Small-scale extreme-ultraviolet (EUV) brightenings are ubiquitous in the solar corona and may represent the low-energy counterparts of larger solar flares, with important implications for coronal heating. A key observational signature of solar and stellar flares is the presence of quasi-periodic pulsations (QPPs), which are thought to reflect fundamental processes of impulsive energy release. QPPs can therefore provide a key diagnostic for determining whether EUV brightenings share the same underlying mechanisms as larger-scale flares or instead represent a fundamentally distinct regime.
Using the high spatial and temporal resolution of the Solar Orbiter/Extreme Ultraviolet Imager, we present the first clear evidence that QPPs are present in EUV brightenings. We characterise their properties over a wide range of spatial and temporal scales and show that their periods extend from a few seconds to several minutes, comparable to those observed in larger flares.
We further demonstrate that the relationship between QPP damping time and period follows a common power-law scaling for both EUV brightenings and EUV solar flares. When combined with previously reported X-ray QPPs from solar and stellar flares, all events align with a single unified scaling trend spanning many orders of magnitude in scale. The universality of this scaling strongly suggests that QPPs in small-scale brightenings, solar flares, and stellar flares are governed by a broadly common underlying physical mechanism.
]]>The plasma composition in the solar corona is variable, with a strong dependency on the first ionisation potential (FIP) of elements. In flaring regions, plasma composition has been shown to have significant spatial and temporal variations, likely driven by dynamical processes triggered by energy release at the reconnection site. The origin of these variations and their impact on flare loop dynamics are not yet fully understood. In this work, we use high cadence Hinode EIS spectroscopic observations of the M-class flare peaking at 13:56 UT on 2 April 2022, alongside simulations from the 0D EBTEL hydrodynamic model, to investigate the role of plasma composition in modulating radiative losses in solar flare loops. We identify two regions along the flare loop arcade, with distinct FIP bias values as well as cooling rates, suggesting that spatial variations in plasma composition may play a key role in influencing flare loop cooling. In this framework, I will also discuss the potential of high resolution spectropolarimetric observations from the upcoming IBIS 2.0 instrument, currently under installation at the THEMIS telescope, particularly for advancing studies of the physical mechanisms driving plasma composition variations, flare dynamics and the coupling between the two.
]]>Magnetohydrodynamic waves are often regarded as efficient pathways for magnetic energy transfer from the solar interior. Consequently, they are key to not only understand the physical processes behind coronal heating and/or solar wind acceleration but also serve as useful diagnostic tools. While Alfvén wave modes are notoriously difficult to detect directly by remote sensing – due to their incompressive nature – magnetoacoustic wave modes can perturb the density and temperature as they propagate. More recently, observations from the Metis coronagraph on board the Solar Orbiter have shown the ubiquitous presence of propagating density fluctuations in a helmet streamer as well as in a pseudo-streamer with a 5-minute period. Using 2.5D MHD simulations, we find that such density fluctuations can be generated either from (non-linear) Alfvén waves or directly from magnetoacoustic waves. Furthermore, density fluctuations generated from Alfvén waves have a doubled frequency with respect to the (driven) Alfvén wave frequency because of non-linear ponderomotive forces. This feature might be a useful diagnostic for the (in-situ) distinction between density fluctuations generated from these different mechanisms.
Flare ribbons are a quintessential part of a flare. They are extensively used to understand the overlying reconnection mechanism and overall flaring process. Further, the reconnection rate is a key parameter in the magnetic reconnection process. But it is difficult to estimate the rate from direct observations at higher heights in the solar atmosphere. However, flare ribbons are believed to be one of the major energy deposition sites and the imprints of reconnection occurring at higher altitudes. Utilizing this advantage to map the reconnection rate at the corona, Qiu et al. (2002, 2006) had provided an approach to estimate the flux and flux rate in a flare.
In the talk, I will discuss about the application of this method to multiple wavelengths in the solar atmosphere using high resolution data from ground-based Multi Application Solar Telescope (MAST)/Udaipur Solar Observatory in Ca II 8542 line, and data in UV and EUV channels from the Atmospheric Imaging Assembly (AIA) and Helioseismic Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO). I will highlight the interesting profiles of reconnection flux and associated rates for all the channels in ribbon (sub)structures, along with the probable nature of reconnection occurring there. The work also explains the triggering mechanism behind the reconnection in 3D using the non-force-free-field (NFFF) extrapolation model.
Recent advances in solar physics increasingly rely on automated identification of coronal structures using machine learning. Yet most studies emphasise scientific performance without evaluating feasibility for onboard deployment to prioritise downlink observations. We investigate the automated identification of active regions and coronal holes by applying segmentation and detection techniques to Solar Dynamics Observatory (SDO) data. We compare three approaches: SCSS-Net, a deep learning model for semantic segmentation; YOLOv8n, a lightweight object detector; and a traditional pipeline based on basic computer vision operations (BCVO). Each method is assessed for its scientific accuracy and its suitability for deployment in future resource-limited missions. While no direct hardware benchmarking has been performed yet, we assess the feasibility of an onboard implementation based on the number of trainable parameters, the architecture, and the associated hardware requirements. Training and evaluation are first conducted on well-calibrated SDO images. We then extend the evaluation to raw and uncalibrated SDO images affected by instrumental artefacts. Performance is mainly measured using the Intersection over Union (IoU) and Dice score. Results show that while SCSS-Net achieves the highest segmentation quality, YOLOv8n offers a strong balance between accuracy and efficiency. The BCVO pipeline remains viable under strict hardware limitations. Interestingly, our models retain compatibility on Level-0 observations. This is the first study comparing these widely used methods from the perspective of onboard deployment. Our findings provide a foundation for designing frameworks tailored to onboard hardware configurations.
This work takes advantage of new observational data collected by the High-resolution Coronal Imager (Hi-C) at the highest spatial and temporal resolutions available. This most recent Hi-C dataset is the first to make use of the hot 129 Å channel and the first to consist of targeted observations of a solar flare, rather than the quiescent corona. Images from Hi-C are analysed and compared with complementary EUV observations from SDO/AIA. The widths of the loop strands are measured, and the resulting populations analysed. Preliminary results suggest the majority of loop strands have a width in the range 500-2,000 km, but there is some variation in the loop strand widths observed in plasma at different temperatures. There is some evidence that there are smaller structures present which are partially resolved by Hi-C, with the very smallest smallest loop strands of a similar order of magnitude to the spatial resolution of the Hi-C images. Further results will be presented, as well as a discussion of future work, investigating individual events within the Hi-C observations, making use of the high cadence available to track the dynamic behaviour of the corona.
]]>Understanding how magnetic properties of solar active regions influence coronal mass ejection (CME) dynamics is essential for constraining eruption models and improving space-weather prediction. In this work, we investigate the relationship between magnetic field diagnostics derived from potential-field extrapolations and the 3D speeds of CMEs.
We focus on physically motivated parameters associated with eruption onset, including the critical height of torus instability (hcrit), the strength of the overlying magnetic field strength (Bt), and the flare ribbon flux (Rf). While hcrit and Bt are traditionally evaluated directly above polarity inversion lines (PILs), ; however, identifying PILs can involve threshold-dependent and partially manual selection procedures. To reduce this dependency, we test whether these diagnostics retain predictive power when computed over broader regions of interest (ROIs) within the active region, without relying on explicit PIL selection.
Using decay index profiles derived from photospheric magnetograms, we find a strong correlation between hcrit and CME speed (r ≈ 0.71). When evaluated over progressively larger ROIs centered on the PIL, weighted hcrit from the largest region considered provides the strongest correlation (r ≈ 0.73), indicating that the broader active-region field structure is as informative as measurements strictly above the PIL. In contrast, Bt shows weaker (r = 0.33) predictive capability, and combining it with hcrit offers only marginal improvement. Ribbon flux exhibits moderate correlation (r = 0.44) with CME speed, but the highest predictive power is consistently obtained when hcrit is included.
These results suggest that, within potential-field models, the critical height of torus instability is the dominant magnetic diagnostic of CME speed, and that the large-scale magnetic environment of active regions plays a key role in regulating eruption dynamics.
Huw Morgan
Solar flares are the most energetic manifestations of solar activity and can significantly affect Earth’s magnetosphere, ionosphere, and technological systems. Therefore, anticipating these events remains a fundamental challenge in heliophysics. Soft X-ray observations from the GOES satellites have long been used to monitor and characterize solar flares. Among the various forecasting approaches, the Flare Anticipation Index (FAI), originally proposed by Hudson (2025), has established itself as a promising diagnostic tool for thermal activity preceding flares. The FAI is based on the detection of a Hot Onset Precursor Event (HOPE), characterized by a gradual increase in plasma temperature, and the emission measure before the impulsive phase of a flare. In this work, we performed a statistical validation of the FAI using a representative dataset of approximately 8,000 days between 1980 and 2025. Plasma temperatures and emission measurements were derived from GOES/XRS observations, and FAI-based alerts were generated using predefined thresholds correlated with GOES solar flares within a 30-minute time interval from flare start to peak. A total of 48,344 flares of different classes were analyzed, yielding varying detection rates depending on the flare class. The parameter sets were chosen to minimize the number of false positives and increase the detection rate of large flares (M and X). The results suggest that the FAI is particularly sensitive to medium and large solar flares and has potential for near real-time prediction, while also highlighting the need to optimize the thresholds to improve its predictive performance for each class.
We discuss how to optimise the science output of the European Solar Telescope (EST), when used without the wide-field compensation for high-altitude seeing that the EST multi conjugate adaptive optics (MCAO) will offer. This will likely be the mode of operating EST during its first year, following first light. In this mode, the spatial resolution of a much smaller telescope could surpass that of EST. We propose to operate EST in multi-aperture mode, which will, together with the use of short exposure times and image reconstruction techniques, dramatically improve image quality. In particular, the multi-aperture mode will provide the sustained stable high image quality needed for obtaining time sequences of spectropolarimetric data. The multi-aperture mode is implemented by optically segmenting the 4.2 m aperture into six 1.4 m subapertures by a low-cost modification of the camera lenses of the three Fabry-Perot systems that are expected to be operational soon after first light.
Coronal bright points are ubiquitous, highly energetic events that are often seen accompanying other dynamic and eruptive phenomena in the solar atmosphere. Their large energy output, their similarity to active regions and their connections to other events make them especially interesting to understand the solar corona. This talk will describe the findings of a recent project focusing on the hottest loop constituents of coronal bright points. We extract and analyse the hot loops of three different state-of-the-art radiative-MHD Bifrost simulations, studying their basic thermodynamic, magnetic and geometrical properties. The simulated loop properties are compared to a recent observational dataset, the first detailed study of this kind found in the literature, finding great compatibility between simulations and observations. Additionally, the loop geometry is assessed by focusing on the deviations from the commonly-assumed semi-circularity, another aspect that has been overlooked so far. We study the heating and cooling mechanisms acting on the loops, a fundamental aspect to accurately model the energy balance of these structures and their contribution to the coronal heating. The results show that only the 3D simulations show strong Joule and viscous heating in the footpoints. This reveals a localized source of entropy possibly stemming from 3D magnetic reconnection at the footpoints, which is consistent with other findings in this work.