arXiv subjects

Matthias Rempel

Publications and source records attributed to Matthias Rempel.

At least 19 recordsLinked to original sources

arXiv2026

Probing the Physics of the Solar Corona with High-Resolution Observations using SKA-Mid

We examine the capability of the SKA-Mid telescope for probing solar coronal structure and evolution. Using radiative magnetohydrodynamics simulations of a solar flare, we synthesise radio emission in bands available to SKA-Mid. SKA-Mid observations would provide important constraints on plasma processes that are important to diverse astrophysical environments, including flares/eruptions, magnetic reconnection, particle acceleration, and gyro-emission processes. Observations with the AA4 configuration would reveal fine-scale structures in the solar atmosphere, making SKA-Mid a complementary telescope to other high resolution solar observatories operating at optical, infrared, and XUV wavelengths. Estimates of coronal scattering suggest that angular broadening rather than instrumental resolution (0.1'' at 10 GHz) will limit the detection of the finest structure under typical conditions. The extent of angular broadening depends on the nature of turbulence in the corona, and the longer baselines of SKA-Mid will serve to provide new observational constraints on coronal structure.

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arXiv2026

Data-inspired simulation of AR 11158

We present a data-inspired simulation of NOAA active region AR 11158. We simulate the formation of a collisional polarity inversion line (cPIL) by moving sunspots in a quadrupolar configuration along the centroid positions extracted from AR 11158. This process builds up free energy in the corona exceeding $4\cdot 10^{32}$ erg, out of which about $2\cdot 10^{32}$ erg are released in a X-flare followed by a series of smaller flares in the B to M range. The 4 strongest flares are associated with coronal mass ejections. About 1-2 hours prior to the X-flare a magnetic flux rope (MFR) is forming above the cPIL. About 5 minutes before the flare an upflow at chromospheric heights indicates a rise of the MFR. The eruption starts when parts of the MFR enter regions with a decay index larger than 1.5, indicating that the flare initiation is consistent with the torus instability. Comparing the series of flares in this simulation to properties of observed flares, we find a comparable trend between flare energy and GOES X-ray flux, but flare duration falls into the short end of the observed solar distribution. As a consequence, energy fluxes into the flare ribbons can be substantial, reaching $10^{13}$ erg cm$^{-2}$ s$^{-1}$ for the simulated X-flare. The X-flare causes step-function like changes of the horizontal magnetic field in the photosphere, a propagation of a momentum pulse into the convection zone and quasi-periodic pulsations in the volume of the corona with periods from sub-seconds to multiple 10 seconds.

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arXiv2026

Chromospheric magnetic field extrapolations reveal the flux-rope configuration of a solar filament

Solar eruptions are powered by the release of magnetic energy stored in the lower solar atmosphere, but the pre-eruptive magnetic configuration of filament channels remains difficult to determine. A central question is whether this energy is stored in a pre-existing magnetic flux rope or in a sheared arcade that forms a flux rope only during eruption. Resolving this ambiguity is critical for identifying instability thresholds and eruption triggers, yet photosphere-based extrapolations often provide insufficient constraints on the three-dimensional coronal field. Here, we introduce a data-driven magnetic field extrapolation framework that combines photospheric and chromospheric vector magnetograms in a unified multi-height optimization, while accounting for variable chromospheric formation heights and the 180{\deg} azimuthal ambiguity. Tests with radiative magnetohydrodynamic simulations show that photosphere-only extrapolations can misidentify the pre-eruptive magnetic configuration, whereas chromospheric vector constraints recover the three-dimensional structure substantially more accurately. Applied to multi-line spectropolarimetric observations of an active region filament obtained with the Swedish Solar Telescope, the method reveals a reconstructed magnetic field consistent with a pre-eruptive flux-rope configuration. These results show that chromospheric vector magnetic measurements can provide decisive constraints on filament magnetic configuration and open a path toward diagnosing magnetic-energy storage and instability in eruptive solar active regions.

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arXiv2026

Neural blind deconvolution to reconstruct high-resolution ground-based solar observations

Ground-based solar observations enable unprecedented spatial, spectral, and temporal resolution of the lower solar atmosphere, yet Earths turbulent atmosphere imposes significant limitations, requiring advanced post-facto image reconstruction. State-of-the-art reconstruction methods are based on restoring a burst of short exposure frames to a single observation. Limitations of these techniques arise due to the sparse information about the atmospheric point spread function (PSF) that degrade the observations and consequently the quality of reconstructions. We develop a novel image reconstruction method to achieve unprecedented spatial resolution from short exposure image bursts. This can provide high-quality reconstructions and therefore advance the study of the smallest spatial scales from the solar photosphere to the chromosphere. In this study, we present a novel approach for high-resolution solar image reconstruction based on physics-informed neural networks. In the training process, the neural network maps coordinate points directly to their corresponding intensity values while simultaneously updating the PSF parameters. The method convolves the true object from the neural network with the estimated PSFs and optimizes the network by minimizing the loss between the synthesized and real short-exposure image burst. This approach enables the simultaneous estimation of both the degrading PSF and the real high-resolution intensity distribution. We demonstrate the method on synthetic intensity data derived from a radiative MHD simulation and apply it to high-resolution observations from GREGOR and DKIST. Our results demonstrate the ability to reconstruct small-scale solar features that exceed the reconstruction performance of state-of-the-art reconstruction methods. With this approach we lay the foundation for future spatially varying PSFs.

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arXiv2026

Measuring the Coronal Magnetic Field with 2D Coronal Seismology: A Forward-Modeling Validation

In recent years, a two-dimensional (2D) coronal seismology technique applied to spectral-imaging data from the Coronal Multi-channel Polarimeter (CoMP) and UCoMP has enabled routine measurement of the global coronal magnetic field. The technique combines coronal transverse wave phase speed from Doppler measurements with electron densities from the Fe \sc{xiii}\rm{} 10798/10747 \AA\ intensity ratio to infer the magnetic field strength, while the wave propagation directions from Doppler measurements trace the magnetic field direction. To validate the accuracy and robustness of this method, we use forward modeling of a MURaM simulation that produces open and closed magnetic structures with excited waves. From the synthetic Doppler velocity, Fe \sc{xiii}\rm{} infrared line intensities, and linear polarization signals, we apply the 2D coronal seismology technique to estimate the magnetic field strength and direction. A comparison with the simulation ground truth shows close agreement, indicating that the technique can recover the line-of-sight emissivity-weighted magnetic field direction and strength with high accuracy. We also perform a parameter-space analysis to quantify sensitivities of the method to parameter choice. These findings provide practical guidance for CoMP/UCoMP-like analysis and demonstrate that 2D coronal seismology can deliver reliable, LOS emissivity-weighted measurements of the coronal magnetic field from coronal wave observations.

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arXiv2025

Multi-height probing of horizontal flows in the solar photosphere

We tested whether simultaneous spectropolarimetric imaging in two magnetically sensitive optical spectral lines, which probe two different layers of the solar atmosphere (the photosphere and the temperature minimum), can help constrain the depth variation of horizontal flows. We first tested the feasibility of our method using Fourier local correlation tracking (FLCT) to track physical quantities at different optical depths ($\log\tau_{500}={-1,-2,-3,-4}$) in an atmosphere simulated with the MURaM code. We then inferred the horizontal distribution of the LOS magnetic field component from synthetic spectropolarimetric observations of Fe I 525.0 nm and Mg I b2 spectral lines, applied FLCT to the time sequence of these synthetic magnetograms, and compared our findings with the original height-dependent horizontal velocities. Tracking the LOS magnetic field component (which coincides with the vertical component at the disk center) yields horizontal velocities that, after appropriate temporal and spatial averaging, agree excellently with the horizontal component of the simulated velocities, both calculated at constant $\tau_{500}$ surfaces, up to the temperature minimum ($\log\tau_{500}=-3$). When tracking the temperature at constant $\tau_{500}$ surfaces, this agreement already breaks down completely at the mid photosphere ($\log\tau_{500}=-2$). Tracking the vertical component of the magnetic field inferred from synthetic observations of the Fe I 525.0 nm and the Mg I b2 spectral lines yields a satisfactory inference of the horizontal velocities in the mid-photosphere ($\log\tau_{500}\approx-1$) and the temperature minimum ($\log\tau_{500}\approx-3$), respectively. Our results indicate that high-spatial-resolution spectropolarimetric imaging in solar spectral lines can provide meaningful information about the horizontal plasma velocities over a range of heights.

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arXiv2025

Spectropolarimetric Inversion in Four Dimensions with Deep Learning (SPIn4D): II. A Physics-Informed Machine Learning Method for 3D Solar Photosphere Reconstruction

Inferring the three-dimensional (3D) solar atmospheric structures from observations is a critical task for advancing our understanding of the magnetic fields and electric currents that drive solar activity. In this work, we introduce a novel, Physics-Informed Machine Learning method to reconstruct the 3D structure of the lower solar atmosphere based on the output of optical depth sampled spectropolarimetric inversions, wherein both the fully disambiguated vector magnetic fields and the geometric height associated with each optical depth are returned simultaneously. Traditional techniques typically resolve the 180-degree azimuthal ambiguity assuming a single layer, either ignoring the intrinsic non-planar physical geometry of constant optical-depth surfaces (e.g., the Wilson depression in sunspots), or correcting the effect as a post-processing step. In contrast, our approach simultaneously maps the optical depths to physical heights, and enforces the divergence-free condition for magnetic fields fully in 3D. Tests on magnetohydrodynamic simulations of quiet Sun, plage, and a sunspot demonstrate that our method reliably recovers the horizontal magnetic field orientation in locations with appreciable magnetic field strength. By coupling the resolutions of the azimuthal ambiguity and the geometric heights problems, we achieve a self-consistent reconstruction of the 3D vector magnetic fields and, by extension, the electric current density and Lorentz force. This physics-constrained, label-free training paradigm is a generalizable, physics-anchored framework that extends across solar magnetic environments while improving the understanding of various solar puzzles.

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arXiv2025

PINN ME: A Physics-Informed Neural Network Framework for Accurate Milne-Eddington Inversions of Solar Magnetic Fields

Spectropolarimetric inversions of solar observations are fundamental for the estimation of the magnetic field in the solar atmosphere. However, instrumental noise, computational requirements, and varying levels of physical realism make it challenging to derive reliable solar magnetic field estimates. In this study, we present a novel approach for spectropolarimetric inversions based on Physics Informed Neural Networks (PINNs) to infer the photospheric magnetic field under the Milne-Eddington approximation (PINN ME). Our model acts as a representation of the parameter space, mapping input coordinates (t, x, y) to the respective spectropolarimetric parameters, which are used to synthesize the corresponding stokes profiles. By iteratively sampling coordinate points, synthesizing profiles, and minimizing the deviation from the observed stokes profiles, our method can find the set of Milne-Eddington parameters that best fit the observations. In addition, we directly include the point-spread-function to account for instrumental effects. We use a predefined parameter space as well as synthetic profiles from a radiative MHD simulation to evaluate the performance of our method and to estimate the impact of instrumental noise. Our results demonstrate that PINN ME achieves an intrinsic spatio-temporal coupling, which can largely mitigate observational noise and provides a memory-efficient inversion even for extended fields-of-view. Finally, we apply our method to observations and show that our method provides a high spatial coherence and can resolve small-scale features both in strong- and weak-field regions.

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arXiv2024

Magnetic Field Evolution of the Solar Active Region 13664

On 2024 May 10/11, the strongest geomagnetic storm since November 2003 has occurred, with a peak Dst index of -412 nT. The storm was caused by NOAA Active Region (AR) 13664, which was the source of a large number of coronal mass ejections and flares, including 12 X-class flares. Starting from about May 7, AR 13664 showed a steep increase in its size and (free) magnetic energy, along with increased flare activity. In this study, we perform 3D magnetic field extrapolations with the NF2 nonlinear-force free code based on physics informed neural networks (Jarolim et al. 2023). In addition, we introduce the computation of the vector potential to achieve divergence-free solutions. We extrapolate vector magnetograms from SDO/HMI at the full 12 minute cadence from 2024 May 5-00:00 to 11-04:36 UT, in order to understand the active regions magnetic evolution and the large eruptions it produced. The computed change in magnetic energy and free magnetic energy shows a clear correspondence to the flaring activity. Regions of free magnetic energy and depleted magnetic energy indicate the flare origin and are in good correspondence with observations in Extreme Ultraviolet. Our results suggest that the modeled solar flares are related to significant topological reconfigurations. We provide a detailed analysis of the X4.0-class flare on May 10, where we show that the interaction between separated magnetic domains is directly linked to major flaring events. With this study, we provide a comprehensive data set of the magnetic evolution of AR 13664 and make it publicly available for further analysis.

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arXiv2024

Spectropolarimetric Inversion in Four Dimensions with Deep Learning (SPIn4D): I. Overview, Magnetohydrodynamic Modeling, and Stokes Profile Synthesis

The National Science Foundation's Daniel K. Inouye Solar Telescope (DKIST) will provide high-resolution, multi-line spectropolarimetric observations that are poised to revolutionize our understanding of the Sun. Given the massive data volume, novel inference techniques are required to unlock its full potential. Here, we provide an overview of our "SPIn4D" project, which aims to develop deep convolutional neural networks (CNNs) for estimating the physical properties of the solar photosphere from DKIST spectropolarimetric observations. We describe the magnetohydrodynamic (MHD) modeling and the Stokes profile synthesis pipeline that produce the simulated output and input data, respectively. These data will be used to train a set of CNNs that can rapidly infer the four-dimensional MHD state vectors by exploiting the spatiotemporally coherent patterns in the Stokes profile time series. Specifically, our radiative MHD model simulates the small-scale dynamo actions that are prevalent in quiet-Sun and plage regions. Six cases with different mean magnetic fields have been conducted; each case covers six solar-hours, totaling 109 TB in data volume. The simulation domain covers at least $25\times25\times8$ Mm with $16\times16\times12$ km spatial resolution, extending from the upper convection zone up to the temperature minimum region. The outputs are stored at a 40 s cadence. We forward model the Stokes profile of two sets of Fe I lines at 630 and 1565 nm, which will be simultaneously observed by DKIST and can better constrain the parameter variations along the line of sight. The MHD model output and the synthetic Stokes profiles are publicly available, with 13.7 TB in the initial release.

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arXiv2024

Observations of Locally Excited Waves in the Low Solar Atmosphere Using the Daniel K. Inouye Solar Telescope (DKIST)

We present an interpretation of the recent Daniel K. Inouye Solar Telescope (DKIST) observations of propagating wavefronts in the lower solar atmosphere. Using MPS/University of Chicago MHD (MURaM) radiative magnetohydrodynamic simulations spanning solar photosphere, overshoot region, and lower chromosphere, we identify three acoustic-wave source mechanisms, each occurring at a different atmospheric height. We synthesize the DKIST Visible Broadband Imager (VBI) G-band, blue-continuum, and CaIIK signatures of these waves at high spatial and temporal resolution, and conclude that the wavefronts observed by DKIST likely originate from acoustic sources at the top of the solar photosphere overshoot region and in the chromosphere proper. The overall importance of these local sources to the atmospheric energy and momentum budget of the solar atmosphere is unknown, but one of the excitation mechanism identified (upward propagating shock interaction with down-welling chromospheric plasma resulting in acoustic radiation) appears to be an important shock dissipation mechanism. Additionally, the observed wavefronts may prove useful for ultra-local helioseismological inversions and promise to play an important diagnostic role at multiple atmospheric heights.

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arXiv2024

Magnetic flux in the Sun emerges unaffected by supergranular-scale surface flows

Magnetic flux emergence from the convection zone into the photosphere and beyond is a critical component of the behaviour of large-scale solar magnetism. Flux rarely emerges amid field-free areas at the surface, but when it does, the interaction between magnetism and plasma flows can be reliably explored. Prior ensemble studies identified weak flows forming near emergence locations, but the low signal-to-noise required averaging over the entire dataset, erasing information about variation across the sample. Here, we apply deep learning to achieve improved signal-to-noise, enabling a case-by-case study. We find that these associated flows are dissimilar across instances of emergence and also occur frequently in the quiet convective background. Our analysis suggests diminished influence of supergranular-scale convective flows and magnetic buoyancy on flux rise. Consistent with numerical evidence, we speculate that small-scale surface turbulence and / or deep-convective processes play an outsize role in driving flux emergence.

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arXiv2024

Spatial resolution effects on the solar open flux estimates

Spectropolarimetric observations used to infer the solar magnetic fields are obtained with a limited spatial resolution. The effects of this limited resolution on the inference of the open flux over the observed region have not been extensively studied. We aim to characterize the biases that arise in the inference of the mean flux density by performing an end-to-end study that involves the generation of synthetic data, its interpretation (inversion), and a comparison of the results with the original model. We synthesized polarized spectra of the two magnetically sensitive lines of neutral iron around 630\,nm from a state-of-the-art numerical simulation of the solar photosphere. We then performed data degradation to simulate the effect of the telescope with a limited angular resolution and interpreted (inverted) the data using a Milne-Eddington spectropolarimetric inversion code. We then studied the dependence of the inferred parameters on the telescope resolution. The results show a significant decrease in the mean magnetic flux density -- related to the open flux observed at the disk center -- with decreasing telescope resolution. The original net magnetic field flux is fully resolved by a 1m telescope, but a 20\,cm aperture telescope yields a 30\% smaller value. Even in the fully resolved case, the result is still biased due to the corrugation of the photospheric surface. Even the spatially averaged quantities, such as the open magnetic flux in the observed region, are underestimated when the magnetic structures are unresolved. The reason for this is the presence of nonlinearities in the magnetic field inference process. This effect might have implications for the modeling of large-scale solar magnetic fields; for example, those corresponding to the coronal holes, or the polar magnetic fields, which are relevant to our understanding of the solar cycle.

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arXiv2023

Advancing solar magnetic field extrapolations through multi-height magnetic field measurements

Non-linear force-free extrapolations are a common approach to estimate the 3D topology of coronal magnetic fields based on photospheric vector magnetograms. The force-free assumption is a valid approximation at coronal heights, but for the dense plasma conditions in the lower atmosphere, this assumption is not satisfied. In this study, we utilize multi-height magnetic field measurements in combination with physics-informed neural networks to advance solar magnetic field extrapolations. We include a flexible height-mapping, which allows us to account for the different formation heights of the observed magnetic field measurements. The comparison to analytical and simulated magnetic fields demonstrates that including chromospheric magnetic field measurements leads to a significant improvement of our magnetic field extrapolations. We also apply our method to chromospheric line-of-sight magnetograms, from the Vector Spectromagnetograph (VSM) on the Synoptic Optical Long-term Investigations of the Sun (SOLIS) observatory, in combination with photospheric vector magnetograms, from the Helioseismic Magnetic Imager (HMI) onboard the Solar Dynamic Observatory (SDO). The comparison to observations in extreme ultraviolet wavelengths shows that the additional chromospheric information leads to a better agreement with the observed coronal structures. In addition, our method intrinsically provides an estimate of the corrugation of the observed magnetograms. With this new approach, we make efficient use of multi-height magnetic field measurements and advance the realism of coronal magnetic field simulations.

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arXiv2023

Quantifying Poynting flux in the Quiet Sun Photosphere

Poynting flux is the flux of magnetic energy, which is responsible for chromospheric and coronal heating in the solar atmosphere. It is defined as a cross product of electric and magnetic fields, and in ideal MHD conditions it can be expressed in terms of magnetic field and plasma velocity. Poynting flux has been computed for active regions and plages, but estimating it in the quiet Sun (QS) remains challenging due to resolution effects and polarimetric noise. However, with upcoming DKIST capabilities, these estimates will become more feasible than ever before. Here, we study QS Poynting flux in Sunrise/IMaX observations and MURaM simulations. We explore two methods for inferring transverse velocities from observations - FLCT and a neural network based method DeepVel - and show DeepVel to be the more suitable method in the context of small-scale QS flows. We investigate the effect of azimuthal ambiguity on Poynting flux estimates, and we describe a new method for azimuth disambiguation. Finally, we use two methods for obtaining the electric field. The first method relies on idealized Ohm's law, whereas the second is a state-of-the-art inductive electric field inversion method PDFI SS. We compare the resulting Poynting flux values with theoretical estimates for chromospheric and coronal energy losses and find that some of Poynting flux estimates are sufficient to match the losses. Using MURaM simulations, we show that photospheric Poynting fluxes vary significantly with optical depth, and that there is an observational bias that results in underestimated Poynting fluxes due to unaccounted shear term contribution.

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arXiv2023

The Puzzling Structure of Solar Convection: Window into the Dynamo

The operation of the solar dynamo, with all of its remarkable spatio-temporal ordering, remains an outstanding problem of modern solar physics. A number of mechanisms that might plausibly contribute to its operation have been proposed, but the relative role played by each remains unclear. This uncertainty stems from continuing questions concerning the speed and structure of deep-seated convective flows. Those flows are in-turn thought to sustain both the Sun's turbulent EMF and the large-scale flows of differential rotation and meridional circulation suspected of influencing the dynamo's organization and timing. Continued progress in this area is complicated by (i) inconsistencies between helioseismic measurements of convective and meridional flow made with different techniques and instruments, and (ii) a lack of high-latitude data for convection, differential rotation, and meridional flow. We suggest that the path forward to resolving these difficulties is twofold. First, the acquisition of long-term helioseismic and emissivity measurements obtained from a polar vantage point is vital to complete our picture of the Sun's outer convection zone. Second, sustained and expanded investment in theory-oriented and combined theory/observational research initiatives will be crucial to fully exploit these new observations and to resolve inconsistencies between existing measurements.

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arXiv2023

Small-scale dynamos: From idealized models to solar and stellar applications

In this article we review small-scale dynamo processes that are responsible for magnetic field generation on scales comparable to and smaller than the energy carrying scales of turbulence. We provide a review of critical observation of quiet Sun magnetism, which have provided strong support for the operation of a small-scale dynamo in the solar photosphere and convection zone. After a review of basic concepts we focus on numerical studies of kinematic growth and non-linear saturation in idealized setups, with special emphasis on the role of the magnetic Prandtl number for dynamo onset and saturation. Moving towards astrophysical applications we review convective dynamo setups that focus on the deep convection zone and the photospheres of solar-like stars. We review the critical ingredients for stellar convection setups and discuss their application to the Sun and solar-like stars including comparison against available observations.

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arXiv2023

Limitations and biases in the retrieval of the polar magnetic field I: the role of the magnetic filling factor in Milne-Eddington inversions of simulated Hinode/SP data

We study the extent to which Milne-Eddington inversions are able to retrieve and characterize the magnetic landscape of the solar poles from observations by the spectropolarimeter onboard Hinode. In particular, we evaluate whether a variable magnetic filling factor is an adequate modeling technique for retrieving the intrinsic magnetic properties from every pixel in the polar field of view. We first generate synthetic spectra emerging from a numerical simulation of a "plage" region at an inclined line of sight of 65$^{\circ}$, and degrade the data to emulate real observations. Then, we invert the synthetic spectra with two Milne-Eddington inversion codes that feature different treatments of the magnetic filling factor, and relate the retrieved magnetic quantities back to their original values in the simulation cube. We find that while the apparent retrieved magnetic properties map well the spatially-degraded simulation, the intrinsic magnetic quantities bear little relation to the magnetic field at the native resolution of the simulation. We discuss the systematic biases caused by line-of-sight foreshortening, spatial degradation, photon noise and modeling assumptions embedded in the inversion algorithm.

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