resolution limit of the current largest telescope) to large scale such as sunspots, active regions and the spatial scales as large as the sun itself. While the major efforts in building large telescopes is going on towards the goal of resolving smallest structure …
