Nonlinear force-free coronal magnetic stereoscopy

Getting insights into the 3D structure of the solar coronal magnetic field have been done in the past by two completely different approaches: (1.) Nonlinear force-free field (NLFFF) extrapolations, which use photospheric vector magnetograms as boundary condition. (2.) Stereoscopy of coronal magnetic loops observed in EUV coronal images from different vantage points. Both approaches have their strength and weaknesses. Extrapolation methods are sensitive to noise and inconsistencies in the boundary data and the accuracy of stereoscopy is affected by the ability of identifying the same structure in different images and by the separation angle between the view directions. As a consequence, for the same observational data, the computed 3D coronal magnetic field with the two methods do not necessarily coincide. In an earlier work (Paper I) we extended our NLFFF optimization code by the inclusion of stereoscopic constrains. The method was successfully tested with synthetic data and within this work we apply the newly developed code to a combined data-set from SDO/HMI, SDO/AIA and the two STEREO spacecraft. The extended method (called S-NLFFF) contains an additional term that monitors and minimizes the angle between the local magnetic field direction and the orientation of the 3D coronal loops reconstructed by stereoscopy. We find that prescribing the shape of the 3D stereoscopically reconstructed loops the S-NLFFF method leads to a much better agreement between the modeled field and the stereoscopically reconstructed loops. We also find an appreciable decrease by a factor of two in the angle between the current and the magnetic field which indicates the improved quality of the force-free solution obtained by S-NLFFF.Comment: 9 pages, 7 figure

3D solar coronal loop reconstructions with machine learning

The magnetic field plays an essential role in the initiation and evolution of different solar phenomena in the corona. The structure and evolution of the 3D coronal magnetic field are still not very well known. A way to get the 3D structure of the coronal magnetic field is by performing magnetic field extrapolations from the photosphere to the corona. In previous work, it was shown that by prescribing the 3D reconstructed loops' geometry, the magnetic field extrapolation finds a solution with a better agreement between the modeled field and the reconstructed loops. Also, it improves the quality of the field extrapolation. Stereoscopy represents the classical method for performing 3D coronal loop reconstruction. It uses at least two view directions. When only one vantage point of the coronal loops is available, other 3D reconstruction methods must be applied. Within this work, we present a method for the 3D loop reconstruction based on machine learning. Our purpose for developing this method is to use as many observed coronal loops in space and time for the modeling of the coronal magnetic field. Our results show that we can build machine learning models that can retrieve 3D loops based only on their projection information. In the end, the neural network model will be able to use only 2D information of the coronal loops, identified, traced and extracted from the EUV images, for the calculation of their 3D geometry.Comment: 7 Pages, 3 Figures, Accepted for publication on Astrophysical Journal Letter

Three Eruptions Observed by Remote Sensing Instruments Onboard Solar Orbiter

On February 21 and March 21 – 22, 2021, the Extreme Ultraviolet Imager (EUI) onboard Solar Orbiter observed three prominence eruptions. The eruptions were associated with coronal mass ejections (CMEs) observed by Metis, Solar Orbiter’s coronagraph. All three eruptions were also observed by instruments onboard the Solar–TErrestrial RElations Observatory (Ahead; STEREO-A), the Solar Dynamics Observatory (SDO), and the Solar and Heliospheric Observatory (SOHO). Here we present an analysis of these eruptions. We investigate their morphology, direction of propagation, and 3D properties. We demonstrate the success of applying two 3D reconstruction methods to three CMEs and their corresponding prominences observed from three perspectives and different distances from the Sun. This allows us to analyze the evolution of the events, from the erupting prominences low in the corona to the corresponding CMEs high in the corona. We also study the changes in the global magnetic field before and after the eruptions and the magnetic field configuration at the site of the eruptions using magnetic field extrapolation methods. This work highlights the importance of multi-perspective observations in studying the morphology of the erupting prominences, their source regions, and associated CMEs. The upcoming Solar Orbiter observations from higher latitudes will help to constrain this kind of study better

An optimization principle for computing stationary MHD equilibria with solar wind flow

TW acknowledges financial support by DLR-grant 50 OC 1701 and DFG-grant WI 3211/5-1. TN acknowledges financial support by the UK’s Science and Technology Facilities Council (STFC) via Consolidated Grant ST/S000402/1. The Astronomical Institute of the Czech Academy of Sciences is supported by the project RVO:67985815. IC acknowledges funding by DFG-grant WI 3211/5-1.In this work we describe a numerical optimization method for computing stationary MHD-equilibria. The newly developed code is based on a nonlinearforce-free optimization principle. We apply our code to model the solar corona using synoptic vector magnetograms as boundary condition. Below about two solar radii the plasma β and Alfvén Mach number MA are small and the magnetic field configuration of stationary MHD is basically identical to a nonlinear force-free field, whereas higher up in the corona (where β and MA are above unity) plasma and flow effects become important and stationary MHD and force-free configuration deviate significantly. The new method allows the reconstruction of the coronal magnetic field further outwards than with potential field, nonlinear force-free or magneto-static models. This way the model might help to provide the magnetic connectivity for joint observations of remote sensing and in-situ instruments on Solar Orbiter and Parker Solar Probe.Publisher PDFPeer reviewe

Machine learning in solar physics

Abstract The application of machine learning in solar physics has the potential to greatly enhance our understanding of the complex processes that take place in the atmosphere of the Sun. By using techniques such as deep learning, we are now in the position to analyze large amounts of data from solar observations and identify patterns and trends that may not have been apparent using traditional methods. This can help us improve our understanding of explosive events like solar flares, which can have a strong effect on the Earth environment. Predicting hazardous events on Earth becomes crucial for our technological society. Machine learning can also improve our understanding of the inner workings of the sun itself by allowing us to go deeper into the data and to propose more complex models to explain them. Additionally, the use of machine learning can help to automate the analysis of solar data, reducing the need for manual labor and increasing the efficiency of research in this field

Linking the Sun to the Heliosphere Using Composition Data and Modelling: A Test Case with a Coronal Jet

Our understanding of the formation and evolution of the corona and the heliosphere is linked to our capability of properly interpret the data from remote sensing and in-situ observations. In this respect, being able to correctly connect in-situ observations with their source regions on the Sun is the key for solving this problem. In this work we aim at testing a diagnostics method for this connectivity. This paper makes use of a coronal jet observed on 2010 August 2nd in active region 11092 as a test for our connectivity method. This combines solar EUV and in-situ data together with magnetic field extrapolation, large scale MHD modeling and FIP (First Ionization Potential) bias modeling to provide a global picture from the source region of the jet to its possible signatures at 1 AU. Our data analysis reveals the presence of outflow areas near the jet which are within open magnetic flux regions and which present FIP bias consistent with the FIP model results. In our picture, one of these open areas is the candidate jet source. Using a back-mapping technique we identified the arrival time of this solar plasma at the ACE spacecraft. The in-situ data show signatures of changes in the plasma and magnetic field parameters, with FIP bias consistent with the possible passage of the jet material. Our results highlight the importance of remote sensing and in-situ coordinated observations as a key to solve the connectivity problem. We discuss our results in view of the recent Solar Orbiter launch which is currently providing such unique data

Three eruptions observed by remote sensing instruments onboard solar orbiter

On February 21 and March 21 – 22, 2021, the Extreme Ultraviolet Imager (EUI) onboard Solar Orbiter observed three prominence eruptions. The eruptions were associated with coronal mass ejections (CMEs) observed by Metis, Solar Orbiter’s coronagraph. All three eruptions were also observed by instruments onboard the Solar–TErrestrial RElations Observatory (Ahead; STEREO-A), the Solar Dynamics Observatory (SDO), and the Solar and Heliospheric Observatory (SOHO). Here we present an analysis of these eruptions. We investigate their morphology, direction of propagation, and 3D properties. We demonstrate the success of applying two 3D reconstruction methods to three CMEs and their corresponding prominences observed from three perspectives and different distances from the Sun. This allows us to analyze the evolution of the events, from the erupting prominences low in the corona to the corresponding CMEs high in the corona. We also study the changes in the global magnetic field before and after the eruptions and the magnetic field configuration at the site of the eruptions using magnetic field extrapolation methods. This work highlights the importance of multi-perspective observations in studying the morphology of the erupting prominences, their source regions, and associated CMEs. The upcoming Solar Orbiter observations from higher latitudes will help to constrain this kind of study better.Fil: Mierla, Marilena. Royal Observatory Of Belgium (rob);Fil: Cremades Fernandez, Maria Hebe. Universidad de Mendoza. Facultad de Ingenieria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Andretta, Vincenzo. Istituto Nazionale di Astrofisica; ItaliaFil: Chifu, Iulia. Universität Göttingen; AlemaniaFil: Zhukov, Andrei N.. Royal Observatory Of Belgium (rob);Fil: Susino, Roberto. Istituto Nazionale di Astrofisica; ItaliaFil: Auchère, Frédéric. Universite Paris-saclay (universite Paris-saclay);Fil: Vourlidas, Angelos. University Johns Hopkins; Estados UnidosFil: Talpeanu, Dana Camelia. Royal Observatory Of Belgium (rob);Fil: Rodriguez, Luciano. Royal Observatory Of Belgium (rob);Fil: Janssens, Jan. Royal Observatory Of Belgium (rob);Fil: Nicula, Bogdan. Royal Observatory Of Belgium (rob);Fil: Aznar Cuadrado, Regina. Max-Planck-Institut für Sonnensystemforschung; AlemaniaFil: Berghmans, David. Royal Observatory Of Belgium (rob);Fil: Bemporad, Alessandro. Istituto Nazionale di Astrofisica; ItaliaFil: D’Huys, Elke. Royal Observatory Of Belgium (rob);Fil: Dolla, Laurent. Royal Observatory Of Belgium (rob);Fil: Gissot, Samuel. Royal Observatory Of Belgium (rob);Fil: Jerse, Giovanna. Royal Observatory Of Belgium (rob);Fil: Kraaikamp, Emil. Royal Observatory Of Belgium (rob);Fil: Long, David M.. The Queens University of Belfast; IrlandaFil: Mampaey, Benjamin. Royal Observatory Of Belgium (rob);Fil: Möstl, Christian. Austrian Space Weather Office; AustriaFil: Pagano, Paolo. Università degli Studi di Palermo; Italia. Istituto Nazionale di Astrofisica; ItaliaFil: Parenti, Susanna. Universite Paris-saclay (universite Paris-saclay);Fil: West, Matthew J.. Southwest Research Institute.; Estados UnidosFil: Podladchikova, Olena. National Polytechnic University of Ukraine; Ucrania. Leibniz Institute for Astrophysics Potsdam; AlemaniaFil: Romoli, Marco. Università di Firenze; Italia. Istituto Nazionale di Astrofisica; ItaliaFil: Sasso, Clementina. Istituto Nazionale di Astrofisica; ItaliaFil: Stegen, Koen. Royal Observatory Of Belgium (rob);Fil: Teriaca, Luca. Max-Planck-Institut für Sonnensystemforschung; AlemaniaFil: Thompson, William. National Aeronautics and Space Administration; Estados UnidosFil: Verbeeck, Cis. Royal Observatory Of Belgium (rob);Fil: Davies, Emma. University of New Hampshire; Estados Unido

Firefly: The Case for a Holistic Understanding of the Global Structure and Dynamics of the Sun and the Heliosphere

This white paper is on the HMCS Firefly mission concept study. Firefly focuses on the global structure and dynamics of the Sun's interior, the generation of solar magnetic fields, the deciphering of the solar cycle, the conditions leading to the explosive activity, and the structure and dynamics of the corona as it drives the heliosphere