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Abstract We present a novel deep generative model, named GenMDI, to improve the temporal resolution of line-of-sight (LOS) magnetograms of solar active regions (ARs) collected by the Michelson Doppler Imager (MDI) on board the Solar and Heliospheric Observatory. Unlike previous studies that focus primarily on spatial super-resolution of MDI magnetograms, our approach can perform temporal super-resolution, which generates and inserts synthetic data between observed MDI magnetograms, thus providing finer temporal structure and enhanced details in the LOS data. The GenMDI model employs a conditional diffusion process, which synthesizes images by considering both preceding and subsequent magnetograms, ensuring that the generated images are not only of high quality but also temporally coherent with the surrounding data. Experimental results show that the GenMDI model performs better than the traditional linear interpolation method, especially in ARs with dynamic evolution in magnetic fields. 

Abstract We present a transformer model, named DeepHalo, to predict the occurrence of halo coronal mass ejections (CMEs). Our model takes as input an active region (AR) and a profile, where the profile contains a time series of data samples in the AR that are collected 24 hr before the beginning of a day, and predicts whether the AR would produce a halo CME during that day. Each data sample contains physical parameters, or features, derived from photospheric vector magnetic field data taken by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. We survey and match CME events in the Space Weather Database Of Notification, Knowledge, Information and the Large Angle and Spectrometric Coronagraph CME Catalog, and we compile a list of CMEs, including halo CMEs and nonhalo CMEs, associated with ARs in the period between 2010 November and 2023 August. We use the information gathered above to build the labels (positive vs. negative) of the data samples and profiles at hand, where the labels are needed for machine learning. Experimental results show that DeepHalo with a true skill statistic (TSS) score of 0.907 outperforms a closely related long short-term memory network with a TSS score of 0.821. To our knowledge, this is the first time that the transformer model has been used for halo CME prediction. 

Abstract We analyze high-resolution observations of an X-1.0 white-light flare, triggered by a filament eruption, on 2022 October 2. The full process of filament formation and subsequent eruption was captured in the Hαpassband by the Visible Imaging Spectrograph (VIS) on board the Goode Solar Telescope (GST) within its center field of view. White-light emissions appear in flare ribbons following the filament eruption and Hαribbon brightening. GST Broadband Filter Imager data show that the continuum intensity, as compared to the nearby quiet-Sun area, has increased by up to 20% in the photospheric TiO band around 7057 Å. The Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory reported 10% contrast enhancement in the continuum near Fei6173 Å line. The separation motion of two white-light kernels is recorded by the high-cadence GST/TiO images and is well accompanied by the motion of the VIS Hαflare ribbon leading edge. One kernel, located in a 150 Gauss field within a granulation area, exhibited an average apparent motion speed of 55 km s⁻¹, which is the highest average speed ever reported. The other kernel drifted at 9 km s⁻¹in an 800 Gauss magnetic field area. Hard X-ray (HXR) emissions reaching up to 300 keV have been observed for this flare. The simultaneous occurrence of high-cadence HXR, microwave, and white-light emissions strongly suggests that the energetic particles from the flare directly contribute to the heating. The inverted HXR energy flux density corresponding to 10% TiO brightening is 2.07 ± 0.23 × 10¹¹erg cm⁻²s⁻¹during the flare peak. 

Abstract Magnetic reconnection is widely believed to be the fundamental process in the solar atmosphere that underlies magnetic energy release and particle acceleration. This process is responsible for the onset of solar flares, coronal mass ejections, and other explosive events (e.g., jets). Here, we report direct imaging of a prolonged plasma/current sheet along with quasiperiodic magnetic reconnection in the solar corona using ultra-high-resolution observations from the 1.6 m Goode Solar Telescope at the Big Bear Solar Observatory and the Solar Dynamics Observatory/Atmospheric Imaging Assembly. The current sheet appeared near a null point in the fan–spine topology and persisted over an extended period (≈20 hr). The length and apparent width of the current sheet were about 6″ and 2″, respectively, and the plasma temperature was ≈10–20 MK. We observed quasiperiodic plasma inflows and outflows (bidirectional jets with plasmoids) at the reconnection site/current sheet. Furthermore, quasiperiodic reconnection at the long-lasting current sheet produced recurrent eruptions (small flares and jets) and contributed significantly to the recurrent impulsive heating of the active region. Direct imaging of a plasma/current sheet and recurrent null-point reconnection for such an extended period has not been reported previously. These unprecedented observations provide compelling evidence that supports the universal model for solar eruptions (i.e., the breakout model) and have implications for impulsive heating of active regions by recurrent reconnection near null points. The prolonged and sustained reconnection for about 20 hr at the breakout current sheet provides new insights into the dynamics and energy release processes in the solar corona. 

Abstract We present observations and analysis of an eruptive M1.5 flare (SOL2014-08-01T18:13) in NOAA active region (AR) 12127, characterized by three flare ribbons, a confined filament between ribbons, and rotating sunspot motions as observed by the Solar Dynamics Observatory. The potential field extrapolation model shows a magnetic topology involving two intersecting quasi-separatrix layers (QSLs) forming a hyperbolic flux tube (HFT), which constitutes the fishbone structure for the three-ribbon flare. Two of the three ribbons show separation from each other, and the third ribbon is rather stationary at the QSL footpoints. The nonlinear force-free field extrapolation model implies the presence of a magnetic flux rope (MFR) structure between the two separating ribbons, which was unclear in the observation. This suggests that the standard reconnection scenario for eruptive flares applies to the two ribbons, and the QSL reconnection for the third ribbon. We find rotational flows around the sunspot, which may have caused the eruption by weakening the downward magnetic tension of the MFR. The confined filament is located in the region of relatively strong strapping field. The HFT topology and the accumulation of reconnected magnetic flux in the HFT may play a role in holding it from eruption. This eruption scenario differs from the one typically known for circular ribbon flares, which is mainly driven by a successful inside-out eruption of filaments. Our results demonstrate the diversity of solar magnetic eruption paths that arises from the complexity of the magnetic configuration. 

Abstract We report a magnetic relaxation process inside a sunspot associated with the evolution of a transient light bridge (LB). From high-resolution imaging and spectro-polarimetric data taken by the 1.6 m Goode Solar Telescope installed at Big Bear Solar Observatory, we observe the evolutionary process of a rapidly evolving LB. The LB is formed as a result of the strong intrusion of filamentary structures with relatively horizontal fields into the vertical umbral field region. A strong current density is detected along a localized region where the magnetic field topology changes rapidly in the sunspot, especially in the boundary region between the LB and the umbra, and bright jets are observed intermittently and repeatedly in the chromosphere along this region through magnetic reconnection. In the second half of our observation, the horizontal component of the magnetic field diminishes within the LB, and the typical convection structure within the sunspot, which manifests itself as umbral dots, is restored. Our findings provide a comprehensive perspective not only on the evolution of an LB itself but also on its impacts in the neighboring regions, including the chromospheric activity and the change of magnetic energy of a sunspot. 

Abstract We propose a novel deep learning framework, named SYMHnet, which employs a graph neural network and a bidirectional long short‐term memory network to cooperatively learn patterns from solar wind and interplanetary magnetic field parameters for short‐term forecasts of the SYM‐H index based on 1‐ and 5‐min resolution data. SYMHnet takes, as input, the time series of the parameters' values provided by NASA's Space Science Data Coordinated Archive and predicts, as output, the SYM‐H index value at time pointt + whours for a given time pointtwherewis 1 or 2. By incorporating Bayesian inference into the learning framework, SYMHnet can quantify both aleatoric (data) uncertainty and epistemic (model) uncertainty when predicting future SYM‐H indices. Experimental results show that SYMHnet works well at quiet time and storm time, for both 1‐ and 5‐min resolution data. The results also show that SYMHnet generally performs better than related machine learning methods. For example, SYMHnet achieves a forecast skill score (FSS) of 0.343 compared to the FSS of 0.074 of a recent gradient boosting machine (GBM) method when predicting SYM‐H indices (1 hr in advance) in a large storm (SYM‐H = −393 nT) using 5‐min resolution data. When predicting the SYM‐H indices (2 hr in advance) in the large storm, SYMHnet achieves an FSS of 0.553 compared to the FSS of 0.087 of the GBM method. In addition, SYMHnet can provide results for both data and model uncertainty quantification, whereas the related methods cannot. 

Abstract We used 29 high-resolution line-of-sight magnetograms acquired with the Goode Solar Telescope (GST) in a quiet-Sun area to extrapolate a series of potential field configurations and study their time variations. The study showed that there are regions that consistently exhibit changes in loop connectivity, whereas other vast areas do not show such changes. Analysis of the topological features of the potential fields indicates that the photospheric footprint of the separatrix between open- and closed-loop systems closely matches the roots of rapid blue- and redshifted excursions, which are disk counterparts of type II spicules. There is a tendency for the footpoints of the observed H_αfeatures to be cospatial with the footpoints of the loops that most frequently change their connectivity, while the area occupied by the open fields that did not show any significant and persistent connectivity changes is void of prominent jet and spicular activity. We also detected and tracked magnetic elements using the Southwest Automatic Magnetic Identification Suite and GST magnetograms, which allowed us to construct artificial magnetograms and calculate the corresponding potential field configurations. Analysis of the artificial data showed tendencies similar to those found for the observed data. The present study suggests that a significant amount of chromospheric activity observed in the far wings of the H_αspectral line may be generated by reconnecting closed-loop systems and canopy fields consisting of “open” field lines. 

Abstract Coronal mass ejections (CMEs) are massive solar eruptions, which have a significant impact on Earth. In this paper, we propose a new method, called DeepCME, to estimate two properties of CMEs, namely, CME mass and kinetic energy. Being able to estimate these properties helps better understand CME dynamics. Our study is based on the CME catalog maintained at the Coordinated Data Analysis Workshops Data Center, which contains all CMEs manually identified since 1996 using the Large Angle and Spectrometric Coronagraph (LASCO) on board the Solar and Heliospheric Observatory. We use LASCO C2 data in the period between 1996 January and 2020 December to train, validate, and test DeepCME through 10-fold cross validation. The DeepCME method is a fusion of three deep-learning models, namely ResNet, InceptionNet, and InceptionResNet. Our fusion model extracts features from LASCO C2 images, effectively combining the learning capabilities of the three component models to jointly estimate the mass and kinetic energy of CMEs. Experimental results show that the fusion model yields a mean relative error (MRE) of 0.013 (0.009, respectively) compared to the MRE of 0.019 (0.017, respectively) of the best component model InceptionResNet (InceptionNet, respectively) in estimating the CME mass (kinetic energy, respectively). To our knowledge, this is the first time that deep learning has been used for CME mass and kinetic energy estimations. 

Abstract Light bridges (LBs) are narrow structures dividing sunspot umbra, and their role in active region evolution is yet to be explored. We investigated the magnetic structure of the two LBs: a narrow LB (with width ∼810 km) and a considerably wider LB (2475 km) in the active region NOAA 12371. We employed: (1) the high-spatial-resolution spectropolarimetric data obtained by the Near InfraRed Imaging Spectropolarimeter (NIRIS) of the 1.6 m Goode Solar Telescope (GST) for studying the magnetic structure at the photosphere, and (2) the nonlinear force-free field (NLFFF) models, extrapolated from both the photospheric magnetogram from GST/NIRIS and from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory, for studying the three-dimensional (3D) magnetic structure on a larger scale. Our observations reveal the presence of a field-free (or, more precisely, weak-field) region and the different velocity structures inside the two LBs. Analysis of the 3D NLFFF model shows a low-lying magnetic canopy as well as the enhanced current system above the LBs. The substantial difference between the LBs and the umbrae is found in the overall magnetic topology in that the field lines emanating from the two LBs are more twisted than that from the neighboring umbrae.