Solar Physics最新文献

The solar chromosphere plays an important role in the transport of energy between the cool, dense photosphere and hot, tenuous corona. The determination of the thermodynamic and kinematics conditions of the chromosphere is crucial to understand the above coupling which is often done with the help of spectral inversion codes (ICs). We study and describe the performance of two ICs that are fundamentally unique in principle, implementation, and speed to infer the temperature of the solar chromosphere over a 3 arcmin field-of-view. We obtained spectral line scans of NOAA active region (AR) 12765 with the Ca ii 8542 Å line using the narrow-band imaging spectro-polarimeter on the 50-cm Multi-Application Solar Telescope at the Udaipur Solar Observatory, India. The temperature of the lower to mid-chromosphere was inferred from the following two ICs, namely, i) Non-LTE Inversion COde using the Lorien Engine (NICOLE) and ii) CAlcium Inversion based on a Spectral ARchive (CAISAR). A similar fit quality of the spectra is obtained with the resulting temperature stratification in good agreement with one another for a significantly large part of the field-of-view, despite the intrinsic differences in the two ICs. A few locations at the umbra-penumbra boundary and palge regions show a deviation in the two temperature stratifications which, to a first order, can be attributed to the generation of the archive spectra in CAISAR, where localised, Gaussian enhancements are provided to the temperature profile and the line-of-sight velocity is not considered/ignored. Once the spectral archive is created, CAISAR is several orders of magnitude faster than the conventional IC NICOLE, can be executed on a simple off-the-shelf workstation, and provide 3-dimensional temperature cubes with temporal information, that is ideally suited for processing observations from imaging spectrometers at most modern solar facilities.

In this study, we report on the processing and analysis of around 10,000 images of the solar disk, obtained from the SOHO and SDO satellites, available in the Helioviewer database. Using our own code, PyMoST (Python Morphological Sunspot Tracker), which employs a mathematical morphology technique, we were able to automatically track and analyze approximately 52,000 sunspots in these images, covering the period from January 1, 1998 to August 28, 2025. By using PyMoST we were able to obtain the distribution of the number of spots as a function of solar latitude and time, accurately reproducing Solar Cycles 23, 24 and the current phase of Solar Cycle 25, in agreement with the literature. In addition, our code was also able to determine the areas and number of sunspots, showing excellent correlation with the results reported by the Royal Greenwich Observatory (RGO), Kodaikanal Solar Observatory (KSO) and the International Sunspot Number - Solar Influences Data Analysis Center (SIDIC), thus consolidating the efficiency of our tool and its importance for the investigation of solar magnetic activity.

In both coronagraphic and total solar eclipse observations, the solar disk is not directly visible. Blocking direct light from the photosphere is essential to observe the visible solar corona, which is (10^{-5}) to (10^{-11}) of the disk intensity. This lack of direct observation of the solar disk introduces uncertainty in determining the Sun center behind the occulter, especially in cases where instrument limitations or low signal-to-noise ratios make it challenging to apply standard astrometric approaches. We present a novel method for locating the Sun center behind the occulter during coronagraphic observations, developed using the Metis polarimetric measurements during the first close Solar Orbiter perihelion. We further suggest how this technique can enable in-flight polarization calibration. We carried out polarimetric observations of the solar corona using data from the Metis visible-light (VL) channel (580 – 640 nm). The linearly polarized brightness of the Thomson scattered corona is expected to be mainly tangential to the solar limb. By identifying pairs of such tangential polarization vectors at approximately (180^{circ }) apart, the Sun center can be geometrically determined as the intersection point of the lines passing by these vectors. Alternatively, if the position of the Sun center is already known, the results can be further refined and potentially used to calibrate the elements of the demodulation matrix employed to derive the Stokes parameters. This article presents a novel method for detecting the Sun center behind an occulter. The approach was successfully tested, considering different distances from the Sun and off-pointing maneuvers. The discrepancy between the actual Sun center and the one estimated using this method is typically within a few pixels on the Metis VL detector, when we use coronal data with high signal-to-noise ratio. These results suggest that the method provides a valuable alternative to traditional astrometric techniques and could enable new in-flight calibration strategies for polarimetric instrumentation.

Plasmoid instability in magnetized plasmas, such as the solar corona, arises from the development of both linear and nonlinear magnetic reconnection processes. This instability releases the stored magnetic energy of the plasma in the form of kinetic and thermal energy. The phenomenon has been investigated from two perspectives: Magnetohydrodynamic (MHD) simulations and Particle-in-Cell (PIC) simulations. In MHD simulations, the Lundquist number is commonly used to estimate the threshold for the onset of this instability. In this paper, we present a new approximation for the initial magnetic power density in plasma, which defines the formation threshold of plasmoid instability in PIC simulations. According to this approximation, the initial magnetic power density depends on parameters such as the initial magnetic field strength and the width of the current sheet. A numerical value for the initial magnetic power density is derived from solar coronal simulation results. PIC simulations demonstrate that plasmoid instability occurs if the initial plasma power exceeds (sim 1.71 times 10^{2}~text{erg}.text{cm}^{ - 3}.text{s}^{ - 1}).

The Sun periodically emits intense bursts of radio emission known as solar radio bursts (SRBs). These bursts can disrupt radio communications and be indicative of large solar events that can disrupt technological infrastructure on Earth and in space. The risks posed by these events highlight the need for automated SRB classification, providing the potential to improve event detection and real-time monitoring. This would advance the techniques used to study space weather and related phenomena. A dataset containing images of radio spectra was created using data recorded by the Compound Astronomical Low frequency Low cost Instrument for Spectroscopy and Transportable Observatory (e-Callisto) network. This dataset comprises three categories: empty spectrograms; spectrograms containing Type II SRBs; and spectrograms containing Type III SRBs. These images were used to fine-tune several popular pre-trained deep-learning models for classifying Type II and Type III SRBs. The evaluated models included VGGnet-19, MobileNet, ResNet-152, DenseNet-201, and YOLOv8. Testing the models on the test set produced F1 scores ranging from 87% to 92%. YOLOv8 emerged as the best-performing model among them, demonstrating that using pre-trained models for event classification can provide an automated solution for SRB classification. This approach provides a practical solution to the limited number of data samples available for Type II SRBs.

Astrophysical plasmas ubiquitously exhibit turbulent behavior, underpinning the conversion of large-scale mechanical and magnetic energies into heat across an extensive range of scales. This review critically examines the mechanisms underlying turbulent energy dissipation in magnetohydrodynamic (MHD) systems, with special emphasis on the enigmatic heating of the solar corona. We synthesize and evaluate classical phenomenological frameworks, such as the Iroshnikov–Kraichnan extension of Kolmogorov’s turbulence theory and contrast these with modern theories of strong turbulence as articulated in Goldreich–Sridhar’s critical balance model. The discussion extends to incorporate contemporary insights into the roles of dynamic alignment and intermittency, which serve to refine energy cascade descriptions in both incompressible (IMHD) and compressible (CMHD) regimes. The multifaceted effects of compressibility, including shock dynamics and mode decomposition, are also discussed, especially in the context of solar coronal heating where density variations cannot be neglected. Finally, emerging methodologies such as physics-informed neural networks (PINNs) are reviewed for their potential to integrate data-driven modeling with fundamental plasma theory. This comprehensive account not only reconciles diverse theoretical perspectives but also highlights unresolved challenges, thereby charting a course for future research into the turbulent processes that govern energy conversion in astrophysical environments.

Coronal arcade loops play a key role in our understanding of solar activity because they contain plasma within closed magnetic field lines. Although these structures have been extensively studied using various observational techniques, combining radio and extreme ultraviolet (EUV) observations provides a unique opportunity to analyse their properties more comprehensively. In this study, we present the first three-dimensional characterisation of coronal loops by analysing simultaneous observations of type J solar radio bursts and EUV imaging. Data were collected from the Observations Radiospectrographiques pour FEDOME et l’Étude des Éruptions Solaires, the Nançay Radioheliograph, and the Solar Dynamics Observatory/Atmospheric Imaging Assembly instruments during an event on 6 March 2014. Our results reveal a direct spatial correlation between the sources of type J bursts and visible coronal loops. Using a new methodology combining radio polarisation measurements and EUV-based three-dimensional loop reconstruction, we determined several key physical parameters: a temperature of approximately 0.82 MK, an electron density distribution ranging from around (10^{9}text{ cm}^{-3}) at the foot of the loop to around (10^{7}text{ cm}^{-3}) at the top, and a magnetic field strength varying from around 850 Gauss at the footpoint to around 5 Gauss at the top. Our results confirm the validity of hydrostatic equilibrium and dipole field models for coronal loops while providing unprecedented insights into their three-dimensional structure and physical properties. This research introduces a new diagnostic technique for studying coronal loop dynamics and their role in solar eruptions.

The distribution of interval times between recurrent discrete events, such as Solar and stellar flares, reflects their underlying dynamics. Log-normal functions provide good fits to the interval time distributions of many recurrent astronomical events. The width of the fit is a dimensionless parameter that characterizes its underlying dynamics, in analogy to the critical exponents of renormalization group theory. If the distribution of event strengths is a power law, as it often is over a wide range, then the width of the log-normal is independent of the detector sensitivity in that range, making it a robust metric. Analyzing two catalogues of Solar flares over periods ranging from 46 days to 37 years, we find that the widths of log-normal fits to the intervals between flares are wider than those of shot noise, indicating memory in the underlying dynamics even over a time much shorter than the Solar cycle. In contrast, the statistics of flare stars are consistent with shot noise (no memory). We suggest that this is a consequence of the production of Solar flares in localized transient active regions with varying mean flare rate, but that the very energetic flares of flare stars result from global magnetic rearrangement that reinitializes their magnetohydrodynamic turbulence.

Solar flare electromagnetic radiation is frequently accompanied by quasi-periodic pulsations (QPPs), which can be observed at various wavelengths, including hard X-rays (HXRs). The investigation of QPPs provides valuable insights into particle acceleration during solar flares and dynamic processes within the solar atmosphere. This study aimed to compare the timing of QPPs with identical periods in both magnetically coupled and uncoupled HXR sources during two solar flares, SOL2014-04-18 and SOL2014-10-22, and to test the hypothesis that subminute QPPs in HXR emission are generated by intrinsic magnetic loop oscillations. To achieve these objectives, we conducted a comparative observational analysis of QPPs within eruptive and confined solar flare events (SOL2014-04-18 and SOL2014-10-22, respectively) and theoretical modeling of electron kinetics using numerical simulations. A detailed examination of the HXR source regions was performed to identify correlations between the QPPs and the magnetic field structures. The numerical modeling of accelerated electron kinetics considers various factors, such as magnetic mirroring, pitch angle scattering, betatron acceleration, inhomogeneity of plasma density distribution, and magnetic field variations. This study revealed a complex relationship between electron acceleration and the generation of QPPs. The analysis of QPP timing and synchronicity in local HXR sources for the two flares provided contrasting results. In SOL2014-04-18, the observed QPP behavior across the magnetically coupled and uncoupled regions presents challenges for simple oscillating trap models based on individual magnetic loops. Conversely, the SOL2014-10-22 event displayed more coherent QPP activity across the flare region, which is potentially indicative of a larger-scale modulation or oscillation. Numerical simulations show how magnetic field oscillations and plasma dynamics can affect electron acceleration and QPP characteristics, but highlight challenges for single oscillating loops in explaining the observed QPP amplitude evolution. Rather than fitting individual events, our simulations yield a small set of robust, falsifiable signatures of the oscillating-trap scenario, such as (i) HXR peak evolution after a single or multiple injections, (ii) pulse-width–period scaling, and (iii) specific magnetically coupled footpoints phase relations, which we compared with the observations from the two flares.

Standard visualizations of Extreme Ultraviolet (EUV) solar imagery often fail to convey the full complexity of the Sun’s corona, especially in faint off-limb regions. This can leave the misleading impression of the Sun as a bright ball in a dark void, rather than revealing it as the dynamic, structured source of the solar wind and space weather. A variety of enhancement algorithms have been developed to address this challenge, each with its own strengths and tradeoffs. We introduce the Radial Histogram Equalizing Filter (RHEF), a novel hybrid technique that optimizes contrast in high dynamic range solar images. By combining the spatial awareness of radial graded filters with the perceptual benefits of histogram equalization, RHEF reveals faint coronal structures and works out of the box—without requiring careful parameter tuning or prior dataset characterization. RHEF operates independently on each frame, and it enhances on-disk and off-limb features uniformly across the field of view. For additional control, we also present the Upsilon redistribution function—a symmetrized cousin of gamma correction—as an optional post-processing step that provides intuitive programmatic tonal compression. We benchmark RHEF against established methods and offer guidance on filter selection across various applications, with examples from multiple solar instruments provided in an appendix. Implemented and available in both Python sunkit_image and IDL, RHEF enables immediate improvements in solar coronal visualization.