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

Total electron content PCA-NN model for middle latitudes

A regression-based model was previously developed to forecast the total electron content (TEC) at middle latitudes. We present a more sophisticated model using neural networks (NN) instead of linear regression. This regional model prototype simulates and forecasts TEC variations in relation to space weather conditions. The development of a prototype consisted of the selection of the best set of predictors, NN architecture and the length of the input series. Tests made using the data from December 2014 to June 2018 show that the PCA-NN model based on a simple feed-forward NN with a very limited number (up to 6) of space weather predictors performs better than the PCA-MRM model that uses up to 27 space weather predictors. The prototype is developed on a TEC series obtained from a GNSS receiver at Lisbon airport and tested on TEC series from three other locations at middle altitudes of the Eastern North Atlantic. Conclusions on the dependence of the forecast quality on longitude and latitude are made.Comment: arXiv admin note: text overlap with arXiv:2201.0347

Mass-luminosity relation for FGK main sequence stars: metallicity and age contributions

The stellar mass-luminosity relation (MLR) is one of the most famous empirical "laws", discovered in the beginning of the 20th century. MLR is still used to estimate stellar masses for nearby stars, particularly for those that are not binary systems, hence the mass cannot be derived directly from the observations. It's well known that the MLR has a statistical dispersion which cannot be explained exclusively due to the observational errors in luminosity (or mass). It is an intrinsic dispersion caused by the differences in age and chemical composition from star to star. In this work we discuss the impact of age and metallicity on the MLR. Using the recent data on mass, luminosity, metallicity, and age for 26 FGK stars (all members of binary systems, with observational mass-errors <= 3%), including the Sun, we derive the MLR taking into account, separately, mass-luminosity, mass-luminosity-metallicity, and mass-luminosity-metallicity-age. Our results show that the inclusion of age and metallicity in the MLR, for FGK stars, improves the individual mass estimation by 5% to 15%.Comment: 7 pages, 4 figures, 1 table, accepted in Astrophysics and Space Scienc

Solar filaments: characteristics and evolution

Este trabalho tem como principal objectivo o estudo dos flamentos solares, começando com um estudo estatístico que levou à criação e implementação de um modelo computacional. Os estudos estatísticos realizados estão relacionados com a longitude e latitude de Carrington, com o comprimento, a curvatura e a orientação dos filamentos. Durante a realização do estudo estatístico referente à orientação levantou-se a necessidade da elaboração do simulador. O simulador permitiu-nos verifcar que as alterações na distribuição da orientação observada eram causadas por efeitos de perspectiva. Outro elemento de interesse que podemos extrair do simulador é a distribuição da orientação de aparecimento dos filamentos, distribuição esta que até à data, tanto quanto pude verificar na bibliografia, não foi alvo de publicação

Revisiting the mass- and radius-luminosity relations for FGK main-sequence stars

Scaling relations are very useful tools for estimating unknown stellar quantities. Within this framework, eclipsing binaries are ideal for this goal because their mass and radius are known with a very good level of accuracy, leading to improved constraints on the models. We aim to provide empirical relations for the mass and radius as function of luminosity, metallicity, and age. We investigate, in particular, the impact of metallicity and age on those relations. We used a multi-dimensional fit approach based on the data from DEBCat, an updated catalogue of eclipsing binary observations such as mass, radius, luminosity, effective temperature, gravity, and metallicity. We used the {PARAM web interface for the Bayesian estimation of stellar parameters, along with} the stellar evolutionary code MESA to estimate the binary age, assuming a coeval hypothesis for both members. We derived the mass and radius-luminosity-metallicity-age relations using 56 stars, {with metallicity and mass in the range -0.34<[Fe/H]<0.27 and 0.66<M/M{_\odot}<1.8}. With that, the observed mass and radius are reproduced with an accuracy of 3.5% and 5.9%, respectively, which is consistent with the other results in literature. We conclude that including the age in such relations increases the quality of the fit, particularly in terms of the mass, as compared to the radius. On the other hand, as other authors have noted, we observed an higher dispersion on the mass relation than in that of the radius. We propose that this is due to a stellar age effect.Comment: 8 pages, 9 figures, Accepted for publication on Astronomy and Astrophysic

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

Testing the Accuracy of Coimbra Astronomical Observatory Solar Filament Historical Series (1929–1941)

The present work aims to validate the positions of solar filaments published in the Annals of Coimbra University Astronomical Observatory, currently the Geophysical and Astronomical Observatory of the University of Coimbra, corresponding to years 1929 to 1941. The published Stonyhurst positions were obtained by an original method devised in the early 20th century that used a spherical calculator instrument, a wood-made model of the Sun. We used the digital images of the original spectroheliograms to measure the positions of the filaments, and heliographic coordinates were determined with the routines implemented in the Python package Sunpy. The correlation coefficients between both sets of coordinates are positive and highly significant. The results validate the method used at the Coimbra observatory and the published data. We conclude that the Coimbra solar filament catalogues are reliable and can therefore be considered for future solar activity studies

Exploring Magnetic Loops and Serpentine Fields in the Quiet Sun with the GRIS-IFU

Synthetic observations produced from radiative magnetohydrodynamic simulations have predicted that higher polarization fractions in the quiet solar photosphere would be revealed by increasing the total integration time of observations at GREGOR resolutions. We present recently acquired disk center observations of the Fe i 15648.5 Å line obtained with the GREGOR telescope equipped with the GRIS-IFU during excellent seeing conditions, showing exceptionally high polarization fractions. Our observations reveal an internetwork region with a majority (>60%) of magnetized pixels displaying a clear transverse component of the magnetic field. This result is in stark contrast to previous disk center GRIS-IFU observations in this spectral line, which had predominantly vertical magnetic fields in the deep photosphere. At the same time, the median magnetic field strength is weaker than previous GRIS-IFU observations, indicating that the larger fraction of polarization signals cannot be explained by a more active target. We use the Stokes Inversion based on Response functions (SIR) code to analyze the data, performing over 45 million inversions, and interrogate the impact of two conflicting approaches to the treatment of noise on the retrieval of the magnetic inclination and azimuth. We present several case studies of the zoo of magnetic features present in these data, including small-scale magnetic loops that seem to be embedded in a sea of magnetism, and serpentine fields, focusing on regions where full-vector spectropolarimetry has been achieved. We also present a new open-source Python 3 analysis tool, SIR Explorer, which we use to examine the dynamics of these small-scale magnetic features

Magnetic properties of short-lived penumbral microjets

Contributions to the XIV.0 Scientific Meeting (virtual) of the Spanish Astronomical Society, held 13-15 July 2020, online at https://www.sea-astronomia.es/reunion-cientifica-2020, id.208.We investigate the temporal evolution of the polarization properties during penumbral microjets (PMJs). Studying the magnetic properties of these transients requires spectropolarimetric observations with the fastest temporal cadence possible and is currently a challenging task. In this work, we used fast temporal cadence spectropolarimetric measurements of the Ca II 8542 A line from the CRISP instrument at the Swedish 1 m Solar Telescope, and exploited the diagnosis capabilities of this line to retrieve the magnetic field configuration and its evolution at different atmospheric heights during PMJs. Our findings show that the short-lived PMJs are associated to a transient perturbation in the photospheric magnetic field and sometimes they show clear but weaker changes in the chromospheric field as well. Here we describe the different types of evolution that were identified.With funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation SEV-2017-070