Eruptive and non-eruptive solar flares were investigated based on an analysis of electric current neutralization and torus instability. Combined analysis of these factors offers a more reliable prediction of eruptive events than relying on either one alone.
The analysis of magnetic fields and electrical currents indicates that a specific configuration – currents in opposite magnetic regions flowing in the same direction and peaking concurrently – might create favorable conditions for the magnetic reconnection process that powers solar flares.
Moreton waves were studied using a systematic survey of Moreton-wave events observed during the SDO era. The results showed that inclined magnetic configurations act as a wall, forcing eruptions and Moreton waves to propagate toward weaker magnetic fields.
A few major geoeffective flares and CMEs occurred in May 2024. HMI magnetic field data were used to examine how the flares occurred and why they became geoeffective.
The coronal magnetic field evolution of the AR 11429 was simulated using time-dependent magneto-friction model. The model reproduced the magnetic structure that has remarkable correspondence with the spatial characteristics in coronal extreme ultraviolet images.
A new method was developed to identify white-light flares (WLFs) observed in SDO/HMI continuum intensity. The new method is able to identify around 30% of C-class flares (and more percentage in stronger flares) having white light brightening associated with them, greatly expanding the total number of WLFs observed by HMI. The increased number of detections would help a statistical study of the properties of WLFs.
A spectro-polarimetric analysis of the sunquake sources observed during an X1.5 flare revealed transient emission in the FeI 6173Å line core, indicating intense, impulsive heating in the lower photosphere at the beginning of the flare impulsive phase.
A survey of how many off-limb white-light events were observed by the SDO/HMI was conducted, and a catalogue is published online with real-time updates.
An analysis of two active regions shows that differently evolving ARs may produce major eruptive flares even when, in addition to the accumulation of significant free magnetic energy budgets, they accumulate large amounts of both left- and right-handed helicity without a strong dominance of one handedness over the other.
Some magnetic features in active regions, related to strong solar flares, are considered as “anomaly” features in a machine learning algorithm. An unsupervised auto-encoder network has been trained to identify such anomalies and is used to predict occurrence of strong flares.