arXiv subjects

C. J. Díaz Baso

Publications and source records attributed to C. J. Díaz Baso.

At least 19 recordsLinked to original sources

arXiv2026

Wave excitation by a collapsing granule: insights from IFU observations and high-resolution RMHD simulations

Context. Granular collapse is an ubiquitous process of granular evolution on the solar surface, but it is hard to analyze in sufficient spatial, temporal, and spectral detail. Aims. We analyze the change in physical conditions in the photosphere during a specific granular collapse event and the subsequent atmospheric response. Methods. We contrast a high-resolution radiative magneto-hydrodynamic simulation of a granular collapse performed using the CO5BOLD code with the recent integral field unit observations carried out using the MiHI instrument at the Swedish 1-m Solar Telescope. Results. Our analysis shows that the observed and simulated granular collapse show remarkable similarity. Specifically, they both exhibit the signature of a wave pulse excited in the deep photosphere and visible up to the temperature minimum. This wave is detectable through a blue-wing emission in the observed and synthetic Na i D1 line. We also estimate the acoustic energy flux carried by the wave and analyze its initiation. Conclusions. Combining high-resolution IFU spectropolarimetry and state-of-the-art simulations of the solar lower atmosphere, this study showcases our current capabilities in identifying specific physical processes taking place during the granular collapse and their impact on the atmosphere above.

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arXiv2026

Inspectorch: Efficient rare event exploration in solar observations

The Sun is observed in unprecedented detail, enabling studies of its activity on very small spatiotemporal scales. However, the large volume of data collected by our telescopes cannot be fully analyzed with conventional methods. Popular machine learning methods identify general trends from observations, but tend to overlook unusual events due to their low frequency of occurrence. We study the applicability of unsupervised probabilistic methods to efficiently identify rare events in multidimensional solar observations and optimize our computational resources to the study of these extreme phenomena. We introduce Inspectorch, an open-source framework that utilizes flow-based models: flexible density estimators capable of learning the multidimensional distribution of solar observations. Once optimized, it assigns a probability to each sample, allowing us to identify unusual events. We apply this approach by applying it to observations from the Hinode Spectro-Polarimeter, the Interface Region Imaging Spectrograph, the Microlensed Hyperspectral Imager at Swedish 1-m Solar Telescope, the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory and the Extreme Ultraviolet Imager on board Solar Orbiter. We find that the algorithm assigns consistently lower probabilities to spectra that exhibit unusual features. For example, it identifies profiles with very strong Doppler shifts, uncommon broadening, and temporal dynamics associated with small-scale reconnection events, among others. As a result, Inspectorch demonstrates that density estimation using flow-based models offers a powerful approach to identifying rare events in large solar datasets. The resulting probabilistic anomaly scores allow computational resources to be focused on the most informative and physically relevant events. We make our Python package publicly available at https://github.com/cdiazbas/inspectorch.

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arXiv2026

Accelerating 3D Non-LTE Synthesis with Graph Neural Networks

Spectropolarimetric interpretation of chromospheric lines requires solving the radiative transfer problem under non-local thermodynamic equilibrium (non-LTE) conditions. This means computing atomic-level populations self-consistently with the radiation field. While traditional inversion codes employ 1.5D approximations, they neglect horizontal radiative transfer, which can be significant near magnetic structures and in the chromosphere. We present a method to solve 3D atomic-level populations using Graph Neural Networks (GNNs), extending prior 1.5D work to the full 3D domain. By discretizing the solar atmosphere as a directed graph, in which nodes encode physical properties and edges encode spatial distances, an Encode-Process-Decode GNN propagates information to efficiently capture radiative coupling. The network is trained on a Bifrost simulation using Ca II populations from Multi3D as ground truth. The trained GNN accurately predicts populations of the five-level Ca II atom plus continuum. Correlations exceed 0.99 in the photosphere and mid-chromosphere; errors in the upper chromosphere remain unbiased. Inference is $\sim 10^6$ times faster than traditional iterative solvers. Spectral synthesis of the Ca II 8542 Å line yields intensity profiles with $< 2 \%$ mean residuals relative to the full 3D solution. This framework bypasses the computational bottleneck of iterative solvers while preserving essential non-LTE physics, including horizontal transfer, paving the way toward routine 3D non-LTE inversions.

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arXiv2026

IRIS NUV diagnostics for Ellerman bombs: spectral properties, thermodynamics, and formation height

Context. Ellerman bombs (EBs) are observational signatures of small-scale magnetic reconnection, key to understanding the lower solar atmosphere. While their role in active regions has been widely studied using the H$α$ line, near-ultraviolet (NUV) spectra routinely observed by the Interface Region Imaging Spectrograph (IRIS) offer a promising alternative for EB identification, enabling large-scale studies. Aims. We aim to identify the most important spectral signatures of EBs in the IRIS NUV spectra. With this, we seek to develop a robust criterion for their detection solely using the IRIS NUV spectra. In parallel, we determine the typical atmospheric stratification associated with EBs. Methods. We used four coordinated observations between the Swedish 1-m Solar Telescope (SST) and IRIS. Using the H$α$ line as a reference, we detected 18 different EBs and studied their associated IRIS NUV spectra. In addition, we used the IRIS$^{2+}$ inversion tool to infer the temperature, line-of-sight velocity, and non-thermal broadening from the EB spectra. Results. The defining feature of EBs in the IRIS NUV is the enhancement of the wings of the subordinated Mg II triplet in between the Mg II h&k lines. Inversions reveal that these signatures are produced by localized temperature increase of $Δ$ T~1650 K around log$τ$=-3.8. Using only the Mg II triplet signatures, we found a detection criterion that successfully recovered 14 of 18 H$α$-detected EBs. In addition, the shape of the Mg II h&k lines in relation to the Mg II triplet can serve as a proxy for the EB formation height. Conclusions. The NUV spectrum observed by IRIS is a good candidate for detecting EBs, opening the doors to large-scale studies across the extensive IRIS database, removing the dependence on H$α$ observations.

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arXiv2025

Thermodynamic and magnetic evolution of an eruptive C-class solar flare observed with SST/TRIPPEL-SP

Solar flares are complex phenomena driven by the release of magnetic energy, but a large energy reservoir is not sufficient to determine their eruptive potential; the magnetic topology and plasma dynamics play a key role. We investigate the thermodynamic and magnetic properties of the solar atmosphere during the rise, peak, and decay phases of a C5.1-class flare and filament eruption in active region NOAA 12561 on 2016 July 7, to understand the origin and atmospheric response of this event. High spatial and spectral resolution spectropolarimetric observations of the chromospheric Ca II 8542A line and nearby photospheric lines were obtained with the TRIPPEL-SP spectropolarimeter at the Swedish 1-m Solar Telescope. Using non-local thermodynamic equilibrium (NLTE) inversions and non-force-free field (NFFF) magnetic extrapolations, we followed the event's evolution from its precursor to its decay. Before the flare, our analysis reveals a complex, sheared magnetic topology with a high free energy content ($\sim2\times10^{30}$ erg). In this precursor phase, we detected persistent, localized heating (temperature increase of $\sim$2000 K) with strong downflows ($\sim$10-20 km/s) deep in the atmosphere. This heating was co-spatial with a bald-patch region, suggesting that low-altitude magnetic reconnection could destabilize the filament of the region. The flare's rise phase was marked by the filament's eruption, with a total speed larger than $\sim$70 km/s, when combining inversions and plane-of-sky motions. Following the eruption, the free energy decreased by $\sim$30$\%$ as post-flare loops formed, connecting the flare ribbons and channeling the released energy into the lower atmosphere. The flare ribbons exhibited significant heating to $\sim$8500 K and downflows up to $\sim$10 km/s, consistent with energy deposition along reconnected loops.

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arXiv2025

Chromospheric velocities in an M3.2 flare using He I 1083.0 nm and Ca II 854.2 nm

We study the chromospheric LOS velocities during the GOES M3.2 flare (SOL2013-05-17T08:43) using simultaneous spectroscopic data of the He I 1083.0 nm triplet and Ca II 854.2 nm line. A filament was present in the flaring area. The observational data were acquired with the VTT (Tenerife, Spain) and covered the pre-flare, flare, and post-flare phases. Spectroscopic inversion techniques (HAZEL and STiC) were applied individually to He I and Ca II lines to recover the atmospheric parameters. Different inversion configurations were tested for Ca II and two families of solutions were found to explain the red asymmetry of the profiles: a redshifted emission feature or a blueshifted absorption feature. These solutions could explain two different flare scenarios (condensation vs. evaporation). The ambiguity was solved by comparing these results to the He I inferred velocities. At the front of the flare ribbon, we observed a thin, short-lived blueshifted layer. This is seen in both spectral regions but is much more pronounced in He I, with velocities of up to -10 km/s. In addition, at the front we found the coexistence of multiple He I profiles within one pixel. The central part of the ribbon is dominated by He I and Ca II redshifted emission profiles. A flare-loop system, visible only in He I absorption and not in Ca II, becomes visible in the post-flare phase and shows strong downflows at the footpoints of up to 39 km/s. In the flare, the Ca II line represents lower heights compared to the quiet Sun, with peak sensitivity shifting from $\log τ\simeq -5.2$ to $\log τ\simeq -3.5$. The inferred LOS velocities support a cool-upflow scenario at the leading edge of the flare. The solar filament in the region remained stable. The inclusion of the He I triplet in the analysis helped resolve the ambiguity between two possible solutions for the plasma velocities detected in the Ca II line.

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arXiv2025

Automatic detection of Ellerman bombs using Deep Learning

Ellerman bombs (EBs) are observable signatures of photospheric small-scale magnetic reconnection events. The reliable automatic detection of EBs would enable the study of the impact of magnetic reconnection on the Sun's dynamics. We aim to develop a method to automatically detect EBs in H$α$ observations from the Swedish 1-m Solar Telescope (SST) and in SDO/AIA observations using the 1600Å, 1700Å, 171Å and 304Å passbands. We trained models based on neural networks (NNs) to perform automatic detection of EBs. Additionally, we used different types of NNs to study how different properties contribute to the detection of EBs. We find that for SST observations, the NN-based models are proficient at detecting EBs. With sufficiently high spectral resolution, the spatial context is not required to detect EBs. However, as we degrade the spectral and spatial resolution, the spatial information becomes more important. Models that include both dimensions perform best. For SDO/AIA, the models struggle to reliably distinguish between EBs and bright patches of different origin. Permutation feature importance revealed that the H$α$ line wings (around $\pm$1 Å from line center) are the most informative features for EB detection. For the SDO/AIA case, the 1600Å channel is the most relevant one when used in combination with 171Å and 304Å. The combination of the four different SDO/AIA passbands is not informative enough to accurately classify EBs. From our analysis of a few sample SDO/AIA 1600Å and 1700Å light curves, we conclude that inclusion of the temporal variation may be a significant step towards establishing an effective EB detection method that can be applied to the extensive SDO/AIA database of observations. Abstract modified for ArXiv purposes.

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arXiv2025

High flow speeds and transition-region like temperatures in the solar chromosphere during flux emergence

Context: Flux emergence in the solar atmosphere is a complex process that causes a release of magnetic energy as heat and acceleration of solar plasma at a variety of spatial scales. Methods: We analysed imaging spectropolarimetric data taken in the He 1083 nm line. This line is sensitive to temperatures larger than 15 kK, unlike diagnostics such as \MgIIhk, \CaIIHK, and \Halpha, which lose sensitivity already at 15 kK. The He I data is complemented by imaging spectropolarimetry in the \CaIIK, \Feline, and \Caline\ lines. We employed inversions to determine the magnetic field and vertical velocity in the solar atmosphere. We computed He 1083 nm profiles from a radiation-MHD simulation of the solar atmosphere to help interpretation of the observations. Results: We find fast-evolving blob-like emission features in the He 1083 nm triplet at locations where the magnetic field is rapidly changing direction, and these are likely sites of magnetic reconnection. We fit the line with a model consisting of an emitting layer located below a cold layer representing the fibril canopy. The modelling provides evidence that this model, while simple, catches the essential characteristics of the line formation. The morphology of the emission in the He 1083 nm line is localized and blob-like, unlike the emission in the \CaIIK\ line, which is more filamentary. Conclusions: The modelling shows that the \Heline\ emission features and their Doppler shifts can be caused by opposite-polarity reconnection and/or horizontal current sheets below the canopy layer in the chromosphere. Based on the high observed Doppler width and the blob-like appearance of the emission features, we conjecture that at least a fraction of them are produced by plasmoids. We conclude that transition-region-like temperatures in the deeper layers of the active region chromosphere are more common than previously thought.

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arXiv2024

Spectral resolution effects on the information content in solar spectra

When interpreting spectropolarimetric observations of the solar atmosphere, wavelength variations of the emergent intensity and polarization translate into information on the depth stratification of physical parameters. We aim to quantify how the information content contained in a representative set of polarized spectra depends on the spectral resolution and spectral sampling. We use a state-of-the-art numerical simulation of a sunspot to synthesize polarized spectra of magnetically sensitive neutral iron lines. We then apply various degrees of spectral degradation to the synthetic spectra and analyze the impact on its dimensionality using PCA and wavelet decomposition. Finally, we apply the SIR code to the degraded synthetic data, to assess the effect of spectral resolution on the inferred parameters. We find that regions with strong magnetic fields where convection is suppressed produce less complex Stokes profiles. On the other hand, regions with strong gradients give rise to more complex Stokes profiles that are more affected by spectral degradation. The degradation also makes the inversion problem more ill-defined, so inversion models with a larger number of free parameters overfit and give wrong estimates. The impact of spectral degradation depends on multiple factors, including spectral resolution, noise level, line spread function (LSF) shape, complexity of the solar atmosphere, and the degrees of freedom in our inversion methods. Having a finely sampled spectrum may be more beneficial than achieving a higher signal-to-noise ratio per wavelength bin. Considering the inclusion of different spectral lines that can counter these effects, and calibrating the effective degrees of freedom in modeling strategies, are also important considerations. These strategies are crucial for the accurate interpretation and have the potential to offer more cost-effective solutions.

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arXiv2024

Exploring spectropolarimetric inversions using neural fields. Solar chromospheric magnetic field under the weak-field approximation

Full-Stokes polarimetric datasets, originating from slit-spectrograph or narrow-band filtergrams, are routinely acquired nowadays. The data rate is increasing with the advent of bi-dimensional spectropolarimeters and observing techniques that allow long-time sequences of high-quality observations. There is a clear need to go beyond the traditional pixel-by-pixel strategy in spectropolarimetric inversions by exploiting the spatiotemporal coherence of the inferred physical quantities. We explore the potential of neural networks as a continuous representation of the physical quantities over time and space (also known as neural fields), for spectropolarimetric inversions. We have implemented and tested a neural field to perform the inference of the magnetic field vector (approach also known as physics-informed neural networks) under the weak-field approximation (WFA). By using a neural field to describe the magnetic field vector, we can regularize the solution in the spatial and temporal domain by assuming that the physical quantities are continuous functions of the coordinates. We investigated the results in synthetic and real observations of the Ca II 8542 A line. We also explored the impact of other explicit regularizations, such as using the information of an extrapolated magnetic field, or the orientation of the chromospheric fibrils. Compared to the traditional pixel-by-pixel inversion, the neural field approach improves the fidelity of the reconstruction of the magnetic field vector, especially the transverse component. This implicit regularization is a way of increasing the effective signal-to-noise of the observations. Although it is slower than the pixel-wise WFA estimation, this approach shows a promising potential for depth-stratified inversions, by reducing the number of free parameters and inducing spatio-temporal constraints in the solution.

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arXiv2024

Properties of sunspot light bridges on a geometric height scale

Investigating light bridges (LBs) helps us comprehend key aspects of sunspots. However, few studies have analyzed the properties of LBs in terms of the geometric height, which is a more realistic perspective given the corrugation of the solar atmosphere. We aim to shed light on LBs by studying the variation in their physical properties with geometric height. We used the SICON code to infer the physical quantities in terms of the optical depth and the Wilson depression values of three LBs hosted by a sunspot observed with Hinode/SP in the Fe I 630 nm pair lines. We also used SIR inversions to cross-check the height variation of the field inclination in the LBs. In both output sets, we performed linear interpolation to convert the physical parameters from optical depth into a geometric height scale in each pixel. We classified each LB as filamentary, grainy, or umbral. They appear as ridges that reach different maximum heights, with the umbral LB being the deepest. While the filamentary LB hosts a plasma inflow from the penumbra, the results for the grainy LB are compatible with an injection of hot plasma through convective cells of reduced field strength. Only a few positions reveal hints suggesting a cusp-like magnetic canopy. Moreover, strong gradients in the magnetic field strength and inclination usually exhibit enhanced electric currents, with the filamentary LB having remarkably strong currents that appear to be related to chromospheric events. The height stratification in filamentary and grainy LBs differ, indicating diverse mechanisms at work. Our results are in general incompatible with a magnetic canopy scenario, and further analysis is needed to confirm whether it exists along the entire LB or only at specific locations. Furthermore, this work assesses the usefulness of SICON when determining the height stratification of solar structures.

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arXiv2023

Designing wavelength sampling for Fabry-Pérot observations. Information-based spectral sampling

Fabry-Pérot interferometers (FPIs) have become very popular in solar observations because they offer a balance between cadence, spatial resolution, and spectral resolution through a careful design of the spectral sampling scheme according to the observational requirements of a given target. However, an efficient balance requires knowledge of the expected target conditions, the properties of the chosen spectral line, and the instrumental characteristics. Our aim is to find a method that allows finding the optimal spectral sampling of FPI observations in a given spectral region. In this study, we propose a technique based on a sequential selection approach where a neural network is used to predict the spectrum (or physical quantities, if the model is known) from the information at a few points. Only those points that contain relevant information and improve the model prediction are included in the sampling scheme. The method adapts the separation of the points according to the spectral resolution of the instrument, the typical broadening of the spectral shape, and the typical Doppler velocities. The experiments using the CaII 8542 A line show that the resulting wavelength scheme naturally places more points in the core than in the wings, consistent with the sensitivity of the spectral line at each wavelength interval. The method can also be used as an accurate interpolator, to improve the inference of the magnetic field when using the weak-field approximation. Overall, this method offers an objective approach for designing new instrumentation or observing proposals with customized configurations for specific targets. This is particularly relevant when studying highly dynamic events in the solar atmosphere with a cadence that preserves spectral coherence without sacrificing much information.

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arXiv2023

Center-to-limb variation of spectral lines and continua observed with SST/CRISP and SST/CHROMIS

Observations of center-to-limb variations (CLV) of spectral lines and continua provide a good test for the accuracy of models of solar and stellar atmospheric structure and spectral-line formation. They are also widely used to constrain elemental abundances and are becoming increasingly important in atmospheric studies of exoplanets. However, only a few such data sets exist for chromospheric lines. We aim to create a set of standard profiles by means of mosaics made with the CRISP and CHROMIS instruments of the Swedish 1-m Solar Telescope (SST), as well as to explore the robustness of said profiles obtained using this method. For each spectral line we use a mosaic that ranges from the center to the limb. Each of these mosaics are averaged down to 50 individual spectral profiles, spaced by 0.02 in the $μ$ scale. These profiles are corrected for p-mode oscillations, and their line parameters (equivalent width, line shift, full-width at half-maximum, and line depth) are then compared against literature values where possible. We present a set of 50 average profiles that are spaced equidistantly along the cosine of the heliocentric angle ($μ$) by steps of 0.02 for five continuum points between 4001 and 7772 Å, as well as ten of the most commonly observed spectral lines at the SST (Ca II H & K, H$β$, Mg I 5173 Å, C I 5380 Å, Fe I 6173 Å, Fe I 6301 Å, H$α$, O I 7772 Å, and Ca II 8542 Å). Center-to-limb variation of line profiles and continua are shared in the CDS as machine-readable tables; providing a quantitative constraint on theoretical models that aim to model stellar atmospheres.

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arXiv2022

Radiative losses in the chromosphere during a C-class flare

Solar flares release an enormous amount of energy into the corona. A substantial fraction of this energy is transported to the lower atmosphere, which results in chromospheric heating. The mechanisms that transport energy to the lower solar atmosphere during a flare are still not fully understood. We aim to estimate the temporal evolution of the radiative losses in the chromosphere at the footpoints of a C-class flare, in order to set observational constraints on the electron beam parameters of a RADYN flare simulation. We estimated the radiative losses from hydrogen, and singly ionized Ca and Mg using semi-empirical model atmospheres. To estimate the integrated radiative losses in the chromosphere the net cooling rates were integrated between the temperature minimum and the height where the temperature reaches 10 kK. The stratification of the net cooling rate suggests that the Ca IR triplet lines are responsible for most of the radiative losses in the flaring atmosphere. During the flare peak time, the contribution from Ca II H & K and Mg II h & k lines are strong and comparable to the Ca IR triplet ($\sim$32 kW m$^{-2}$). Since our flare is a relatively weak event the chromosphere is not heated above 11 kK, which in turn yields a subdued Lyα contribution ($\sim$7 kW m$^{-2}$). The temporal evolution of total integrated radiative losses exhibits sharply-rising losses (0.4 kW m$^{-2}$ s$^{-1}$) and a relatively slow decay (0.23 kW~m$^{-2}$ s$^{-1}$). The maximum value of total radiative losses is reached around the flare peak time, and can go up to 175 kW m$^{-2}$ for a single pixel located at footpoint. After a small parameter study, we find the best model-data consistency in terms of the amplitude of radiative losses and the overall atmospheric structure with a RADYN flare simulation in the injected energy flux of $5\times10^{10}$ erg s$^{-1}$ cm$^{-2}$.

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arXiv2022

Spatio-temporal analysis of chromospheric heating in a plage region

Our knowledge of the heating mechanisms that are at work in the chromosphere of plage regions remains highly unconstrained from observational studies. The purpose of our study is to estimate the chromospheric heating terms from a plage dataset, characterize their spatio-temporal distribution and set constraints on the heating processes that are at work. We make use of NLTE inversions to infer a model of the photosphere and chromosphere of a plage dataset acquired with the Swedish 1-m Solar Telescope. We use this model atmosphere to calculate the chromospheric radiative losses from H i, Ca ii and Mg ii atoms. We approximate the chromospheric heating terms by the net radiative losses predicted by the inverted model. In order to make the analysis of time-series over a large field-of-view computationally tractable, we make use of a neural network. In the lower chromosphere, the contribution from the Ca ii lines is dominant and located in the surroundings of the photospheric footpoints. In the upper chromosphere, the H i contribution is dominant. Radiative losses in the upper chromosphere form an homogeneous patch that covers the plage region. The net radiative losses can be split in a periodic component with an average amplitude of ampQ = 7.6 kW m^{-2} and a static (or very slowly evolving) component with a mean value of -26.1 kW m^{-2}. Our interpretation is that in the lower chromosphere, the radiative losses are tracing the sharp lower edge of the hot magnetic canopy, where the electric current is expected to be large. In the upper chromosphere, both the magnetic field and the distribution of net radiative losses are room-filling, whereas the amplitude of the periodic component is largest. Our results suggest that acoustic wave heating may be responsible for one third of the energy deposition in the upper chromosphere, whereas other heating mechanisms must be responsible for the rest.

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arXiv2021

Bayesian Stokes inversion with Normalizing flows

Stokes inversion techniques are very powerful methods for obtaining information on the thermodynamic and magnetic properties of solar and stellar atmospheres. In recent years, very sophisticated inversion codes have been developed that are now routinely applied to spectro-polarimetric observations. Most of these inversion codes are designed for finding an optimum solution to the nonlinear inverse problem. However, to obtain the location of potentially multimodal cases (ambiguities), the degeneracies, and the uncertainties of each parameter inferred from the inversions, algorithms such as Markov chain Monte Carlo (MCMC), require to evaluate the likelihood of the model thousand of times and are computationally costly. Variational methods are a quick alternative to Monte Carlo methods by approximating the posterior distribution by a parametrized distribution. In this study, we introduce a highly flexible variational inference method to perform fast Bayesian inference, known as normalizing flows. Normalizing flows are a set of invertible, differentiable, and parametric transformations that convert a simple distribution into an approximation of any other complex distribution. If the transformations are conditioned on observations, the normalizing flows can be trained to return Bayesian posterior probability estimates for any observation. We illustrate the ability of the method using a simple Milne-Eddington model and a complex non-LTE inversion. However, the method is extremely general and other more complex forward models can be applied. The training procedure need only be performed once for a given prior parameter space and the resulting network can then generate samples describing the posterior distribution several orders of magnitude faster than existing techniques.

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arXiv2021

Active region chromospheric magnetic fields

Context. A proper estimate of the chromospheric magnetic fields is believed to improve modelling of both active region and coronal mass ejection evolution. Aims. We investigate the similarity between the chromospheric magnetic field inferred from observations and the field obtained from a magnetohydrostatic (MHS) extrapolation. Methods. Based Fe i 6173 Å and Ca ii 8542 Å observations of NOAA active region 12723, we employed the spatially-regularised weak-field approximation (WFA) to derive the vector magnetic field in the chromosphere from Ca ii, as well as non-LTE inversions of Fe i and Ca ii to infer a model atmosphere for selected regions. Milne-Eddington inversions of Fe i serve as photospheric boundary for the MHS model that delivers the three-dimensional field, gas pressure and density. Results. For the line-of-sight component, the MHS chromospheric field generally agrees with the non-LTE inversions and WFA, but tends to be weaker than those when larger in magnitude than 300 G. The observationally inferred transverse component is stronger, especially in magnetically weaker regions, yet the qualitative distribution with height is similar to the MHS results. For either field component the MHS chromospheric field lacks the fine structure derived from the inversions. Furthermore, the MHS model does not recover the magnetic imprint from a set of high fibrils connecting the main polarities. Conclusions. The MHS extrapolation and WFA provide a qualitatively similar chromospheric field, where the azimuth of the former is better aligned with Ca ii 8542 Å fibrils than that of the WFA, especially outside strong-field concentrations. The amount of structure as well as the transverse field strengths are underestimated by the MHS extrapolation. This underscores the importance of considering a chromospheric magnetic field constraint in data-driven modelling of active regions.

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arXiv2021

An observationally-constrained model of strong magnetic reconnection in the solar chromosphere. Atmospheric stratification and estimates of heating rates

The evolution of the photospheric magnetic field plays a key role in the energy transport into the chromosphere and the corona. In active regions, newly emerging magnetic flux interacts with the pre-existent magnetic field, which can lead to reconnection events that convert magnetic energy to thermal energy. We aim to study the heating caused by a strong reconnection event that was triggered by magnetic flux cancellation. We use imaging-spectropolarimetric data in the Fe I 6301A, Fe I 6302A, Ca II 8542A and Ca II K obtained with the CRISP and CHROMIS instruments at the Swedish 1-m Solar Telescope. This data was inverted using multi-atom, multi-line non-LTE inversions using the STiC code. The inversion yielded a three-dimensional model of the reconnection event and surrounding atmosphere, including temperature, velocity, microturbulence, magnetic file configuration, and the radiative loss rate. The model atmosphere shows the emergence of magnetic loops with a size of several arcsecs into a pre-existing predominantly unipolar field. Where the reconnection region is expected to be, we see an increase in the chromospheric temperature of roughly 2000 K as well as bidirectional flows of the order of 10 km s$^{-1}$ emanating from the region. We see bright blobs of roughly 0.2 arcsec diameter in the Ca II K moving at a plane-of-the-sky velocity of order 100 km s$^{-1}$ and a blueshift of 100 km s$^{-1}$, which we interpret as plasmoids ejected from the same region. This evidence is consistent with theoretical models of reconnection and we thus conclude that reconnection is taking place. The chromospheric radiative losses at the reconnection site in our inferred model are as high as 160 kW m$^{-2}$, providing a quantitative constraint on theoretical models that aim to simulate reconnection caused by flux emergence in the chromosphere.

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