Signatures of the impact of flare ejected plasma on the photosphere of a sunspot light-bridge

We investigate the properties of a sunspot light-bridge, focusing on the changes produced by the impact of a plasma blob ejected from a C-class flare. We observed a sunspot in active region NOAA 12544 using spectropolarimetric raster maps of the four Fe I lines around 15655 \AA\ with the GREGOR Infrared Spectrograph (GRIS), narrow-band intensity images sampling the Fe I 6173 \AA\ line with the GREGOR Fabry-P\'erot Interferometer (GFPI), and intensity broad band images in G-band and Ca II H band with the High-resolution Fast Imager (HiFI). All these instruments are located at the GREGOR telescope at the Observatorio del Teide, Tenerife, Spain. The data cover the time before, during, and after the flare event. The analysis is complemented with Atmospheric Imaging Assembly (AIA) and Helioseismic and Magnetic Imager (HMI) data from the Solar Dynamics Observatory (SDO). The physical parameters of the atmosphere at differents heights were inferred using spectral-line inversion techniques. We identify photospheric and chromospheric brightenings, heating events, and changes in the Stokes profiles associated to the flare eruption and the subsequent arrival of the plasma blob to the light bridge, after traveling along an active region loop. The measurements suggest that these phenomena are the result of reconnection events driven by the interaction of the plasma blob with the magnetic field topology of the light bridge.Comment: Accepted for publication in A&

Accelerating Multiframe Blind Deconvolution via Deep Learning

Ground-based solar image restoration is a computationally expensive procedure that involves nonlinear optimization techniques. The presence of atmospheric turbulence produces perturbations in individual images that make it necessary to apply blind deconvolution techniques. These techniques rely on the observation of many short exposure frames that are used to simultaneously infer the instantaneous state of the atmosphere and the unperturbed object. We have recently explored the use of machine learning to accelerate this process, with promising results. We build upon this previous work to propose several interesting improvements that lead to better models. As well, we propose a new method to accelerate the restoration based on algorithm unrolling. In this method, the image restoration problem is solved with a gradient descent method that is unrolled and accelerated aided by a few small neural networks. The role of the neural networks is to correct the estimation of the solution at each iterative step. The model is trained to perform the optimization in a small fixed number of steps with a curated dataset. Our findings demonstrate that both methods significantly reduce the restoration time compared to the standard optimization procedure. Furthermore, we showcase that these models can be trained in an unsupervised manner using observed images from three different instruments. Remarkably, they also exhibit robust generalization capabilities when applied to new datasets. To foster further research and collaboration, we openly provide the trained models, along with the corresponding training and evaluation code, as well as the training dataset, to the scientific community.Comment: 26 pages, 9 figures, accepted for publication in Solar Physic

How different Fermi surface maps emerge in photoemission from Bi2212

We report angle-resolved photoemission spectra (ARPES) from the Fermi energy ($E_F$) over a large area of the ($k_x,k_y$) plane using 21.2 eV and 32 eV photons in two distinct polarizations from an optimally doped single crystal of Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ (Bi2212), together with extensive first-principles simulations of the ARPES intensities. The results display a wide-ranging level of accord between theory and experiment and clarify how myriad Fermi surface (FS) maps emerge in ARPES under various experimental conditions. The energy and polarization dependences of the ARPES matrix element help disentangle primary contributions to the spectrum due to the pristine lattice from those arising from modulations of the underlying tetragonal symmetry and provide a route for separating closely placed FS sheets in low dimensional materials.Comment: submitted to PR

Determining the dynamics and magnetic fields in He I 10830 \r{A} during a solar filament eruption

We investigate the dynamics and magnetic properties of the plasma, such as line-of-sight velocity (LOS), optical depth, vertical and horizontal magnetic fields, belonging to an erupted solar filament. The filament eruption was observed with the GREGOR Infrared Spectrograph (GRIS) at the 1.5-meter GREGOR telescope on 2016 July 3. Three consecutive full-Stokes slit-spectropolarimetric scans in the He I 10830 \r{A} spectral range were acquired. The Stokes I profiles were classified using the machine learning k-means algorithm and then inverted with different initial conditions using the HAZEL code. The erupting-filament material presents the following physical conditions: (1) ubiquitous upward motions with peak LOS velocities of ~73 km/s; (2) predominant large horizontal components of the magnetic field, on average, in the range of 173-254 G, whereas the vertical components of the fields are much lower, on average between 39-58 G; (3) optical depths in the range of 0.7-1.1. The average azimuth orientation of the field lines between two consecutive raster scans (<2.5 minutes) remained constant. The analyzed filament eruption belonged to the fast rising phase, with total velocities of about 124 km/s. The orientation of the magnetic field lines does not change from one raster scan to the other, indicating that the untwisting phase has not started yet. The untwisting seems to start about 15 min after the beginning of the filament eruption.Comment: Accepted for publication in Astronomy & Astrophysics, 12 pages, 13 figures, 1 appendix, 2 online movie

Towards the Identification and Classification of Solar Granulation Structures Using Semantic Segmentation

Solar granulation is the visible signature of convective cells at the solar surface. The granulation cellular pattern observed in the continuum intensity images is characterised by diverse structures e.g., bright individual granules of hot rising gas or dark intergranular lanes. Recently, the access to new instrumentation capabilities has given us the possibility to obtain high-resolution images, which have revealed the overwhelming complexity of granulation (e.g., exploding granules and granular lanes). In that sense, any research focused on understanding solar small-scale phenomena on the solar surface is sustained on the effective identification and localization of the different resolved structures. In this work, we present the initial results of a proposed classification model of solar granulation structures based on neural semantic segmentation. We inspect the ability of the U-net architecture, a convolutional neural network initially proposed for biomedical image segmentation, to be applied to the dense segmentation of solar granulation. We use continuum intensity maps of the IMaX instrument onboard the Sunrise I balloon-borne solar observatory and their corresponding segmented maps as a training set. The training data have been labeled using the multiple-level technique (MLT) and also by hand. We performed several tests of the performance and precision of this approach in order to evaluate the versatility of the U-net architecture. We found an appealing potential of the U-net architecture to identify cellular patterns in solar granulation images reaching an average accuracy above 80% in the initial training experiments

Magnetic field fluctuations in the shocked umbral chromosphere

Several studies have reported magnetic field fluctuations associated with umbral shock waves. We aim to study the properties and origin of magnetic field fluctuations in the umbral chromosphere. Temporal series of spectropolarimetric observations were acquired with the GREGOR telescope. The chromospheric and photospheric conditions were derived from simultaneous inversions of the He I 10830 \AA\ triplet and the Si I 10827 \AA\ line using HAZEL2. The oscillations are interpreted using wavelet analysis and context information from UV observations acquired with SDO/AIA and IRIS. The chromospheric magnetic field shows strong fluctuations in the sunspot umbra, with peak field strengths up to 2900 G. Magnetic field and velocity umbral oscillations exhibit a strong coherence, with the magnetic field lagging the shock fronts detected in the velocity fluctuations. This points to a common origin of the fluctuations in both parameters, whereas the analysis of the phase shift between photospheric and chromospheric velocity is consistent with upwards wave propagation. These results suggest that the strong inferred magnetic field fluctuations are caused by changes in the response height of the He I 10830 \AA\ line to the magnetic field, which is sensitive to high photospheric layers after the shock fronts. The coronal activity seen in EUV data could possibly have some impact on the inferred fluctuations, but it is not the main driver of the magnetic field oscillations since they are found before EUV events take place. Chromospheric magnetic field fluctuations measured with the He I 10830 \AA\ triplet arise due to variations in the opacity of the line. After shocks produced by slow magnetoacoustic waves, the response of the line to the magnetic field can be shifted down to the upper photosphere. This is seen as remarkably large fluctuations in the line of sight magnetic field strength.Comment: Accepted for publication in A&A. Abstract abridged due to arXiv's 1920 character limi

Matrix Element and Strong Electron Correlation Effects in ARPES from Cuprates

We discuss selected results from our recent work concerning the ARPES (angle-resolved photoemission) spectra from the cuprates. Our focus is on developing an understanding of the effects of the ARPES matrix element and those of strong electron correlations in analyzing photointensities. With simulations on Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ (Bi2212), we show that the ARPES matrix element possesses remarkable selectivity properties, such that by tuning the photon energy and polarization, emission from the bonding or the antibonding states can be enhanced. Moreover, at low photon energies (below 25 eV), the Fermi surface (FS) emission is dominated by transitions from just the O-atoms in the CuO$_2$ planes. In connection with strong correlation effects, we consider the evolution with doping of the FS of Nd$_{2-x}$Ce$_x$CuO$_{4\pm\delta}$ (NCCO) in terms of the $t$-$t'$-$U$ Hubbard model Hamiltonian. We thus delineate how the FS evolves on electron doping from the insulating state in NCCO. The Mott pseudogap is found to collapse around optimal doping suggesting the existence of an associated quantum critical point.Comment: 5 pages, 4 figures, accepted to be published in Journal of Physics and Chemistry of Solid