Research
Research interests
🔅 Generation, propagation and damping of magnetohydrodynamic (MHD) waves.
🔅 Magnetic reconnection and its role in coronal heating problem.
🔅 Restoration of historical solar data.
🔅 Development of automated feature detection (and tracking) algorithms.
1. MHD waves in the solar corona
The solar corona is a million Kelvin hot and dynamic upper atmospheric layer of the Sun. It is highly structured due to the dominance of the magnetic field at this height (we find lots of beautiful looking loops in EUV corona). One of the long-standing problems of solar physics is to examine why the corona is so hot (FYI, photosphere is at ~5770K). This is somewhat counter-intuitive as one expects to have cooler temperatures as you move away from the source (i.e., center of the Sun). After decades of research on this problem, two major sources have been identified as potential solutions to this 'coronal heating' problem. These two sources are: 1. MHD waves, 2. Magnetic reconnection. Interestingly, it is quiet possible to have wave-modulated reconnection or reconnection-driven waves and hence, the added complexity.
My work in this field mainly focuses on the origin and propagation of these MHD waves (both longitudinal and transverse) in long coronal structures such as coronal loops, polar plumes etc. It is rather important to first correctly identify the source(s) of these waves as it shrines light on the dynamics of the stratified solar atmosphere. I mostly use observational data from modern space-base telescopes (e.g., SDO, Hinode, IRIS, Solar Orbiter), as well as data-driven simulations [AMRVAC] along with 'forward modelling' [FoMo] to characterize these waves and also find out the possible mechanisms which can damp these waves in order to dissipate their energies into the surrounding plasma.
2. Long-term variation study
Physical processes in the Sun occur at variety of time scales, ranging from few seconds to few tens of years. Solar cycle often refers to the cyclic variation in sunspot number or in sunspot area with a period of ~11 years. Sunspots are the proxy for the magnetic fields of the Sun and hence, such variation related to the sunspots will obviously mean a variation of solar magnetic fields. Thus, almost all the solar phenomena will be affected by this solar cycle including number of solar flares and occurrences CMEs (CMEs or Coronal Mass Ejections are large scale plasma eruption from the Sun). These two things (flares & CMEs) are particularly important to us as they affect the space-weather (Sun-Earth inter-space) heavily.
In one of my works, using century-long solar observational data from Kodaikanal Solar Observatory (KSO), I have compiled a sunspot area database which spans almost 90 years from 1921. This data is also made public [visit this link to access the catalogue]. Solar active longitudes, Sunspot size variations are some of the key sciences extracted, for the first time, using this data set.
These long and consistent sunspot area records are important for our understanding of the long-term solar activity and variability. Such records also provide valuable insights into solar dynamo theory and models. Apart from Kodaikanal Observatory (India), there are other places in the world such as the Royal Greenwich Observatory (England), Debrecen Observatory (Hungary), Kislovodsk and Pulkovo observatories (UdSSR/Russia) etc have regularly recorded sunspot areas and positions. However, the individual records only cover restricted periods of time and due to some systematic differences between them, these records need to be cross-calibrated before they can be reliably used for further studies. This is exactly what we have done in @ Mandal et al, A&A,2020 . A long and consistent daily sunspot area catalogue that has been constructed by cross-calibrating data from nine different observatories. The catalogue provides daily total areas as well as individual group areas. It is thus far the most up-to-date calibrated sunspot area catalogue available out there and it is being widely used to calculate solar irradiance, sunspot group distribution and other sunspot properties. Again, this catalogue is public and can be downloaded from here.
3. Feature detection techniques
Retrieving information from old historical sunspot observations requires special feature detection techniquies (and lots of patience). In any given historical catalogue, images are often found to be in-homogeneous e.g., change in drawing style (pencil to pen & black-and-white to color), change in capturing device (change in paper), aging effects (dust in photograpic plates), miss-handeling of images (leading to artifacts like scratches) etc. Moreover, these catalogues often contain tens of thousands of images. Hence, we need suitable feature detection methods that are not only accurate but also fast enough to complete the detection in a reasonable time. I am involved in generating such algorithms for detection of sunspots, filaments and plages. Recently, I have started exploring the usage of neural networks in such detection and even applied one kind of network onto the sunspot drawings from Purple mountain observatory, China and the preliminary results indeed look very promising.
Detection of sunspot groups from Purple mountain sunspot drawings data,. using modified MRCNN model. The project is in its infancy phase and, we are working on it to improve it further.