Biswajit Mondal

Solar plasma composition differs between the photosphere and corona over a range of timescales, with preferential enhancement of elements with low first ionization potential (FIP). However, the physical origin of the FIP fractionation remains incompletely understood. Furthermore, during flares, the FIP bias also exhibits rapid changes, associated with fast transport of material with different FIP biases. We present novel observations from the Solar Orbiter SPICE and Extreme Ultraviolet Imager (EUI), Hinode Extreme Ultraviolet Imaging Spectrometer (EIS), and Chandrayaan-2 Solar X-ray Monitor (XSM) instruments, finding rapid abundance changes in the emitting plasma, on timescales of minutes, during the eruptive M7.6-class solar flare observed on 2024 September 30. These instruments have wide temperature coverage and find contrasting abundance evolution patterns between the hotter and cooler plasma components. 3D reconstruction of the active region and additional observations from the Solar Orbiter STIX X-ray telescope show how the hot and cool plasma components, emitting in different spectral regions and observed with the various instruments, sample the plasma composition evolution in distinct locations within the observed flaring plasma. The bright postflare looptops observed by SPICE show coronal FIP bias, while the hot plasma observed with XSM exhibits FIP bias decreasing from coronal to photospheric during the impulsive phase. We interpret these observations as evidence of the X-ray diagnostics seeing hot coronal reconnection outflows mixing with chromospheric plasma as flare loops sequentially energize and relax, explaining why the FIP bias decreases from coronal to a hybrid; and the cool looptops seen with SPICE show coronal abundances due to coronal material deposited near the looptops.

Continuum emission from a solar flare observed with the Extreme ultraviolet Imaging Spectrometer (EIS) on board the Hinode satellite is used to obtain the radiometric calibration of the instrument. The flare had a GOES class of M8, and peaked at 23:59 UT on 2024 September 30. The continuum is modeled by computing a differential emission measure curve using EIS emission lines and atomic data from the CHIANTI database. The ratio of the observed continuum to model continuum yields effective area curves for the instrument. The new curves confirm earlier findings that the EIS long-wavelength channel has degraded by a factor of 2 compared to the short-wavelength channel. However, no evidence is found for the fine-scale structure in the effective area curves that has been presented by previous authors. In order to reproduce both the emission-line intensities and the continuum, it is found that the plasma must be depleted in elements with low first ionization potentials (FIPs), i.e., the so-called inverse-FIP effect. In particular, the Fe/H relative abundance is found to be a factor of 0.57 below the photospheric value at a temperature of 10 MK. This is confirmed by an analysis of soft X-ray spectra from the Solar X-ray Monitor on Chandrayaan-2, which yields an Fe/H FIP bias of 0.55 averaged over the entire flare.

Since the advent of X-ray and EUV spectroscopy, the discovery of the First Ionization Potential (FIP) effect--where coronal elemental compositions diverge from their photospheric values based on the element's FIP--has remained a key puzzle in solar and stellar astrophysics. These deviations exhibit significant fluctuations during flares, yet their connection to plasma dynamics has remained unclear. Here, we report a clear correlation between temperature-sensitive flaring plasma emission and element-specific abundance changes for a solar flare. These findings indicate that energy deposition in the chromosphere drives plasma evaporation from different chromospheric heights, modulating elemental abundances. Hydrodynamic simulations support these observations, showing that varying energy deposition magnitudes generate plasma upflows from different chromospheric heights, leading to element-specific FIP fractionation. These results provide new insights into the dynamic coupling of flare energy, plasma flows, and abundance variability, with implications for understanding coupling between different atmospheric layers.

Elemental abundance diagnostics in the solar corona are crucial for understanding energy transport, plasma heating, and magnetic activity. Most earlier imaging-spectroscopic studies have relied on slit-based spectrometers, which offer high spectral resolution but are limited in spatiotemporal coverage and temperature diagnostics. In contrast, slitless spectrographs like the Marshall Grazing Incidence X-ray Spectrometer (MaGIXS) produce overlapping spatial-spectral data (overlappograms) to enable wide-field imaging spectroscopy with broader temperature coverage. However, extracting elemental abundances from overlappogram data remains inherently challenging due to spatial and spectral confusion. In this work, we present a proof-of-concept technique for elemental abundance diagnostics from overlappograms, demonstrating its feasibility with simulated MaGIXS-2 observations.

Elemental abundance diagnostics in the solar corona are crucial for understanding energy transport, plasma heating, and magnetic activity. Most earlier imaging-spectroscopic studies have relied on slit-based spectrometers, which offer high spectral resolution but are limited in spatiotemporal coverage and temperature diagnostics. In contrast, slitless spectrographs like the Marshall Grazing Incidence X-ray Spectrometer (MaGIXS) produce overlapping spatial-spectral data (overlappograms) to enable wide-field imaging spectroscopy with broader temperature coverage. However, extracting elemental abundances from overlappogram data remains inherently challenging due to spatial and spectral confusion. In this work, we present a proof-of-concept technique for elemental abundance diagnostics from overlappograms, demonstrating its feasibility with simulated MaGIXS-2 observations.

Nanoflares are believed to be key contributors to heating solar nonflaring active regions, though their individual detection remains challenging. This study uses a data-driven field-aligned hydrodynamic model to examine nanoflare properties throughout the lifecycle of active region (AR) 12758. We simulate coronal loop emissions, where each loop is heated by random nanoflares depending on the loop parameters derived from photospheric magnetograms observed by the Solar Dynamics Observatory/Helioseismic and Magnetic Imager. Simulated X-ray flux and temperature can reproduce the temporal variations observed by the Chandrayaan-2/Solar X-ray Monitor. Our findings show that high-frequency nanoflares contribute to cool emissions across the AR, while low- and intermediate-frequency primarily contribute to hot emissions. During the emerging phase, energy deposition is dominated by low-frequency events. Post-emergence, energy is deposited by both low- and intermediate-frequency nanoflares, while as the AR ages, the contribution from intermediate- and high-frequency nanoflares increases. The spatial distribution of heating frequencies across the AR reveals a clear pattern: the core of the active region spends most of its time in a low-frequency heating state, the periphery is dominated by high-frequency heating, and the region between the core and periphery experiences intermediate-frequency heating.

Nanoflares are believed to be key contributors to heating solar non-flaring active regions, though their individual detection remains challenging. This study uses a data-driven field-aligned hydrodynamic model to examine nanoflare properties throughout the lifecycle of AR12758. We simulate coronal loop emissions, where each loop is heated by random nanoflares depending on the loop parameters derived from photospheric magnetograms observed by SDO/HMI. Simulated X-ray flux and temperature can reproduce the temporal variations observed by Chandrayaan-2/XSM. Our findings show that high-frequency nanoflares contribute to cool emissions across the AR, while low- and intermediate- frequency primarily contribute to hot emissions. During the emerging phase, energy deposition is dominated by low-frequency events. Post-emergence, energy is deposited by both low- and intermediate-frequency nanoflares, while as the AR ages, the contribution from intermediate- and high-frequency nanoflares increases. The spatial distribution of heating frequencies across the AR reveals a clear pattern: the core of the active region spends most of its time in a low-frequency heating state, the periphery is dominated by high-frequency heating, and the region between the core and periphery experiences intermediate-frequency heating.

Nanoflares are thought to be one of the prime candidates that can heat the solar corona to its multimillion kelvin temperature. Individual nanoflares are difficult to detect with the present generation of instruments, but their presence can be inferred by comparing simulated nanoflare-heated plasma emissions with the observed emission. Using HYDRAD coronal loop simulations, we model the emission from an X-ray bright point (XBP) observed by the Marshall Grazing Incidence X-ray Spectrometer (MaGIXS), along with the nearest available observations from the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) and the X-Ray Telescope (XRT) on board the Hinode observatory. The length and magnetic field strength of the coronal loops are derived from the linear force-free extrapolation of the observed photospheric magnetogram by the Helioseismic and Magnetic Imager on board SDO. Each loop is assumed to be heated by random nanoflares, whose magnitude and frequency are determined by the loop length and magnetic field strength. The simulation results are then compared and matched against the measured intensity from AIA, XRT, and MaGIXS. Our model results indicate the observed emission from the XBP under study could be well matched by a distribution of nanoflares with average delay times 1500–3000 s. Further, we demonstrate the high sensitivity of MaGIXS and XRT for diagnosing the heating frequency using this method, while AIA passbands are found to be the least sensitive.

Nanoflares are thought to be one of the prime candidates that can heat the solar corona to its multi-million kelvin temperature. Individual nanoflares are difficult to detect with the present generation instruments, however their presence can be inferred by comparing simulated nanoflare-heated plasma emissions with the observed emission. Using HYDRAD coronal loop simulations, we model the emission from an X-ray bright point (XBP) observed by the Marshall Grazing Incidence X-ray Spectrometer (MaGIXS), along with nearest-available observations from the Atmospheric Imaging Assembly (AIA) onboard Solar Dynamics Observatory (SDO) and X-Ray Telescope (XRT) onboard Hinode observatory. The length and magnetic field strength of the coronal loops are derived from the linear-force-free extrapolation of the observed photospheric magnetogram by Helioseismic and Magnetic Imager (HMI) onboard SDO. Each loop is assumed to be heated by random nanoflares, whose magnitude and frequency are determined by the loop length and magnetic field strength. The simulation results are then compared and matched against the measured intensity from AIA, XRT, and MaGIXS. Our model results indicate the observed emissions from the XBP under study could be well matched by a distribution of nanoflares with average delay times 1500 s to 3000 s, which suggest that the heating is dominated by high-frequency events. Further, we demonstrate the high sensitivity of MaGIXS and XRT to diagnose the heating frequency using this method, while AIA passbands are found to be the least sensitive.

We present multiwavelength observations by Chandrayaan-2/Solar X-ray Monitor, Solar Dynamics Observatory/Atmospheric Imaging Assembly, and Hinode/X-Ray Telescope (XRT) of a B-class flare observed on 2021 February 25, originating from an active region (AR 12804) near the northwest limb. The microflare lasts for ∼30 minutes and is composed of hot loops reaching temperatures of 10 MK. We report excellent agreement (within 20%) for the average effective temperatures obtained at the flare peak from all the three instruments, which have different temperature sensitivities. The XRT filter combination of Be-thin and Be-med provides an excellent opportunity to measure the high temperatures in such microflare events. The elemental abundances during the evolution of the microflare are also studied and observed to drop toward photospheric values at the flare peak time, compared to coronal values during the rise and decay phase. This is consistent with previous XSM studies.