arXiv subjects

Upasna Baweja

Publications and source records attributed to Upasna Baweja.

3 recordsLinked to original sources

arXiv2026

Inferring physical parameters of solar filaments from simultaneous longitudinal and transverse oscillations

Context. Different modes of oscillations are frequently observed in solar prominences/filaments, and prominence seismology helps estimate important physical parameters like the magnetic field strength. Although the simultaneous detection of longitudinal and transverse oscillations in the same filament is not common, such rare observations provide a unique opportunity to constrain the physical parameters of interest. Aims. In this study, we aim to estimate the physical parameters of prominences undergoing simultaneous longitudinal and transverse oscillations. Methods. We apply Bayesian seismology techniques to observations of longitudinal and transverse filament oscillations to infer the magnetic field strength, the length, and the number of twists in the flux tube holding the prominence plasma. We first use the observations of longitudinal oscillations and the pendulum model to infer the posterior probability density for the magnetic field strength. The obtained marginal posterior of the magnetic field, combined with the observations of the transverse oscillations, is then used to estimate the probable values of the length of the magnetic flux tube that supports the filament material using Bayesian inference. This estimated length is used to compute the number of twists in the flux tube. Results. For the prominences under study, we find that the length of the flux tubes supporting the quiescent prominences can be very large (from 100 to 1000 Mm) and the number of twists in the flux tube are not more than three. Conclusions. Our results demonstrate that Bayesian analysis offers valuable methods to perform parameter inference in the context of prominence seismology.

astro-ph.SR↗

arXiv2025

Co-existence of longitudinal and transverse oscillations in polar plumes observed with Solar Orbiter/EUI

Magnetohydrodynamic (MHD) waves play a key role in heating the solar corona and driving the solar wind. Recent observations have shown the presence of slow magneto-acoustic and Alfv\'enic waves in polar plumes and inter-plumes. However, a complete understanding of wave dynamics in the polar regions has long been limited by the lack of simultaneous, high-resolution observations. In this study, we utilize high spatial (210 km per pixel) and high cadence (5s) dataset from the Extreme Ultraviolet Imager (EUI) aboard Solar Orbiter, acquired on 14 September 2021. Our findings reveal the simultaneous presence of slow magneto-acoustic and Alfv\'enic waves within the same polar plumes. For slow magneto-acoustic waves, the amplitudes of propagating disturbances are 1.4 to 3.2$\%$ of background intensity, with periodicities of 9 min, and the projected speed of these disturbances ranges between 115 to 125 kms$^{-1}$. The corresponding electron temperature in plumes ranges between 0.58 and 0.69 MK. The damping length of these propagating disturbances for five plumes is $\approx$2.4 to 7.1 Mm. The propagating disturbances are also detected in the fine-scale substructures within the plumes. Alfv\'enic waves, on the other hand, are detected with average displacement amplitude, periodicity, and velocity amplitudes of 165$\pm$82 km, 93$\pm$39 s, and 12$\pm$7 kms$^{-1}$ respectively. The ranges for displacement amplitude, period, and velocity amplitude are 50-600 km, 50-250 s, and 3-32 kms$^{-1}$ respectively. These results mark the first demonstration of Solar Orbiter/EUI's ability to simultaneously detect both slow magneto-acoustic and Alfv\'enic wave modes extending up to 20 Mm in polar plumes.

astro-ph.SR↗

arXiv2024

Global Coronal Magnetic Field Estimation Using Bayesian Inference

Estimating the magnetic field strength in the solar corona is crucial for understanding different physical processes happening over diverse spatio-temporal scales. However, the high temperatures and low density of the solar corona make this task challenging. The coronal magnetic field is too weak to produce a measurable splitting of the spectral lines using the Zeeman effect, and high temperature causes spectral lines to become weak and broad, making it difficult to detect the small Zeeman splitting. Coronal magneto-seismology, which combines the theoretical and observed properties of magnetohydrodynamic (MHD) waves, can be used to infer the magnetic field strength of oscillating structures in the solar corona, which are otherwise difficult to estimate. In this work, we use the Doppler velocity and density data obtained from the Coronal Multichannel Polarimeter (CoMP) on 2016 October 14 to obtain the global map of the coronal magnetic field using Bayesian inference. Two priors are used for plasma density, viz Gaussian and uniform distributions. Bayesian inference provides us with the probability distribution for the magnetic field strength at each location from 1.05 to 1.35 $R_\odot$. A comparison between the magnetic field obtained using simple inversion and Bayesian inference is also drawn. We find that the values obtained using simple inversion do not always match the maximum posterior estimates obtained using Bayesian inference. We find that the inferred values follow a power-law function for the radial variation of the coronal magnetic field, with the power-law indices for simple and Bayesian inversion being similar.

astro-ph.SR↗