Photospheric bright points represent the footpoints of magnetic flux tubes, which can guide magnetohydrodynamic (MHD) waves such as torsional Alfvén waves. These waves propagate upward from the photosphere into the upper atmosphere, transporting energy and contributing to plasma heating through their dissipation. This study aims to analyze, from a theoretical perspective, the spectrum of torsional Alfvén waves in solar photospheric flux tubes. The linearized resistive MHD equations are solved in a cylindrical flux tube model whose physical properties vary in the radial direction. The eigenvalues and eigenfunctions of torsional Alfvén waves are computed using analytical and semi-analytical methods for different configurations with increasing levels of complexity. The results show that, under realistic photospheric conditions, a significant number of propagating eigenmodes exist, including internal modes and discretized modes of the Alfvén continuum. These modes are not strictly confined to the interior of the flux tube, and their eigenfunctions extend into the surrounding plasma as well. The results suggest that photospheric convective motions could naturally deposit energy into a broad spectrum of torsional modes capable of propagating upward.
The solar photosphere exhibits a wide range of multi-scale dynamical phenomena, commonly analyzed through Fourier power spectra of velocity fields. However, the physical relevance of these spectra has been questioned, particularly regarding whether scale-dependent power arises from intrinsic dynamics or from edge-related artifacts in the data. In this study, we investigate the origin of power spectra derived from vertical velocity fields obtained in quiet-Sun three-dimensional magnetohydrodynamic (MHD) simulations. A series of controlled numerical experiments is performed. First, intergranular lanes were replaced with sharp edges with a height of -0.2 ^-1 , -2 ^-1 and -5 ^-1 . Subsequently, noise was included with a variety of bin sizes in the intergranular lanes to produce various types of edges. Finally, the resolution was reduced and data were re-binned to a grid size up to 16 times the original one. Our results show that the introduction of edges has a negligible effect on the overall shape and consistency of the power spectra when compared to the original unperturbed data. Noticeable distortions arise only in undersampled datasets, and these effects drastically diminish when statistically significant samples are considered. Complementary Monte Carlo simulations with synthetic data demonstrate that edges induce spurious oscillatory features in spectra of isolated two-dimensional fields, which cancel out when multiple realizations are combined, indicating that such artifacts behave as unsynchronized perturbations. These findings indicate that photospheric velocity power spectra predominantly reflect genuine physical processes rather than edge effects, except in limited cases involving small or poorly sampled datasets. Furthermore, analysis of the positive component of the vertical velocity reveals a more extended power-law range than that of the full vertical velocity, suggesting improved access to inertial-range dynamics relevant to turbulence studies.
The Chinese H α Solar Explorer (CHASE) satellite provided invaluable full-disk H α spectral data, but images from its initial mission phase (before August 2022) suffered from significant defocus blur, limiting their scientific utility. This paper proposes an enhanced Multi-Input Multi-Output U-Net (MIMO-Unet) model to address this blind deconvolution challenge. Because sharp ground-truth counterparts are unavailable for real early-phase CHASE observations, we constructed a physically constrained dataset by applying a Zernike-polynomial-based defocus model to sharp CHASE/HIS observations acquired after the focusing condition became stable. The proposed model enhances the baseline MIMO-Unet by integrating Squeeze-and-Excitation (SE) blocks into the encoder for adaptive channel-wise feature recalibration and an Atrous Spatial Pyramid Pooling (ASPP) module into the feature fusion stage to capture multi-scale context. On the Zernike-simulated CHASE defocus dataset, the proposed method improves PSNR from 27.0169 dB to 33.8707 dB, corresponding to a 6.85 dB gain, and increases SSIM, FSIM, and the multi-fractal texture-based Perception Evaluation (PE) metric by 45.67 α observations, with quantitative validation on Zernike-simulated defocus data and preliminary qualitative tests on real early-phase CHASE observations.
Magnetic helicity and magnetic energy are key to understanding the solar dynamo and eruptions, and their three-dimensional distributions are of great significance. However, how these quantities vary with height remains poorly understood. Moreover, because the three-dimensional distribution depends on magnetic field extrapolation, determining the optimal extrapolation height from physical rather than empirical criteria remains an open problem. To address this issue, this work investigates the vertical distributions of magnetic helicity and magnetic energy in the solar corona within active regions. We analyze 150 active regions observed by the Solar Magnetic Field Telescope (SMFT) from 1988 to 2019, grouped by absolute magnetic flux, perform nonlinear force-free field (NLFFF) extrapolations, and compute the relative magnetic helicity with a finite volume method. It is found that an extrapolation height of at least 81 Mm retains 97
Thermal non-equilibrium (TNE) is a well-known thermodynamic mechanism, generally studied in coronal loops. These evaporation and condensation cycles are induced by a quasi-steady and stratified heating. Long-period EUV pulsations and coronal rain are two manifestations of TNE. The quasi-periodicity of the cycles is a strong characteristic of TNE as the system dynamically evolves around a thermal equilibrium position that is not reachable. There are recent reports of coronal rain at open-closed boundaries such as fan-spine topologies and pseudo-streamers. However, no definite conclusions were drawn on the physical mechanisms driving these coronal rain events. In this article, we report the detection of long-period EUV pulsations and co-spatial recurring coronal rain showers in a pseudo-streamer observed with the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamic Observatory (SDO). The magnetic topology and evolution of the pseudo-streamer are studied in detail using a combination of potential field source-surface (PFSS) modeling and EUV dynamics. The 2.5-day event exhibits all the characteristic features of previous TNE events reported in coronal loops: periodic EUV pulses appearing sequentially in the different channels, following the ordering of the peaks in their temperature response, and coronal rain showers appearing toward the end of these cycles. We further show that the TNE cycles in the pseudo-streamer occur not only in the closed field but also in the open field. Our observations support the findings of recent numerical studies showing that TNE can also occur in open field regions and at open-closed boundaries. In parallel, interchange reconnection occurs continuously and non-impulsively all along the open-closed boundary as seen in EUV. The interplay between TNE and interchange reconnection may play a role in the release of condensations below the open-closed boundary and should be studied in detail in future works. This observation opens further perspectives for the understanding of TNE in the solar atmosphere and its potential implications for the solar wind.
Coronal holes (CHs) are low-density regions in the solar atmosphere, characterised by open magnetic field lines driving the high-speed solar wind. While appearing dark in EUV/X-rays, their radio signatures are complex and frequency-dependent, showing either brightness depressions or enhancements relative to the quiet-Sun (QS). This variability reflects the complex inner temperature, density and magnetic structures of the solar atmosphere. Within the SunDish project, we investigate the CH phenomenology using the National Institute for Astrophysics (INAF) large single-dish radio telescopes (Medicina ‘Gavril Grueff’ 32-m and Sardinia Radio Telescope ‘SRT’ 64-m), aiming to bridge the observational gap between the chromosphere and corona by exploring the under-investigated K-band (18 – 26 GHz ). This study analyses three representative scenarios: expected brightness temperature ( T_b ) depressions, radio-enhanced CHs, and radio-dark regions (RDRs) unrelated to standard CHs. Our analysis reveals a non-uniform phenomenology where radio-enhanced CHs and RDRs identify deep-penetrating structures affecting the upper chromosphere, including the first radio counterpart to a dark halo. Spectral indices and weak circular polarisation confirm thermal free-free emission as the primary mechanism, excluding significant gyro-magnetic contributions. However, magnetic field estimates suggest that a purely thermal model in a simple stratified atmosphere cannot fully describe these regions, where radio enhancements likely arise from unresolved structures like coronal bright points and magnetic flux tubes. These results highlight multi-frequency diagnostics as an essential tool for probing the coupling between different layers of the solar atmosphere, demonstrating that CHs are dynamic environments where complex magnetic activity drives their vertical structure and evolution.
Magnetic reconnection converts stored magnetic energy into kinetic energy, heat, and radiation. While extensively studied in fully ionized plasmas, observations show that ionization and recombination also play a role by modifying the local plasma resistivity and enabling additional heating channels. This study examines magnetic reconnection in the partially ionized solar chromosphere, analyzing its morphology and energy releases with attention to elastic collisions, ionization, and recombination. The MAGNUS code, originally built for ohmic resistivity and heat transfer, was modified to handle elastic and inelastic collisions. The simulations are 2.5D resistive MHD with two-fluid effects (charged + neutrals), adapted to handle interactions via these collision terms. A mixed explicit-implicit scheme was implemented to manage the stiffness of these terms. Simulations were carried out for three different magnetic field strengths: 100 G , 110 G , and 120 G . These values correspond to the low to mid chromosphere in quiet Sun conditions. We found that reconnection heats the plasma components by 18% to 110% . Although plasma beta rises only slightly, the energy release grows far more, indicating that charged–neutral collisions, not just beta or available magnetic energy, drive the enhanced reconnection. Furthermore, ionization and recombination become most significant in regions of peak temperature, particularly where particles are accelerated. Maximum reconnection rates from temporal analysis are 0.226, 0.253, and 0.279, respectively. Finally, in terms of energy, our results show that in a chromospheric volume of 0.4 × 0.01 × 0.4 Mm^3 , the energy released ranges from 10^22 to 10^23 erg .
The Tunable Magnetograph (TuMag) onboard Sunrise III is an imaging spectropolarimeter designed to ultimately infer the solar vector magnetic field and line-of-sight velocity. It includes Liquid Crystal Variable Retarders for polarimetric modulation and hence requires accurate polarimetric calibration to achieve its scientific goals. This work reports on the pre-flight calibration carried out on ground at different stages during the TuMag assembly, integration and verification phase. It includes the polarization modulator characterization, the verifications at instrument level, and, finally, the full system calibration after its integration in SUNRISE within the Post-Focus Instrumentation platform.The calibration includes determining the field-dependent demodulation matrices (pixel-by-pixel calibration) and evaluating polarimetric efficiencies, ensuring compliance with the mission sensitivity requirements. The results of this work provide the calibrated demodulation matrices that will be used for the scientific exploitation of the mission data.
The separation of multiscale fluctuations in the solar F_10.7 flux is hindered by substantial spectral overlap. We investigate the nonlinear dynamical evolution of F_10.7 across Solar Cycles 18 – 25 (1947 – 2025) using a hybrid method that combines Singular Spectrum Analysis (SSA) with log-frequency hierarchical clustering. This framework effectively mitigates the spectral mixing associated with conventional filtering and provides a more robust decomposition of the signal. The main results are as follows: (1) The F_10.7 flux is objectively decomposed into a secular trend, the 11-year Schwabe cycle, the 27-day rotational modulation, and intermediate-period components. (2) An intermittent Quasi-Biennial Oscillation (QBO) is isolated in the 1 – 3-year band, with dominant periods near 2.39 and 1.78 years, together with an additional 3.36-year component consistent with a Quasi-Triennial Oscillation (QTO). (3) QBO variability is preferentially enhanced during the ascending and maximum phases but does not scale monotonically with peak background activity; the largest excursions occur during SC22, whereas the stronger SC19 exhibits a comparatively moderate response. (4) The intermittent wave-packet morphology and marked cycle-to-cycle variability support the interpretation of the QBO as an instability-related secondary component rather than a persistent independent oscillation.
There are observational evidences supporting the existence of twisted magnetic fields in the solar corona. The dispersive properties and resonant absorption of the fast sausage modes (FSMs) in a twisted coronal loop are investigated. The coronal loop is modeled as a structured straight magnetic cylinder with an azimuthal magnetic field throughout in addition to an axis-aligned longitudinal magnetic field. The dispersion relation (DR) of FSMs is derived by numerically solving the eigenvalue problem (EVP) resulting from the one-dimensional resistive magnetohydrodynamic (MHD) equations. Our results confirm the previous conclusion that the principal FSM exhibits no cutoff, implying that this mode can propagate with arbitrary wavelengths. The dependencies of the oscillation frequency and damping rates of FSMs on the magnetic twist and longitudinal wavenumber are examined. For the flux tube parameters considered in this paper, we find that the damping of FSMs is too weak to produce observable signals in actual observations.
Solar Type II radio bursts are manifestations of shocks produced by explosive and eruptive solar activities, such as solar flares and coronal mass ejections (CMEs). Metric range or coronal Type II bursts are interesting because of their association with CME-driven shocks. It is therefore important to examine the correlation between the properties of Type II bursts and the associated CMEs. This, in turn, would be useful in understanding the impact of CMEs on space weather and geomagnetic activity. We conducted a statistical study of 23 coronal Type II radio bursts in the frequency range 150 – 20 MHz, for the period spanning 2007 – 2024. We correlated the frequency bandwidth of coronal Type II bursts with the angular width of the associated CMEs. Our investigation showed an anti-correlation between the two quantities with a correlation coefficient of ≈ −0.62. We further deduced the height of the Type II bursts (rTypeII) at the onset time of the burst and compared them with the estimated height of the associated CMEs/shocks (rCME). With the exception of one event, for the rest of the Type II burst events, rTypeII was < rCME. The results suggest that the CMEs with large angular widths produce narrow-band Type II emissions, and these Type II emissions could possibly be produced in the flank region of the CME-driven shock rather than at the shock front.
This manuscript is part of the Heliophysics Summer School Machine Learning Special Collection. Predicting solar flares remains a major challenge in space-weather forecasting. Large eruptive flares can trigger coronal mass ejections and energetic particle events that threaten satellites, endanger astronauts, and degrade High Frequency (HF) communications. Current flare alerts rely on Soft X-ray measurements from the X-ray Sensor onboard Geostationary Operational Environmental Satellite (GOES-XRS) crossing fixed flux thresholds, and therefore are issued only once the flare is already in its impulsive phase. This study focuses on solar-flare nowcasting using the Hot Onset Precursor Event (HOPE), a recently identified pre-flare phenomenon. In this study we extend existing HOPE trigger algorithms by applying a simple multilayer perceptron model to estimate flare peak magnitude and peak time. The method consists of detecting HOPE plasma temperature and emission measure signatures, and then using the time-histories of these variables to predict flare magnitude and time. The system is optimized to detect >M5.0 flares. The model was trained using 180 flares from GOES-14 through GOES-19 XRS instrument dataset, and tested over 46 independent flares. A 1-week proof-of-concept validation was performed during which all four >M5.0 flares were successfully detected, with an average lead time of 17.9 minutes relative to the NOAA R3 radio-blackout alert. These results show that HOPE-based machine learning models can deliver early warnings for high-impact flares.
Currently coronal mass ejections (CME) detection and measurements heavily depend on time-consuming human observations. Existing automated catalogs are based on manually crafted mathematical algorithms and struggle to provide the performance of a human observer (Lamy et al. 2019). Recent advances in machine learning (ML) have opened up new avenues for the early detection and analysis of coronal mass ejections (CMEs), which pose significant risks to space weather and technological systems on Earth. This study presents a novel methodology utilizing deep learning algorithms to analyze images from SOHO/LASCO coronagraphs, with the objective of enhancing the identification of CMEs by classifying the coronagraph frames into two categories: CME and non-CME. We created a dataset based on level 0.5 SOHO LASCO (Solar and Heliospheric Observatory Large Angle Spectrometer COronagraph) C2 observations correlated with CDAW (Coordinated Data Analysis Workshop) CME measurements. Then we developed two convolutional neural network (CNN) models for binary classification: the standard AlexNet and a modified AlexNet for action recognition (Spatiotemporal AlexNet). We tested various data augmentation techniques and evaluated various approaches to clip creation from static images. Initial results are very promising and show improvements in detection accuracy with the spatiotemporal model and suggest areas for further research in CME detection using machine learning. This research provides methodological insights that could aid the development of more effective CME detection systems and, ultimately, improved space weather preparedness. Further work will focus on replacing the automatically generated CDAW-based dataset with a manually curated version, as improved labeling quality is likely to enhance detection accuracy.
Sunspot oscillations provide a unique probe of magnetic-plasma interactions in the solar atmosphere. This study investigates oscillation period properties of six single sunspot active regions observed in the 8 – 10 μ m infrared band using the Accurate Infra-red Magnetic-field Solar Telescope (AIMS) at Lenghu Observatory. Light curves were extracted from three regions (umbra, penumbra, quiet Sun) and wavelet analysis was applied to determine dominant and weighted mean periods, comparing four methods: pixel-wise wavelet analysis with mean aggregation, pixel-wise wavelet analysis with median aggregation, spatial mean prior to wavelet analysis, and spatial median prior to wavelet analysis. The weighted mean period appears more physically meaningful than the dominant period, better representing the multi-mode nature of solar oscillations. A consistent period sequence holds across all six datasets: umbra (U) < penumbra (P) < quiet Sun (Q), with typical values of 260 – 313 s, 286 – 374 s, and 294 – 382 s, respectively. This key pattern is recovered with 100 0.14 ± 0.03 ), confirming the inherent multi-mode nature of solar oscillations. These findings provide important observational constraints for models of magneto-convection and wave propagation in sunspot atmospheres, establishing the 8 – 10 μ m band as a valuable diagnostic window for solar physics.
Polar faculae are footprints of the polar magnetic field that are visible as bright spots along intergranular lanes. Unlike equatorial faculae and sunspots, which are found at low to moderate solar latitudes and peak in number at solar maximum, polar faculae are found at latitudes greater than 70^∘ and peak in number around solar minimum. Polar faculae tend to have the same magnetic polarity as the general polar magnetic field, and their number has been shown to correlate with the strength of that magnetic field. This makes them good candidates for studying the evolution of polar conditions throughout the solar cycle from the ecliptic. We present a new automated method for counting and studying polar faculae in Helioseismic and Magnetic Imager (HMI) Ic_720s data using a source detection function from the Python library Photutils. We applied this method to both polar regions, using data averaged over each hour throughout the day between 2010 and 2022, the period for which HMI data is available in HelioCloud. Our results show a variation that is similar to that of the faculae count data from the Debrecen Heliophysical Observatory when they overlap, and extend that time series to December 2022. We also found that the magnetic field of the polar faculae averaged over the polar cap has the same polarity as the polar magnetic field from other measurements. However, we show that faculae with both polarities are present throughout the sunspot cycle. This indicates that some polar faculae may be generated by a local dynamo.
High-energy γ -ray emission generated in the solar atmosphere during powerful flares provides a unique channel of information on the acceleration of protons and ions to energies ≳ 300 MeV. Reliably identifying the shape of their energy spectrum with that of the secondary γ -ray emission requires a robust theoretical calculation of both the evolution of accelerated particles in the solar atmosphere and the resulting γ -ray emission for different particle injection scenarios. In this work, a numerical solution to the non-stationary Ginzburg–Syrovatskii particle transport equation in the “leaky box” approximation is obtained. Scenarios of free proton precipitation into the photosphere and precipitation with their preliminary trapping in the coronal parts of low and high magnetic loops are considered. The calculations for the photospheric and deeper layers take into account energy losses due to ionization and inelastic collisions, nuclear reactions that regenerate protons, and the production of neutral pions — the primary source of high-energy γ -ray emission. The results of the calculation comprise the time-dependent spectra of secondary particles and the corresponding light curves of the γ -ray emission. The inclusion of particle trapping in a coronal magnetic loop leads to sustained high-energy γ -ray emission on time scales ranging from a fraction of a minute to several tens of minutes. For large coronal loops, the trapping time could potentially reach the order of hours. The obtained spectra are compared both with some calculations from previous years and with recent calculations performed using the Monte Carlo method.
Supra-arcade downflows (SADs) are sunward-traveling features routinely observed in hot fan structures above magnetic loop arcades during eruptive solar flares. We manually compiled a catalog (SADCat) of 178 SAD-productive flares imaged by the Atmospheric Imaging Assembly (AIA) aboard the Solar Dynamics Observatory (SDO) during solar cycle 24 as a resource for the wider solar flare community. We conducted a preliminary analysis of the SADCat, comparing the flare X-ray and CME properties between eruptive solar flares with and without SADs. We found that peak GOES X-ray flux, flare duration, CME speed, and CME mass have a strong influence on whether a flare produces visible SADs, whereas flare impulsivity and CME acceleration have little effect.
We present a combined observational and modeling study of a geo-effective event on 2011 May 28, which produced a symmetric horizontal component index (SYM-H) index of −80 nT. The event occurred when active regions were bordered by a large coronal hole, potentially influencing the behavior of eruptive structures. We analyze magnetogram and extreme ultraviolet (EUV) images and find that this event involved two filament eruptions 8 hours apart from two different active regions closed to each other. Then, we track their coronal mass ejection (CME) counterparts using coronagraph images. We analyze plasma, magnetic field, particle energies and the SYM-H to find their relationship to the CMEs and the high-speed streams (HSS). The HSS interval is marked by enhanced particle energies and thermal speeds, with reduced ionic charge states and elemental abundance ratios, whereas the CME intervals exhibit the opposite behavior, emphasizing their distinct plasma characteristics. We reconstruct 3D magnetic field configurations for the active regions and assessed flux rope stability. We find that the presence of a nearby coronal hole makes flux ropes unstable at lower axial flux values, approximately three times smaller than in comparable cases without a coronal hole. Using a hydrodynamic (HD) model, constrained by remote sensing, and in situ data, we track the CME/ICME propagation up to 1 au. The model reproduces the overall timing and structure of the transients. Our results suggest that the coronal hole likely influenced CME propagation and may have reduced interactions between the CMEs, with the transients subsequently propagating along the solar wind streams emerging from the coronal hole. This study demonstrates how nearby magnetic structures can affect CME dynamics, which is critical for forecasting Earth-directed solar transients.
The turnover phenomenon observed for the radial variation of interplanetary scintillation (IPS) represents transition between weak and strong scattering of radio waves, and its location from the Sun (the turnover distance) serves as a reliable measure of solar-wind density fluctuations. In this study, we determined the turnover distances for 36 sources from IPS observations during 2008 – 2022 (Cycle 23/24 minimum through Cycle 25 rising phase) using the 327 MHz radio telescope at Toyokawa Observatory of the Institute for Space-Earth Environmental Research, Nagoya University. Such turnover-distance measurements over a long period using multiple sources provide unique information on the global distribution of solar-wind density fluctuations evolving with time, leading to improved understanding of the heliospheric response to the solar cycle. At Cycle 24 maximum, large values of the turnover distance were observed for all latitudes, whereas smaller values were observed at Cycle 23/24 and 24/25 minima particularly over the poles. These results suggest that the solar-wind density fluctuations at around 0.2 AU from the Sun increase (decrease) at solar maximum (minimum), and that their distribution in latitude were nearly uniform at solar maximum and non-uniform at minimum. The decrease in the turnover distance over the poles at solar minimum is ascribed to the effect of the polar coronal hole. Although the results obtained here were generally consistent with IPS observations made in Cycles 21 and 22, the turnover distances of the equator observed at Cycles 23/24 and 24/25 minima were smaller than those at the Cycle 20/21 and 21/22 minima, suggesting a marked reduction in density fluctuations of the equator at Cycles 23/24 and 24/25 minima, which is regarded as a manifestation of the weak solar cycle. A significant negative correlation was found between the turnover distance and the sharpness of the turnover. This means that the density gradient becomes flat (steep) when the solar-wind density fluctuations decrease (increase), providing with important implications on formation of large-scale density structure in the heliopshere.
Understanding and predicting the trigger of solar flares has been an area of focus for many years. In this work, we analyze EUV coronal data from SDO/AIA and Solar Orbiter EUI EUV High Resolution Imager (HRIEUV) to determine whether regions with high free magnetic energy in the photosphere show related dynamics in the corona. We studied two large solar flares from the same active region on 19 and 20 March 2024. We found that the two identified magnetic regions with high free energy also had frequent small spatial scale EUV intensity changes as highlighted through the standard deviation of the imaging data. The standard deviation enhancement in these regions peaked at least two minutes before the GOES X-ray emission and was close in time to the peak of the non-thermal emission, providing an additional method to identify the early flare trigger location and start.
