Solar Physics最新文献

This study comprehensively evaluates deep-learning models across three types of sunspot data: 13-month smoothed Sunspot Number (SSN), yearly SSN, and mean monthly SSN data. Traditional models such as LSTM, GRU, CNN, RNN, and BiLSTM are compared against proposed hybrid models: Hybrid1 (CNN-DilatedLSTM-BiLSTM-GRU), Hybrid2 (CNN-GRU-RNN with Dropout Regularization), Hybrid3 (CNN-GRU), Hybrid4 (CNN-GRU-RNN without Dropout) (Hybrid2 and Hybrid4 both integrate CNN-GRU-RNN architectures, but Hybrid2 introduces Dropout layers to reduce overfitting, making it a regularized version of Hybrid4), and a Hybrid Ensemble model (Hybrid2 + Hybrid4). Key metrics like RMSE, MAE, MSE, and R² are used to assess model performance. The results indicate that hybrid models consistently outperform traditional models across all datasets. Specifically, the Hybrid Ensemble achieves enhanced predictive accuracy, recording an RMSE of 4.062 and R² of 0.9964 for 13-month smoothed SSN data, an RMSE of 22.11 and R² of 0.8920 for yearly SSN data, and an RMSE of 24.61 and R² of 0.8826 for mean monthly SSN data. These findings demonstrate the ability of hybrid models, especially the Hybrid Ensemble, to effectively capture complex patterns in sunspot time-series data.

In addition to model evaluation, this study provides forecasted SSN values for Solar Cycle 26, projecting a gradual increase in solar activity from 2025 (SSN: 112.39) to a peak in 2036 (SSN: 165.35), followed by a slight decline in 2037 (SSN: 155.25), with the lowest SSN occurring in 2032 (SSN: 10.41). These forecasts align well with known solar cycle variations and offer valuable insights into upcoming solar activity and its implications for space weather, climate, and technology. A Friedman non-parametric test was conducted to rank model performance, confirming the Hybrid Ensemble as the top performer. Holm-adjusted multiple comparisons showed negligible differences, reinforcing the robustness of the hybrid and ensemble approaches. This research highlights the value of combining different architectures to improve forecasting accuracy, especially for complex scientific time-series data such as solar activity.

Filaments/prominences are cold plasma ((approx 10^{4}) K) embedded in the solar corona, two orders of magnitude hotter. Filament plasma is structured by the magnetic field in thin elongated threads. Counter-streaming flows have been observed. The aim of this paper is to characterize these flows. For that, we use high spatial resolution observations of spectral data obtained with THEMIS in H(alpha ) and with IRIS in Mg II k lines on 29 September 2023. We best detect counter-streaming flows in both the blue and red wings of these spectral lines. They are forming long Doppler shifted strands slightly inclined on the filament axis. The blue/red shift alternates across the strands at the arc second scale. H(alpha ) spectral profiles with large widths are interpreted as formed by multi-strands with opposite velocity directions. The absorption in the core of Mg II k line is also broader than in the chromosphere. This corresponds also to counter-streaming velocities. We derive that a fraction of the filament plasma is moving at supersonic speed (of the order of 20 km s⁻¹) with the assumption that the filament is optically thick. We conclude that the counter-directed Doppler shifts might not be magnetic field aligned flows but rather correspond to kink transverse oscillations of the magnetic field with independent motions in nearby strands.

Helioseismology and solar modelling have enjoyed a golden era thanks to decades-long surveys from ground-based networks such as for example GONG, BiSON, IRIS and the SOHO and SDO space missions which have provided high-quality helioseismic observations that supplemented photometric, gravitational, size and shape, limb-darkening and spectroscopic constraints as well as measurements of neutrino fluxes. However, the success of solar models is also deeply rooted in progress in fundamental physics (equation of state of the solar plasma, high-quality atomic physics computations and opacities, description of convection and the role of macroscopic transport processes of angular momentum and chemicals, such as for example meridional circulation, internal gravity waves, shear-induced turbulence or even convection. In this paper, we briefly outline some key areas of research that deserve particular attention in solar modelling. We discuss the current uncertainties that need to be addressed, how these limit our predictions from solar models and their impact on stellar evolution in general. We outline potential strategies to mitigate them and how multidisciplinary approaches will be needed in the future to tackle them.

In this work, we describe the design and flight performance of the REFOS instrument (from Russian REntgenovskiy FOto Spektrometr; in English “X-ray Photo Spectrometer”). REFOS is a soft X-ray spectrophotometer that registers full-disk integrated solar spectra (“Sun as a star”). It operates on board the Impulse-1 nanosatellite, which was launched on 24 June 2023. REFOS has a 1.2 – 30 keV spectral range, a 0.123 keV nominal full width at half-maximum (FWHM) resolution at 5.9 keV, and a cadence of 16 s. We illustrate the instrument flight performance using the spectra of the X5.0 flare that occurred on 31 December 2023 at 21:55 UT. For this flare, REFOS registered a meaningful signal in all of its energy bins. Based on a comparison between the GOES and REFOS fluxes, we corrected the REFOS spectral sensitivity. Additionally, we assessed the quality of the calibration based on the shape of the continuum. The observed continuum allows diagnosing the plasma temperature, and the observed spectral lines allow studying abundances of the Mg, Si, S, Ar, Ca, Fe, and Ni.

The Parker Solar Probe (PSP), as the spacecraft nearest to the Sun, has revolutionized our comprehension of the solar corona and interplanetary space. Among its significant discoveries is the ubiquity of switchbacks, exhibiting localized magnetic reversals that deviate from the otherwise prevalent Parker spirals. The formation reason of these switchbacks still remains an enigma. In this research, we utilized a 3-dimensional (3D) data-driven global full magnetohydrodynamics (MHD) model to thoroughly investigate the formation reason of switchbacks. Through simulations, we propose a possible formation reason: when disturbances in the velocity or pressure of the plasma near the solar surface arise and their intensity and scope surpass a specific threshold, the magnetic field will progressively curve over time, ultimately forming a switchback structure. Furthermore, the magnitude and range of these perturbations directly correlate with the swiftness of the switchback’s formation; the more intense or widespread the perturbations, the quicker the structure will materialize.

The transport of chemical elements in stellar interiors is one of the greatest sources of uncertainties of solar and stellar modelling. The Sun, with its exquisite spectroscopic, helioseismic and neutrino observations, offers a prime environment to test the prescriptions used for both microscopic and macroscopic transport processes. We study in detail the impact of various formalisms for atomic diffusion on helioseismic constraints in both CLES (Scuflaire et al. 2008a) and Cesam2k20 (Morel and Lebreton 2008; Marques et al. 2013; Deal et al. 2018) models and compare both codes in detail. Moreover, due to the inability of standard models using microscopic diffusion to reproduce light element depletion in the Sun (Li, Be), another efficient process must be included to reproduce these constraints (rotation-induced: Eggenberger et al. 2022, overshooting -or penetrative convection- below the convective envelope: Thévenin et al. 2017, or ad hoc turbulence: Lebreton and Maeder 1987; Richer, Michaud, and Turcotte 2000). However, introducing such an extra mixing leads to issues with the CNO neutrino fluxes (see Buldgen et al. 2023), which seem to be systematically lower than the Borexino observations (Appel et al. 2022). Another key aspect to consider when reconciling models with neutrino fluxes is the impact of electronic screening (Mussack and Däppen 2011).

The analysis of the meridional displacement velocity of individual solar pores and sunspots has been performed. In the period May 2010 – March 2025 of observations in the continuum of the Solar Dynamics Observatory/Helioseismic and Magnetic Imager (SDO/HMI), we identified more than (3.6cdot 10^{5}) sunspots and pores for analysis and tracked their displacement. The velocity of the meridional displacement of spots (v_{mathrm{m}}) depends on their magnetic polarity, latitude, and stage of development. For sunspots and pores of trailing polarity, the velocity of movement is on average directed toward the poles. For such spots, the dependence of the velocity on latitude can be represented by linear regressions for pores: (v^{mathrm{pr}}_{mathrm{tr}} approx 2.0+0.62cdot theta ^{mathrm{o}}) m s⁻¹; for sunspots: (v^{mathrm{sp}}_{mathrm{tr}}approx 0.02+0.94cdot theta ^{mathrm{o}}) m s⁻¹. For sunspots and pores of leading polarity, the dependence is non-monotonic in nature on latitude. For pores: (v^{mathrm{pr}}_{mathrm{ld}}approx 0.35-11.7cdot {mathrm{sin}}(theta )+16.5 cdot {mathrm{sin}}^{mathrm{2}} (theta ) +76.5cdot {mathrm{sin}}^{3} (theta )-32.7 cdot {mathrm{sin}}^{4}(theta )) m s⁻¹; for sunspots: (v^{mathrm{sp}}_{mathrm{ld}}approx -0.35-18.3cdot {mathrm{sin}}(theta )+32.2 cdot {mathrm{sin}}^{mathrm{2}}(theta ) +71.4cdot {mathrm{sin}}^{mathrm{3}} ( theta )-6.7cdot {mathrm{sin}}^{mathrm{4}}(theta )) m s⁻¹. The highest speed of meridional movement to the poles is observed for sunspots of trailing polarity during the phase of growth of the sunspot area. The velocity of the meridional movement depends on their area, reaching a maximum for an area of (Sapprox ) 80 – 100 (mu )sh.

In September 1777 Ruđer Bošković observed and measured the sunspot positions to determine the solar rotation elements. In 1785, among other methods, he described a trigonometric spherical solution for the determination of the position of the axis and rate of the solar rotation using three sunspot positions, but without equations. For the first time, we derive the equations that are applicable to modern computers for calculating the solar rotation elements, as they were described by Bošković. We recalculated Bošković’s original example using his measurements of sunspot positions from 1777 and the equations developed here, confirming his results from 1785. Bošković’s methodology of arithmetic means determines (i), (Omega ), and the sidereal period (T') separately, while the planar trigonometric solution determines (i) and (Omega ) together. His spherical trigonometric solution calculates (i), (Omega ), and the sidereal period (T') in a single procedure.

In this paper, we present the results of our analysis of solar eruptive flares observed by the Ondřejov radiospectrographs over more than three decades. By combining the eruptive flare model with findings from our magnetohydrodynamic and particle-in-cell simulations, we demonstrate the crucial role of decimetric radio bursts in understanding plasma processes during eruptive flares. We describe unusual drifting continua associated with the rise of a magnetic rope at the onset of these flares. Notably, we report very rare slowly positively drifting bursts (SPDBs) linked to the bright helical structure of the ascending rope. Drifting pulsation structures (DPSs) are identified as signatures of plasmoids, while narrowband decimetric spikes are associated with magnetic reconnection outflows. We also examine pairs of decimetric Type III bursts, which indicate electron beams propagating both upward and downward in the solar atmosphere from the acceleration site, as well as a special Type III burst likely traveling around a plasmoid. We introduce a method for computing period maps and identifying a unique wave/shock feature in the radio spectrum. A movie illustrating the plasma processes responsible for generating the drifting pulsation structure is also shown. The interpretations of all presented bursts are based on the standard model of eruptive flares. However, positional data for sources of these radio bursts are often lacking. To emphasize the importance of spatial information, we present an example of a drifting pulsation structure observed simultaneously with observations from the Expanded Owens Valley Solar Array (EOVSA). Finally, we summarize all discussed bursts in a comprehensive scheme that extends our knowledge about a role of decimetric bursts at the onset of eruptive flares.

The Solar Ultraviolet Imaging Telescope (SUIT) onboard Aditya-L1 is an imager that observes the solar photosphere and chromosphere through observations in the wavelength range of 200 – 400 nm. A comprehensive understanding of the plasma and thermodynamic properties of chromospheric and photospheric morphological structures requires a large sample statistical study of these regions, necessitating the development of automatic feature detection methods. To this end, we develop the feature detection algorithm SPACE-SUIT: Solar Phenomena Analysis and Classification using Enhanced vision techniques for SUIT, to detect and classify the solar chromospheric features to be observed from SUIT’s Mg II k filter. Specifically, we target plage regions, sunspots, filaments, and off-limb structures for detection using this algorithm. SPACE uses You Only Look Once (YOLO), a neural network-based model to identify regions of interest. We train and validate SPACE using mock-SUIT images developed from Interface Region Imaging Spectrometer (IRIS) full-disk mosaic images in Mg II k line, while we also perform detection on Level-1 SUIT data. SPACE achieves a precision of (approx 0.788), recall of (approx 0.863) and a MAP of (approx 0.874) on the validation mock SUIT FITS dataset. Since our dataset is manually labeled, we perform ‘self-validation’ on the identified regions by defining statistical measures and Tamura features on the ground truth and predicted bounding boxes. We find the distributions of entropy, contrast, dissimilarity, and energy to show differences for the features in consideration. We find these differences to be captured qualitatively by the detected regions predicted by SPACE. Furthermore, we find these differences to also be qualitatively captured by the observed SUIT images, reflecting validation in the absence of a labeled ground truth. This work hence not only develops a chromospheric feature extractor, but it also demonstrates the effectiveness of statistical metrics and Tamura features in differentiating chromospheric features of interest, providing independent validation measures for any future detection and validation scheme.