Coronagraph observations provide key information about the orientation of the Sun’s magnetic field. Previous studies used various algorithms to segment quasi-radial features in coronagraph images and approximate their local plane-of-sky (POS) geometry and orientation, which can be used as input for optimizing and constraining coronal magnetic field models. We present a new framework that allows for further quantitative evaluations of image-based coronal segmentation methods against magnetic field models, and vice versa. We compare quasi-radial features identified from QRaFT, a global coronal feature tracing algorithm, in white-light coronagraph images to outputs of the Magnetohydrodynamic Algorithm outside a Sphere (MAS) model, an advanced MHD model. We use the FORWARD toolset to produce synthetic polarized brightness images coaligned to real coronagraph observations, segment features in these images, and quantify the difference between the inferred and model magnetic field. This approach allows us to geometrically compare features segmented in artificial images to those segmented in white-light coronagraph observations against the POS projected MAS coronal magnetic field. We quantify QRaFT’s performance in the artificial images and observational data, and perform statistical analyses that measure the accuracy and uncertainty of the model output to the observational data. The results demonstrate that a coronal segmentation method identifies the global large-scale orientation of the coronal magnetic field within ∼±10 ^∘ of the POS projected MAS magnetic field.

The morphology and heliospheric impact of coronal mass ejections (CMEs) are strongly shaped by their pre-eruptive magnetic configuration and surrounding coronal environment, yet these influences remain difficult to constrain observationally. We analyze a complex CME that erupted on 2024 October 26 using multiviewpoint remote-sensing observations and in situ measurements. Using the physics-based CORHEL-CME magnetohydrodynamic model, we test multiple physically plausible realizations of the pre-eruptive magnetic flux rope (MFR) and background magnetic field, using agreement with the observed evolution as a constraint on the CME's initial state. We find that modest changes in MFR footpoint location and force balance lead to substantially different coronal trajectories, enabling rapid discrimination among candidate initial states. While several configurations reproduce the CME's large-scale propagation, realistic small-scale morphology is achieved only when a near-dated background magnetic field is employed. The resulting simulation reproduces key morphologies observed from three viewpoints without fine-tuning, indicating that the inferred pre-eruptive configuration represents a robust, global solution and provides a physically consistent interpretation of their magnetic origin. Comparison with in situ shock detections highlights the role of CME-solar wind interactions in shaping heliospheric signatures, though shock arrival times remain uncertain at the 11 hr level. These results demonstrate that data-informed, physics-based modeling can meaningfully constrain CME pre-eruptive conditions and bridge remote and in situ observations, while emphasizing the need for timely magnetic field measurements to improve predictive capability.

Magnetic flux fills the heliosphere, expands outward from the solar corona, and is fundamentally related to the structure and dynamics of the solar corona and solar wind. Open magnetic flux and the fast wind are thought to originate from open magnetic field lines in coronal holes. Less understood processes in the streamer belt and the boundaries of coronal holes, associated with the more variable slow wind, may be formed by interchange reconnection between open and closed magnetic flux. Interchange reconnection is thought to give rise to field lines that are “folded,” i.e., that turn back on themselves. The properties of strahl electrons measured in the solar wind give clues to the heliospheric magnetic connectivity. Unidirectionally outward strahl indicates open field lines, while bidirectional strahl is associated with closed magnetic flux and coronal mass ejections (CMEs). Inward-directed, unidirectional strahl is believed to indicate folded flux. We use two time-dependent, flux-evolutionary magnetohydrodynamic (MHD) models of the combined corona and heliosphere, one for a solar-minimum configuration and one for the 2024 total solar eclipse, to investigate the magnetic connectivity of the corona/heliosphere system. We examine how magnetic connectivity varies with distance from the Sun in the two configurations. We evaluate the evolutionary effects by contrasting time-dependent results with the corresponding steady-state calculations and compare the model connectivities with statistical studies of strahl. The connectivities in the time-evolving simulations are roughly consistent with observed strahl occurrence rates, while those from the steady-state models are not. Our results suggest that complex magnetic connectivities are ubiquitous in the heliosphere.

The Sun's magnetic field is a key driver in coronal heating and consequently solar wind acceleration. Remote measurement of the photosphere provides the magnetic surface boundary condition necessary for data-constrained 3D global coronal models. With one such model, we explore how the spatial resolution of the surface boundary condition influences the global properties of the magnetic field and coronal heating. Using spherical harmonic decomposition, we quantify how three different resolution simulations vary in the low and middle corona. Through examination of the magnetic field, the squashing factor, and the heating rate, we demonstrate that small-scale photospheric magnetic flux enhances heating across spatial regimes. We calculate 40% more heating in our best-resolution simulation compared to our base resolution. We describe a strong correlation between the structure of the magnetic field and the structure of the heating rate in the low corona across resolutions. These results provide key information as to what more efficient, low-resolution models might inherently miss. This can provide context to incorporate the effects of unresolvable features in future modeling efforts.

How the solar wind is heated to over a million degrees and accelerated to supersonic speeds remains an unresolved problem. One promising mechanism invokes numerous nanoflare-like energy release events driven by interchange reconnection between open and closed magnetic field lines in the solar corona, yet direct evidence for their ubiquity and particle-acceleration nature has been elusive. Using ultra-sensitive radio imaging spectroscopy, we detect extremely frequent and faint type III radio bursts originating from regions near open–closed magnetic boundaries in the low solar corona. These bursts trace energetic electrons produced by prevalent interchange reconnection events, injecting energy, momentum, and particles into the solar wind. Direct in situ measurements from the Parker Solar Probe reveal suprathermal electrons and ions in the near-Sun solar wind consistent with particle injections from these regions. Together, these observations uncover a previously inaccessible spectrum of particle-accelerating, small-scale interchange reconnection events and provide new insight into the long-standing problem of coronal heating and solar wind acceleration.

We apply the slip-back mapping method of V. S. Titov et al. and R. Lionello et al. to a thermodynamic MHD simulation to track topological changes in the magnetic field at a range of temporal cadences. The method constitutes the logical successor to a simple open-field map for a steady-state model, as it tracks changes in the open and closed fields for a time-dependent model by tracking individual magnetic elements as they advect across the map, rather than simply tracing field line connectivity from each cell. Through careful categorization of the slip-back mapping values and analysis of the flux changes, we not only effectively track the open flux but can recover the flux processed through interchange reconnection as well. The field lines involved in these processes are shown to follow lines of high squashing factor, as proposed by interchange-reconnection-driven slow solar wind theory. The time-dependent model, which is scaled to solar-minimum-like activity, projects that a median value of 3.5% of the total open flux in any given 24 hr interval has been processed through interchange reconnection. This corresponds to a relatively high proportion of the total open flux changes over time in the heliosphere. Our results show that not only is this method a useful tool for accurately tracking topological changes in time-dependent simulations, but that its inherent complexity can be visually reduced into an intuitive 2D plot that simply and effectively communicates temporal changes.

Incoherent radio emission at meter--decimeter wavelengths provides a key diagnostic of the coronal thermal plasma, but at frequencies below $\sim$\,1\,GHz coronal refraction can substantially bend ray paths and modify the apparent source size and brightness distribution. We develop a forward-modeling framework that combines refractive ray tracing through a global 3D coronal model with radiative transfer along each ray. The method tracks the ray-tube cross-sectional area $S(s)$ using a step-wise perturbation retracing approach and incorporates a geometric magnification term proportional to $d\ln S/ds$ to enforce flux conservation under focusing/defocusing. Thermal free--free emission and absorption are then computed with the \texttt{GRFF} radiative transfer code to produce synthetic radio maps over 40--800\,MHz. Applying the framework to Carrington rotation 2298, we find that including propagation effects allows the quiet-Sun background spectrum to be well reproduced. However, active region brightness is less accurately modeled, suggesting that additional physical factors should be considered in future work. These results establish a physics-based method for generating low-frequency quiet-Sun synthetic images suitable for quantitative comparison with interferometric observations and for assessing how propagation effects shape the observed morphology.

The morphology and heliospheric impact of coronal mass ejections (CMEs) are strongly shaped by their preeruptive magnetic configuration and surrounding coronal environment, yet these influences remain difficult to constrain observationally. We analyze a complex CME that erupted on 2024 October 26 using multiviewpoint remote sensing observations and in situ measurements. Using the physics based CORHELCME magnetohydrodynamic model, we test multiple physically plausible realizations of the preeruptive magnetic flux rope (MFR) and background magnetic field, using agreement with the observed evolution as a constraint on the CMEs initial state. We find that modest changes in MFR footpoint location and force balance lead to substantially different coronal trajectories, enabling rapid discrimination among candidate initial states. While several configurations reproduce the CMEs large scale propagation, realistic small scale morphology is achieved only when a near dated background magnetic field is employed. The resulting simulation reproduces key morphologies observed from three viewpoints without fine tuning, indicating that the inferred preeruptive configuration represents a robust, global solution and provides a physically consistent interpretation of their magnetic origin. Comparison with in situ shock detections highlights the role of CME solar wind interactions in shaping heliospheric signatures, though shock arrival times remain uncertain at the 11 hr level. These results demonstrate that data informed, physics based modeling can meaningfully constrain CME preeruptive conditions and bridge remote and in situ observations, while emphasizing the need for timely magnetic field measurements to improve predictive capability.

Global solar photospheric magnetic maps play a critical role in solar and heliospheric physics research. Routine magnetograph measurements of the field occur only along the Sun–Earth line, leaving the far side of the Sun unobserved. Surface flux transport (SFT) models attempt to mitigate this by modeling the surface evolution of the field. While such models have long been established in the community (with several releasing public full-Sun maps), none are open source. The Open-source Flux Transport (OFT) model seeks to fill this gap by providing an open and user-extensible SFT model that also builds on the knowledge of previous models with updated numerical and data acquisition/assimilation methods along with additional user-defined features. In this first of a series of papers on OFT, we introduce its computational core: the High-performance Flux Transport (HipFT) code ( https://github.com/predsci/hipft ). HipFT implements advection, diffusion, and data assimilation in a modular design that supports a variety of flow models and options. It can compute multiple realizations in a single run across model parameters to create ensembles of maps for uncertainty quantification and is high-performance through the use of multi-CPU and multi-GPU parallelism. HipFT is designed to enable users to write extensions easily, enhancing its flexibility and adaptability. We describe HipFT’s model features, validations of its numerical methods, performance of its parallel and GPU-accelerated code implementation, analysis/postprocessing options, and example use cases.

Shocks in the low corona are best observed in the extreme ultraviolet (EUV); however, time-dependent ionization in the postshock region is generally incompatible with the otherwise straightforward plasma diagnostics typically applied to EUV imaging data. As a result, these rich data are largely underutilized. In this work, we present our approach to modeling the evolving EUV emission from coronal shocks, including nonequilibrium ionization (NEI) effects in the shocked plasma. Our framework combines (1) a 3D reconstruction of the shock geometry and kinematics derived from Solar Dynamics Observatory Atmospheric Imaging Assembly and STEREO-A/EUVI imaging, with (2) a simulated MHD snapshot of the pre-eruption corona built from magnetogram data, to solve Rankine–Hugoniot jump conditions. We then (3) track the density, temperature, and ionization history of the expanding 3D downstream region from which we generate synthetic postshock EUV light curves. We model the 2010 June 13 coronal mass ejection and shock wave using this framework, where we find that NEI is necessary to replicate the observed time-dependent EUV signal. This is especially true for the observed AIA 193 Å and 211 Å shock emission given that the predicted postshock temperatures would result in little Fe XII and Fe XIV . Moreover, the EUV model is highly sensitive to the postshock electron-to-ion temperature ratio ( T _e / T _p ). We find that the data are well described by the model and broadly prefer lower T _e / T _p < 1, suggesting inefficient electron heating throughout most of the shock structure.

We present observations of an eruptive solar flare on 2016 January 6 that occurred behind the solar limb from the perspective of the Earth, but was well observed by the Solar-Terrestrial Relations Observatory (or STEREO) and the Solar Extreme Ultraviolet Monitor on NASA's Mars Atmosphere and Volatile EvolutioN (MAVEN) mission. Light curves showing the evolution of the flare’s irradiance as a function of time taken by MAVEN are well correlated with the brightness evolution of fan structures observed in the Project for On-Board Autonomy 2's Sun Watcher with Active Pixels and Image Processing (SWAP) 174 Å passband, suggesting that the radiance of structures near the flare site was influenced by emission from the flare. Because SWAP did not directly observe the flare itself, this event represents a rare opportunity to study the evolution of emission near a flare without the risk of instrumental scattered light contaminating the observations. We analyze this evolution and implement a simple model to explore the possibility that resonant excitation (RE, also known as resonant scattering) plays an important role in driving coronal extreme-ultraviolet (EUV) emission during flaring events. Our modeling shows that for a large flare, RE could increase emission from nearby structures by about 45%, consistent with our findings that the involved structures observed by SWAP increased in brightness by about 60% during the flare. We conclude that RE may play an important role in driving coronal EUV emission under certain circumstances and should be accounted for in models and emission-based analysis tools.

The solar magnetic field expands outward from the Sun with the solar wind and fills the heliosphere. Understanding the structure, dynamics, and connectivity of this field underlies many unanswered questions in solar and heliospheric physics. In the presence of ideal flows and in the reference frame co-rotating with the Sun, the solar wind plasma flow is aligned with the magnetic field. In this approximation, tracing the magnetic connectivity of plasma parcels encountered in the heliosphere back to the Sun reveals their solar origin. The magnetic field is also important for the propagation of solar energetic particles (SEPs), guiding them along magnetic field lines from their generation near the Sun to locations in the heliosphere. Models with varying degrees of complexity are used to estimate the magnetic field connectivity and interpret observations. A standard approach is to use potential field models to describe the corona, and to ballistically map points in the heliosphere back to the corona with the in situ measured solar wind speed. More advanced models couple the potential field corona with a heliospheric MHD model. We test the strengths and limitations of these approaches by utilizing a data-driven time-evolving model of the corona and heliosphere, computed for a month of evolution surrounding the 2024 total solar eclipse. The time-evolving model is highly dynamic, with many small-scale eruptions. We treat the time-dependent model as the ``ground truth'' and investigate how well the standard approaches capture the time-varying magnetic connectivity.Research Supported by NASA and NSF. Computational resources provided by the NSF ACCESS program and the NASA Advanced Supercomputing division at Ames.

NASA's Community Coordinated Modeling Center (CCMC) presents CORHEL-CME, our newest addition to the Runs-On-Request system in the solar and heliospheric modeling domain. CORHEL-CME, developed by Predictive Science Inc., is a highly automated and interactive MHD modeling framework designed to simulate multiple coronal mass ejections within a realistic coronal and heliospheric environment. It combines three key innovations: 1. Interactive design of CMEs using a GUI-based web interface CORHEL-CME's user interface is designed for non-experts. It offers real-time diagnostics to assist with model settings, guides users through creating full physics-based CME simulations, and provides web-based visualization reports. 2. Modeling CMEs originating from complex active regions CORHEL-CME includes a flux rope model called RBSL (Titov et al., 2018), allowing users to create pre-eruptive flux rope configurations above elongated and curved polarity inversion lines. This feature enables users to realistically simulate CMEs originating from complex active regions. 3. Efficient, full physics-based simulations of CMEs Using the web interface, the users set up simulation runs, including a simplified (zero-beta) MHD model of multiple flux ropes, a quasi-steady-state coronal MHD background model, and a high-fidelity time-dependent CME simulation. All simulation runs are performed on AWS high-performance GPU servers maintained by the CCMC. In this presentation, we will showcase the usage of CORHEL-CME via CCMC's Runs-On-Request system and show an example run based on an event from March 7th, 2012. The new framework is publicly accessible through the CCMC website.

Optical observations of the solar corona provide key information on its magnetic geometry. The large-scale open field of the corona plays an important role in shaping the ambient solar wind and constraining the propagation dynamics of the embedded structures, such as interplanetary coronal mass ejections. Rigorous analysis of the open-flux coronal regions based on coronagraph images can be quite challenging because of the depleted plasma density, resulting in low signal-to-noise ratios. In this paper, we present an in-depth description of a new image segmentation methodology, the Quasi-Radial Field-line Tracing (QRaFT), enabling the detection of optical coronal features indicating the orientation of the steady-state open magnetic field. The methodology is tested using synthetic coronagraph images generated by a three-dimensional magnetohydrodynamic model. The results of the numerical tests indicate that the extracted optical features are aligned within ∼4°–7° with the local magnetic field in the underlying numerical solution. We also demonstrate the performance of the method on real-life coronal images obtained from a space-borne coronagraph and a ground-based camera. We argue that QRaFT outputs contain valuable empirical information about the global steady-state morphology of the corona, which could help improve the accuracy of coronal and solar wind models and space weather forecasts.

The Sun's corona is its tenuous outer atmosphere of hot plasma, which is difficult to observe. Most models of the corona extrapolate its magnetic field from that measured on the photosphere (the Sun's optical surface) over a full 27-day solar rotational period, providing a time-stationary approximation. We present a model of the corona that evolves continuously in time, by assimilating photospheric magnetic field observations as they become available. This approach reproduces dynamical features that do not appear in time-stationary models. We used the model to predict coronal structure during the total solar eclipse of 8 April 2024 near the maximum of the solar activity cycle. There is better agreement between the model predictions and eclipse observations in coronal regions located above recently assimilated photospheric data.

Total solar eclipses offer an unparalleled opportunity to observe the low and middle corona. As is our tradition, the solar physics team at Predictive Science is predicting the structure of the solar corona for the April 8, 2024 total solar eclipse, using a magnetohydrodynamic (MHD) model of the corona. The model incorporates thermodynamic transport terms and employs a wave-turbulence-driven (WTD) description of coronal heating and solar wind acceleration. Our previous coronal predictions employed relaxed MHD solutions corresponding to a boundary condition based on a single photospheric magnetic map, incorporating data that at best was measured 10 to 14 days prior to the eclipse.This year, we introduce a new paradigm: A continuously updated prediction based on a time-evolving model. To accomplish this near-real time description, we have incorporated 3 new elements: (1) a time-evolving MHD model driven by evolution of the photospheric magnetic field, (2) an automated method for energizing the non-potential corona near polarity inversion lines that evolve in time, and (3) The Open-source Flux Transport (OFT) model, that assimilates near-real time surface magnetic flux observations from SDO HMI as well as low-latency observations from the Solar Orbiter PHI instrument made away from the Sun–-Earth line.This presentation will give an overview of the entire prediction effort and describe the time-dependent coronal dynamical features that appear in the solutions.Research Supported by NASA and NSF. Computational resources provided by the NSF ACCESS program and the NASA Advanced Supercomputing division at Ames.

Astrophysical simulations require trade-offs between compute time and physical accuracy. This frequently includes targeting certain physical scales at the expense of others. Simulations investigating solar coronal heating and solar wind acceleration usually select either high resolution for a small domain or low resolution for a global domain. Bridging this gap requires linking structures present on the solar surface to both the middle corona (approximately 1.5 - 6 solar radii) and the solar wind. In this work we analyze three simulations of the global solar corona that vary the resolution of the surface boundary condition while keeping the same parameterization of a thermodynamic, wave-turbulence-driven magnetohydrodynamic model. We quantify structural differences endemic to each simulation using spherical harmonic decomposition and associated statistics. We use this information to examine how surface resolution influences heating and magnetic complexity in the corona and solar wind and the subsequent impacts on density, temperature, and flow structure. In principle, this can enable more efficient subgrid modeling in future low resolution simulations.

We generalize a magnetogram-matching Biot–Savart law (BS l ) from planar to spherical geometry. For a given coronal current density J , this law determines the magnetic field B ˜ whose radial component vanishes at the surface. The superposition of B ˜ with a potential field defined by a given surface radial field, B r , provides the entire configuration where B r remains unchanged by the currents. Using this approach, we (1) upgrade our regularized BS l s for constructing coronal magnetic flux ropes (MFRs) and (2) propose a new method for decomposing a measured photospheric magnetic field as B = B pot + B T + B S ˜ , where the potential, B pot , toroidal, B T , and poloidal, B S ˜ , fields are determined by B r , J r , and the surface divergence of B – B pot , respectively, all derived from magnetic data. Our B T is identical to the one in the alternative Gaussian decomposition by P. W. Schuck et al., while B pot and B S ˜ are different from their poloidal fields B P < and B P > , which are potential in the infinitesimal proximity to the upper and lower side of the surface, respectively. In contrast, our B S ˜ has no such constraints and, as B pot and B T , refers to the same upper side of the surface. In spite of these differences, for a continuous J distribution across the surface, B pot and B S ˜ are linear combinations of B P < and B P > . We demonstrate that, similar to the Gaussian method, our decomposition allows one to identify the footprints and projected surface-location of MFRs in the solar corona, as well as the direction and connectivity of their currents.

Coronal dimmings associated with coronal mass ejections (CMEs) from the Sun have gained much attention since the late 1990s when they were first observed in high-cadence imagery of the SOHO/EIT and Yohkoh/SXT instruments. They appear as localized sudden decreases of the coronal emission at extreme ultraviolet (EUV) and soft X-ray (SXR) wavelengths, that evolve impulsively during the lift-off and early expansion phase of a CME. Coronal dimmings have been interpreted as “footprints” of the erupting flux rope and also as indicators of the coronal mass loss by CMEs. However, these are only some aspects of coronal dimmings and how they relate to the overall CME/flare process. The goal of this review is to summarize our current understanding and observational findings on coronal dimmings, how they relate to CME simulations, and to discuss how they can be used to provide us with a deeper insight and diagnostics of the triggering of CMEs, the magnetic connectivities and coronal reconfigurations due to the CME as well as the replenishment of the corona after an eruption. In addition, we go beyond a pure review by introducing a new, physics-driven categorization of coronal dimmings based on the magnetic flux systems involved in the eruption process. Finally, we discuss the recent progress in studying coronal dimmings on solar-like and late-type stars, and how to use them as a diagnostics for stellar coronal mass ejections and their properties.

To understand its evolution and the effects of its eruptive events, the Sun is permanently monitored by multiple satellite missions. The optically thin emission of the solar plasma and the limited number of viewpoints make it challenging to reconstruct the geometry and structure of the solar atmosphere; however, this information is the missing link to understand the Sun as it is: a 3D evolving star. We present a method that enables a complete 3D representation of the uppermost solar layer (corona) observed in extreme ultraviolet (EUV) light. We use a deep-learning approach for 3D scene representation that accounts for radiative transfer to map the entire solar atmosphere from three simultaneous observations. We demonstrate that our approach provides unprecedented reconstructions of the solar poles and directly enables height estimates of coronal structures, solar filaments, coronal hole profiles, and coronal mass ejections. We validate the approach using model-generated synthetic EUV images, finding that our method accurately captures the 3D geometry of the Sun even from a limited number of 32 ecliptic viewpoints ( divide latitude divide <= 7 degrees). We quantify the uncertainties of our model using an ensemble approach that allows us to estimate the model performance in the absence of a ground truth. Our method enables a novel view of our closest star and is a breakthrough technology for the efficient use of multi-instrument data sets, which paves the way for future cluster missions.