Using machine learning to identify magnetic reconnection in two-dimensional simulations

2020 ◽  
Author(s):  
Andong Hu ◽  
Jannis Teunissen ◽  
Manuela Sisti ◽  
Francesco Califano ◽  
Jérémy Dargent ◽  
...  
Keyword(s):  
Machine Learning ◽  
Solar Wind ◽  
Magnetic Reconnection ◽  
Solar Wind Plasma ◽  
Space Physics ◽  
Electron Velocity ◽  
Two Dimensional ◽  
The European Union ◽  
Horizon 2020 ◽  
Research And Innovation

<div>The understanding of fundamental processes at play in a collisionless plasmas such as the solar wind, is a frontier problem in space physics. We investigate here the occurrence of magnetic reconnection in a plasma with parameters corresponding to solar wind plasma and its interplay with a fully-developed turbulent state. Ongoing magnetic reconnection can, at the moment, be accurately identified only by humans. Therefore, as a first step, the goal of this study is to present a new method to automatically recognise reconnection events in the output of two-dimensional HVM (Hybrid Vlasov Maxwell) simulations where ions evolve by solving the Vlasov equation and the electrons are treated as a fluid with mass. A large dataset with labelled reconnection events was prepared, including parameters such as the magnetic field, the electron velocity field and the current density. We consider two types of machine learning models: classical approaches using on physics-based features, and convolutional neural networks (CNNs). We will investigate which approach performs better, and which input variables are most relevant. In addition, we will try to categorize magnetic reconnection regions (current sheets). This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 776262 (AIDA, www.aida-space.eu).</div>

Using clustering techniques for magnetic reconnection detection

2021 ◽  
Author(s):  
Manuela Sisti ◽  
Francesco Finelli ◽  
Giorgio Pedrazzi ◽  
Matteo Faganello ◽  
Francesco Califano ◽  
...  
Keyword(s):  
Machine Learning ◽  
Magnetic Reconnection ◽  
Theoretical Models ◽  
The European Union ◽  
Clustering Techniques ◽  
Horizon 2020 ◽  
Research And Innovation ◽  
Typical Data ◽  
Set Up ◽  
The One

<p>The formation of coherent current structures in turbulent collisionless magnetized plasmas and their disruption through magnetic reconnection has been extensively studied in past years via in situ observations, numerical simulations, and theoretical models. Presently there is no automatic verified way to detect reconnection events so that only an accurate human analysis can be performed. We set-up a machine learning unsupervised technique aimed at automatically detecting the presence of current sheet (CS) magnetic structures where reconnection is occurring. We make use of clustering techniques as KMeans and DBscan, and compare their efficiency to that of simpler methods which do not use machine learning but are only based on thresholds on important physical quantities. The unsupervised machine learning method turns out to be the one with the best performance. We applied these techniques to 2D kinetic HVM (Hybrid Vlasov Maxwell) plasma turbulence simulations, where ions evolve by solving the Vlasov equation while the electrons are treated as a fluid. Electron inertia is included. We are presently working on adapting our techniques to 1D time series extracted from our simulations aiming at reproducing typical data measured by satellites. This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 776262 (AIDA, www.aida-space.eu).</p>

The low-energy ion event on 2020 June 19 measured by Solar Orbiter

2021 ◽  
Author(s):  
Angels Aran ◽  
Daniel Pacheco ◽  
Monica Laurenza ◽  
Nicolas Wijsen ◽  
Evangelia Samara ◽  
...  
Keyword(s):  
Solar Wind ◽  
Energy Range ◽  
Extreme Ultraviolet ◽  
Solar Rotation ◽  
Complex Structure ◽  
Forbush Decrease ◽  
Solar Wind Plasma ◽  
Low Energy ◽  
The European Union ◽  
Horizon 2020

<p>Shortly after reaching the first perihelion, the Energetic Particle Detector (EPD) onboard Solar Orbiter measured a low-energy (<1 MeV/nuc) ion event whose duration varied with the energy of the particles. The increase above pre-event intensity levels was detected early on June 19 for ions in the energy range from ~50 keV to ~1 MeV and lasted up to ~12:00 UT on June 20. In the energy range from ~10 keV to < 40 keV, the ion event spanned from June 18 to 21. This latter low-energy ion intensity enhancement coincided with a two-step Forbush decrease (FD) as displayed in the EPD > 17 MeV/nuc ion measurements. On the other hand, no electron increases were detected. As seen from 1 au, there is no clear evidence of solar activity from the visible disk that could be associated with the origin of this ion event. We hypothesize about the origin of this event as due to either a possible solar eruption occurring behind the visible part of the Sun or to an interplanetary spatial structure. We use interplanetary magnetic field data from the Solar Orbiter Magnetometer (MAG), solar wind electron density derived from measurements of the Solar Orbiter Radio and Plasma Waves (RPW) instrument to specify the in-situ solar wind conditions where the ion event was observed. In addition, we use solar wind plasma measurements from the Solar Orbiter Solar Wind Analyser (SWA) suite gathered during the following solar rotation, for comparison purposes. In order to seek for possible associated solar sources, we use images from the Extreme Ultraviolet Imager (EUI) instrument onboard Solar Orbiter. Together with the lack of electron observations and Type III radio bursts, the simultaneous response of the ion intensity-time profiles at various energies indicates an interplanetary source for the particles. The two-step FD shape observed during this event suggests that the first step early on June 18 was due to a transient structure, whereas the second step on June 19, together with the ~50 –1000 keV/nuc ion enhancement, was due to a solar wind stream interaction region. The observation of a similar FD in the next solar rotation favours this interpretation, although a more complex structure cannot be discarded due to the lack of concurrent solar wind temperature and velocity observations.</p><p>Different parts of this research have received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870405 (EUHFORIA 2.0) and grant agreement No 01004159 (SERPENTINE).</p>

Improving CME evolution and arrival predictions with AMR and grid stretching in EUHFORIA

2021 ◽  
Author(s):  
Tinatin Baratashvili ◽  
Christine Verbeke ◽  
Nicolas Wijsen ◽  
Emmanuel Chané ◽  
Stefaan Poedts
Keyword(s):  
Solar Wind ◽  
Adaptive Mesh Refinement ◽  
Adaptive Mesh ◽  
Mhd Equations ◽  
Efficiency Gain ◽  
The European Union ◽  
Interplanetary Shocks ◽  
Horizon 2020 ◽  
Research And Innovation ◽  
Speed Up

<p>Coronal Mass Ejections (CMEs) are the main drivers of interplanetary shocks and space weather disturbances. Strong CMEs directed towards Earth can cause severe damage to our planet. Predicting the arrival time and impact of such CMEs can enable to mitigate the damage on various technological systems on Earth. </p><p>We model the inner heliospheric solar wind and the CME propagation and evolution within a new heliospheric model based on the MPI-AMRVAC code. It is crucial for such a numerical tool to be highly optimized and efficient, in order to produce timely forecasts. Our model solves the ideal MHD equations to obtain a steady state solar wind configuration in a reference frame corotating with the Sun. In addition, CMEs can be modelled by injecting a cone CME from the inner boundary (0.1 AU).</p><p>Advanced techniques, such as grid stretching and Adaptive Mesh Refinement (AMR) are employed in the simulation. Such methods allow for high(er) spatial resolution in the numerical domain, but only where necessary or wanted. As a result, we can obtain a detailed, highly resolved image at the (propagating) shock areas, without refining the whole domain.</p><p>These techniques guarantee more efficient simulations, resulting in optimised computer memory usage and a significant speed-up. The obtained speed-up, compared to the original approach with a high-resolution grid everywhere, varies between a factor of 45 - 100 depending on the domain configuration. Such efficiency gain is momentous for the mitigation of the possible damage and allows for multiple simulations with different input parameters configurations to account for the uncertainties in the measurements to determine them. The goal of the project is to reproduce the observed results, therefore, the observable variables, such as speed, density, etc., are compared to the same type of results produced by the existing (non-stretched, single grid) EUropean Heliospheric FORecasting Information Asset (EUHFORIA) model and observational data for a particular event on 12th of July, 2012. The shock features are analyzed and the results produced with the new heliospheric model are in agreement with the existing model and observations, but with a significantly better performance. </p><p> </p><p><strong>This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870405 (EUHFORIA 2.0).</strong></p>

Modeling the Sun – Earth propagation of solar disturbances for the H2020 SafeSpace project

2021 ◽  
Author(s):  
Benoit Lavraud ◽  
Rui Pinto ◽  
Rungployphan Kieokaew ◽  
Evangelia Samara ◽  
Stefaan Poedts ◽  
...  
Keyword(s):  
Solar Wind ◽  
Interplanetary Space ◽  
Coronal Magnetic Field ◽  
Physical Parameters ◽  
The European Union ◽  
Horizon 2020 ◽  
Research And Innovation ◽  
Reconstruction Methods ◽  
Solar Disturbances ◽  
Magnetic Field Computation

<p>We present the solar wind forecast pipeline that is being implemented as part of the H2020 SafeSpace project. The Goal of this project is to use several tools in a modular fashion to address the physics of Sun – interplanetary space – Earth’s magnetosphere. This presentation focuses on the part of the pipeline that is dedicated to the forecasting – from solar measurements – of the solar wind properties at the Lagrangian L1 point. The modeling pipeline puts together different mature research models: determination of the background coronal magnetic field, computation of solar wind acceleration profiles (1 to 90 solar radii), propagation across the heliosphere (for regular solar wind, CIRs and CMEs), and comparison to spacecraft measurements. Different magnetogram sources (WSO, SOLIS, GONG, ADAPT) can be combined, as well as coronal field reconstruction methods (PFSS, NLFFF), wind (MULTI-VP) and heliospheric propagation models (CDPP 1D MHD, EUHFORIA). We aim at providing a web-based service that continuously supplies a full set of bulk physical parameters of the solar wind at 1 AU several days in advance, at a time cadence compatible with space weather applications. This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870437.</p>

scholarly journals A self-consistent simulation of proton acceleration and transport near a high-speed solar wind stream

2021 ◽  
Author(s):  
Nicolas Wijsen ◽  
Evangelia Samara ◽  
Àngels Aran ◽  
David Lario ◽  
Jens Pomoell ◽  
...  
Keyword(s):  
Solar Wind ◽  
Energetic Particle ◽  
High Speed ◽  
Three Dimensional ◽  
Acceleration Process ◽  
Solar Wind Stream ◽  
The European Union ◽  
Horizon 2020 ◽  
Compression Waves ◽  
Research And Innovation

<p>Solar wind stream interaction regions (SIRs)  are often characterised by energetic ion enhancements. The mechanisms accelerating these particles as well as the locations where the acceleration occurs, remains debated. Here, we report the findings of a simulation of a SIR-event observed by Parker Solar Probe at 0.56 au and the Solar Terrestrial Relations Observatory-Ahead at 0.96 au in September 2019 when both spacecraft were approximately radially aligned with the Sun. The simulation reproduces the solar wind configuration and the energetic particle enhancements observed by both spacecraft. Our results show that the energetic particles are produced at the compression waves associated with the SIR and that the suprathermal tail of the solar wind is a good candidate to provide the seed population for particle acceleration. The simulation confirms that the acceleration process does not require shock waves and can already commence within Earth's orbit, with an energy dependence on the precise location where particles are accelerated. The three-dimensional configuration  of the solar wind streams strongly modulates the energetic particle distributions, illustrating the necessity of advanced models to understand  these particle events.</p><p>This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870405 (EUHFORIA 2.0).</p><p> </p>

The Dynamic Time Warping as a means to assess modeled solar wind time series

2021 ◽  
Author(s):  
Evangelia Samara ◽  
Emmanuel Chane ◽  
Brecht Laperre ◽  
Christine Verbeke ◽  
Manuela Temmer ◽  
...  
Keyword(s):  
Time Series ◽  
Solar Wind ◽  
Dynamic Time Warping ◽  
Optimal Alignment ◽  
The European Union ◽  
Time Warping ◽  
Horizon 2020 ◽  
Research And Innovation ◽  
Single Number ◽  
Dynamic Time

<p>In this work, the Dynamic Time Warping (DTW) technique is presented as an alternative method to assess the performance of modeled solar wind time series at Earth (or at any other point in the heliosphere). This method can quantify how similar two time series are by providing a temporal alignment between them, in an optimal way and under certain restrictions. It eventually estimates the optimal alignment between an observed and a modeled series, which we call the warping path, by providing a single number, the so-called DTW cost. A description on the reasons why DTW should be applied as a metric for the assessment of solar wind time series, is presented. Furthermore, examples on how exactly the technique is applied to our modeled solar wind datasets with EUHFORIA, are shown and discussed.</p><p><span><span><em>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870437 (SafeSpace).</em></span></span></p>

Current structures and reconnection events analysis in hybrid-kinetic turbulence simulations using unsupervised machine learning

2020 ◽  
Author(s):  
Manuela Sisti ◽  
Francesco Califano ◽  
Matteo Faganello ◽  
Giorgio Pedrazzi ◽  
Francesca Delli Ponti ◽  
...  
Keyword(s):  
Machine Learning ◽  
Theoretical Models ◽  
Data Sets ◽  
The European Union ◽  
Horizon 2020 ◽  
Magnetic Structures ◽  
Research And Innovation ◽  
In Situ Observations ◽  
Space Data

<div>Kinetic turbulence in magnetized space plasmas has been extensively studied via in situ observations, numerical simulations and theoretical models. In this context, a key point concerns the formation of coherent current structures and their disruption through magnetic reconnection. As of today, reconnection can only be accurately identified by human analysis. We are setting-up a machine learning unsupervised technique aimed at automatically detecting the presence of current sheet (CS) magnetic structures where reconnection is occurring. We make use of anomaly detection and clustering techniques. We are applying these techniques to 2D kinetic HVM (Hybrid Vlasov Maxwell) plasma turbulence simulations, where ions evolve by solving the Vlasov equation and the electrons are treated as a fluid. Electron inertia is included. The final goal is to build up an algorithm able to select data subsets starting from big data sets where potentially interesting physical processes are at play. After that, we intend to extend the technique to space data and to 3D simulation data.</div><div>This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 776262 (AIDA, www.aida-space.eu).</div>

Coordinated observations of relativistic electron enhancements following an HSS period 

2021 ◽  
Author(s):  
Afroditi Nasi ◽  
Ioannis A. Daglis ◽  
Christos Katsavrias ◽  
Ingmar Sandberg ◽  
Wen Li ◽  
...  
Keyword(s):  
Solar Wind ◽  
Relativistic Electron ◽  
High Speed ◽  
Geomagnetic Storms ◽  
Wind Pressure ◽  
The European Union ◽  
Horizon 2020 ◽  
Research And Innovation ◽  
Wave Measurements ◽  
Substorm Activity

<p>During the second half of 2019, a sequence of solar wind high-speed streams (V<sub>SW</sub> ≥ 600 km/s)  impacted the magnetosphere, resulting in a series of recurrent, relatively weak, geomagnetic storms (Dst<sub>min</sub> ≥ - 80 nT). During one of these storms, a longer-lasting solar wind pressure pulse and intense substorm activity were also recorded (AL ≤ - 1600 nT on August 31 and September 1).</p><p>We use particle measurements from the Van Allen Probes, Arase and Galileo 207, 215 satellites, to investigate this event; all spacecraft observed a significant enhancement of relativistic electron fluxes. We also use ULF and chorus wave measurements, as well as interplanetary parameters, for a detailed investigation of this event and of the acceleration mechanisms involved.</p><p>This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870437 for the SafeSpace project.</p>

Monitoring and assessment of an oil spill event with very high resolution tools. 

2021 ◽  
Author(s):  
Ana M. Mancho ◽  
Guillermo García-Sánchez ◽  
Antonio G. Ramos ◽  
Josep Coca ◽  
Begoña Pérez-Gómez ◽  
...  
Keyword(s):  
High Resolution ◽  
Oil Spill ◽  
In Situ Observation ◽  
The European Union ◽  
Horizon 2020 ◽  
Research And Innovation ◽  
Port Authorities ◽  
Different Sources ◽  
Very High

<p>This presentation discusses a downstream application from Copernicus Services, developed in the framework of the IMPRESSIVE project, for the monitoring of  the oil spill produced after the crash of the ferry “Volcan de Tamasite” in waters of the Canary Islands on the 21<sup>st</sup> of April 2017. The presentation summarizes the findings of [1] that describe a complete monitoring of the diesel fuel spill, well-documented by port authorities. Complementary information supplied by different sources enhances the description of the event. We discuss the performance of very high resolution hydrodynamic models in the area of the Port of Gran Canaria and their ability for describing the evolution of this event. Dynamical systems ideas support the comparison of different models performance. Very high resolution remote sensing products and in situ observation validate the description.</p><p>Authors acknowledge support from IMPRESSIVE a project funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 821922. SW acknowledges the support of ONR Grant No. N00014-01-1-0769</p><p><strong>References</strong></p><p>[1] G.García-Sánchez, A. M. Mancho, A. G. Ramos, J. Coca, B. Pérez-Gómez, E. Álvarez-Fanjul, M. G. Sotillo, M. García-León, V. J. García-Garrido, S. Wiggins. Very High Resolution Tools for the Monitoring and Assessment of Environmental Hazards in Coastal Areas.  Front. Mar. Sci. (2021) doi: 10.3389/fmars.2020.605804.</p>

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