Mihalis Mathioudakis

One of the first high-cadence chromospheric image sequences recorded with the recently commissioned Daniel K. Inouye Solar Telescope (DKIST) has revealed propagating arc-shaped bright fronts of a few hundred kilometers width. These bright fronts maintain their arc shape over up to one minute, travel with apparent horizontal speeds of ∼8 km s ⁻¹ , and originate from chromospheric bright grains seen at the center of the arc. We identify photospheric G -band bright points underneath the chromospheric bright grains, which are typically the signature of small-scale magnetic flux concentrations. The G -band bright points are found to interact with colocated vortices prior to the appearance of the chromospheric bright fronts. Images synthesized from three-dimensional magnetohydrodynamic simulations show a striking similarity with the discovered phenomenon and reveal that the arc-shaped bright fronts arise from essentially acoustic, weak shock fronts that propagate in the ambient medium, seemingly triggered by the vortex dynamics of the underlying magnetic flux concentration. In this work, we provide the first hints of a hitherto unknown magnetohydrodynamic process by which vortex-driven torsional Alfvén pulses couple to predominantly acoustic waves that steepen into shocks and dissipate their energies. The detected number density and frequency of these events are at least a factor 10 too small to be a major source of solar chromospheric heating but simulations show a seven times higher number density. We therefore expect to discover many more events with tailored narrow band observations.

We present high-resolution multiline spectropolarimetric observations of a quiet-Sun network element obtained with the S unrise iii Chromospheric Infrared SpectroPolarimeter. The observations combine photospheric, upper-photospheric, and chromospheric diagnostics at a spatial resolution and polarimetric sensitivity that allow the transverse magnetic structure of the network boundary to be examined directly. We find that the strongest linear polarization is concentrated in a narrow ridge around the edge of the magnetic element, cospatial with enhanced transverse magnetic field inferred from multiline inversions. The magnetic azimuth exhibits a coherent, predominantly radial organization around a more vertical core, consistent with an expanding magnetic canopy. An azimuth proxy derived directly from the observed Fe i and K i linear polarization reproduces the same large-scale organization, showing that this structure is encoded in the Stokes profiles rather than imposed by the inversion. Response functions and a MURaM-based forward-synthesis test indicate that the Fe i 8468 Å linear polarization is sensitive to magnetic azimuth in the upper photosphere, with the closest proxy agreement occurring near log τ ≈ − 3 . We find no evidence for strong azimuthal shear between the Fe- and K-sensitive diagnostics. At the network boundary, we also identify localized parasitic-polarity patches associated with complex, multilobed Stokes V profiles and one case in which the Stokes V polarity reverses between photospheric Fe i and chromospheric Ca ii lines. These results demonstrate that quiet-Sun network boundaries contain organized upper-photospheric canopy fields together with a small-scale mixed-polarity structure, providing new constraints on the three-dimensional magnetic structure of network elements.

Bright points (BPs) are small-scale, dynamic features that are ubiquitous across the solar disc and are often associated with the underlying magnetic field. Using broadband photospheric images obtained with the Visible Broadband Imager at the National Science Foundation’s Daniel K. Inouye Solar Telescope (DKIST), the properties of BPs have been analyzed with DKIST for the first time at the highest spatial resolutions achievable. BPs were observed to have an average lifetime of 95 ± 29 s and a mean transverse velocity of 1.60 ± 0.41 km s ⁻¹ . The BPs had a log-normal area distribution with a peak at 2300 km ² . Transverse velocities and lifetimes across the DKIST images were comparable and consistent with previous studies. The area distribution of the DKIST data peaked in areas significantly lower than those from the literature. This was explored further and was observed to be due to an overestimation of BP areas due to the merging of close features when the spatial resolution is reduced, in tandem with possible oversplitting of features in the DKIST images. Furthermore, the effect of variable seeing in the data was determined. This showed that the average spatial resolution of the data was around 0 . ″ 034 ± 0 . ″ 007 , in comparison to the theoretical diffraction limit of 0 . ″ 022 . Accounting for the influence of seeing, the peak of the area distribution of BPs in the DKIST data was estimated as 4800 km ² , which is still significantly lower than previously observed.

Solar spectropolarimetric inversion—inferring atmospheric conditions from the Stokes vector—is a key diagnostic tool for understanding solar magnetism, but traditional inversion methods are computationally expensive and sensitive to local minima. Advances in artificial intelligence offer faster solutions, but are often restricted to shallow models or a few spectral lines. We present a proof-of-concept study using a transformer machine learning model for multiline, full-Stokes inversion, to infer stratified parameters from synthetic spectra produced from 3D magnetohydrodynamic simulations. We synthesize a large set of Stokes vectors using forward modeling across 15 spectral lines spanning the deep photosphere toward the chromosphere. The model maps full-Stokes input to temperature, magnetic field strength, inclination, azimuth (encoded as sin 2 ϕ , cos 2 ϕ ), and line-of-sight velocity as a function of optical depth. The transformer incorporates an attention mechanism that allows the model to focus on the most informative regions of the spectrum for each inferred parameter, and uses positional embedding to encode wavelength and depth order. We benchmark it against a multilayer perceptron (MLP), test robustness to noise, and assess generalization. The transformer outperforms the MLP, especially in the higher layers and for magnetic parameters, yielding higher correlations and more regularized stratifications. The model retains strong performance across a range of noise levels typical for real observations, with magnetic parameter inference degrading predictably while temperature and velocity remain stable. We explore attention maps, linking the transformer’s learned behaviour to line-formation physics.

The morphology of circular polarization profiles from solar spectropolarimetric observations encodes information about the magnetic field strength, inclination, and line-of-sight velocity gradients. Previous studies used manual methods or unsupervised machine learning (ML) to classify the shapes of circular polarization profiles. We trained a multilayer perceptron comparing classifications with unsupervised ML. The method was tested on quiet Sun data sets from Daniel K. Inouye Solar Telescope (DKIST), Hinode, and GREGOR, as well as simulations of granulation and a sunspot. We achieve validation metrics typically close to or above 90%. We also present the first statistical analysis of quiet Sun DKIST/ViSP data using inversions and our supervised classifier. We demonstrate that classifications with unsupervised ML alone can introduce systemic errors that could compromise statistical comparisons. DKIST and Hinode classifications in the quiet Sun are similar, despite our modeling indicating spatial resolution differences should alter the shapes of circular polarization signals. Asymmetrical (symmetrical) profiles are less (more) common in GREGOR than DKIST or Hinode data, consistent with narrower response functions in the 1564.85 nm line. Single-lobed profiles are extremely rare in GREGOR data. In the sunspot simulation, the 630.25 nm line produces “double” profiles in the penumbra, likely a manifestation of magneto-optical effects in horizontal fields; these are rarer in the 1564.85 nm line. We find the 1564.85 nm line detects more reverse polarity magnetic fields in the penumbra, in contradiction to observations. We detect mixed-polarity profiles in nearly one fifth of the penumbra. Supervised ML robustly classifies solar spectropolarimetric data, enabling detailed statistical analyses of magnetic fields.

The composition of the solar corona differs from that of the photosphere, with the plasma thought to fractionate in the solar chromosphere according to the first ionization potential (FIP) of the different elements. This produces a FIP bias, wherein elements with a low FIP are preferentially enhanced in the corona compared to their photospheric abundance, but direct observations of this process remain elusive. Here, we use a series of spectroscopic observations of active region AR 12759 as it transited the solar disk over a period of 6 days from 2020 April 2–7 taken using the Hinode Extreme ultraviolet Imaging Spectrometer and Interface Region Imaging Spectrograph (IRIS) instruments to look for signatures of plasma fractionation in the solar chromosphere. Using the Si x/S x and Ca xiv/Ar xiv diagnostics, we find distinct differences between the FIP bias of the leading and following polarities of the active region. The widths of the IRIS Si iv lines exhibited clear differences between the leading and following polarity regions, indicating increased unresolved wave activity in the following polarity region compared to the leading polarity region, with the chromospheric velocities derived using the Mg ii lines exhibiting comparable, albeit much weaker, behavior. These results are consistent with plasma fractionation via resonant/nonresonant waves at different locations in the solar chromosphere following the ponderomotive force model, and indicate that IRIS could be used to further study this fundamental physical process.

The strongly coupled hydrodynamic, magnetic, and radiation properties of the plasma in the solar chromosphere make it a region of the Sun's atmosphere that is poorly understood. We use data obtained with the high-resolution Visible Broadband Imager (VBI) equipped with an Hβ filter and the Visible Spectro-Polarimeter (ViSP) on the Daniel K. Inouye Solar Telescope to investigate the fine-scale structure of the plage chromosphere. To aid in the interpretation of the VBI imaging data, we also analyze spectra from the CHROMospheric Imaging Spectrometer on the Swedish Solar Telescope. The analysis of spectral properties, such as enhanced line widths and line depths, explains the high contrast of the fibrils relative to the background atmosphere demonstrating that Hβ is an excellent diagnostic for the enigmatic fine-scale structure of the chromosphere. A correlation between the parameters of the Hβ line indicates that opacity broadening created by overdense fibrils could be the main reason for the spectral line broadening frequently observed in chromospheric fine-scale structures. Spectropolarimetric inversions of the ViSP data in the Ca ii 8542 Å and Fe i 6301/6302 Å lines are used to construct semiempirical models of the plage atmosphere. Inversion outputs indicate the existence of dense fibrils in the Ca ii 8542 Å line. The analyses of the ViSP data show that the morphological characteristics, such as orientation, inclination, and length of fibrils, are defined by the topology of the magnetic field in the photosphere. Chromospheric maps reveal a prominent magnetic canopy in the area where fibrils are directed toward the observer.

The composition of the solar corona differs from that of the photosphere, with the plasma thought to fractionate in the solar chromosphere according to the First Ionisation Potential (FIP) of the different elements. This produces a FIP bias, wherein elements with a low FIP are preferentially enhanced in the corona compared to their photospheric abundance, but direct observations of this process remain elusive. Here we use a series of spectroscopic observations of Active Region AR 12759 as it transited the solar disc over a period of 6 days from 2-7 April 2020 taken using the Hinode Extreme ultraviolet Imaging Spectrometer (EIS) and Interface Region Imaging Spectrograph (IRIS) instruments to look for signatures of plasma fractionation in the solar chromosphere. Using the Si X/S X and Ca XIV/Ar XIV diagnostics, we find distinct differences between the FIP bias of the leading and following polarities of the active region. The widths of the IRIS Si IV lines exhibited clear differences between the leading and following polarity regions, indicating increased unresolved wave activity in the following polarity region compared to the leading polarity region, with the chromospheric velocities derived using the Mg II lines exhibiting comparable, albeit much weaker, behaviour. These results are consistent with plasma fractionation via resonant/non-resonant waves at different locations in the solar chromosphere following the ponderomotive force model, and indicate that IRIS could be used to further study this fundamental physical process.

Previous examinations of fully convective M-dwarf stars have highlighted enhanced rates of nanoflare activity on these distant stellar sources. However, the specific role the convective boundary, which is believed to be present for spectral types earlier than M2.5V, plays on the observed nanoflare rates is not yet known. Here, we utilize a combination of statistical and Fourier techniques to examine M-dwarf stellar lightcurves that lie on either side of the convective boundary. We find that fully convective M2.5V (and later subtypes) stars have greatly enhanced nanoflare rates compared with their pre-dynamo mode-transition counterparts. Specifically, we derive a flaring power-law index in the region of 3.00 ± 0.20, alongside a decay timescale of 200 ± 100 s for M2.5V and M3V stars, matching those seen in prior observations of similar stellar subtypes. Interestingly, M4V stars exhibit longer decay timescales of 450 ± 50 s, along with an increased power-law index of 3.10 ± 0.18, suggesting an interplay between the rate of nanoflare occurrence and the intrinsic plasma parameters, e.g., the underlying Lundquist number. In contrast, partially convective (i.e., earlier subtypes from M0V to M2V) M-dwarf stars exhibit very weak nanoflare activity, which is not easily identifiable using statistical or Fourier techniques. This suggests that fully convective stellar atmospheres favor small-scale magnetic reconnection, leading to implications for the flare-energy budgets of these stars. Understanding why small-scale reconnection is enhanced in fully convective atmospheres may help solve questions relating to the dynamo behavior of these stellar sources.

We present the first quiet Sun spectropolarimetric observations obtained with the Visible SpectroPolarimeter at the 4 m Daniel K. Inouye Solar Telescope. We recorded observations in a wavelength range that includes the magnetically sensitive Fe i 6301.5/6302.5 Å doublet. With an estimated spatial resolution of 0.″08, this represents the highest spatial resolution full-vector spectropolarimetric observations ever obtained of the quiet Sun. We identified 53 small-scale magnetic elements, including 47 magnetic loops and four unipolar magnetic patches, with linear and circular polarization detected in all of them. Of particular interest is a magnetic element in which the polarity of the magnetic vector appears to change three times in only 400 km and which has linear polarization signals throughout. We find complex Stokes V profiles at the polarity inversion lines of magnetic loops and discover degenerate solutions, as we are unable to conclusively determine whether these arise due to gradients in the atmospheric parameters or smearing of opposite-polarity signals. We analyze a granule that notably has linear and circular polarization signals throughout, providing an opportunity to explore its magnetic properties. On this small scale, we see the magnetic field strength range from 25 G at the granular boundary to 2 kG in the intergranular lane (IGL) and sanity-check the values with the weak and strong field approximations. A value of 2 kG in the IGL is among the highest measurements ever recorded for the internetwork.