Home About Me Research CV Academics Extracurricular
Research Interests


Identifying Gravitational Lenses in Rubin LSST Data
I'm doing my master's thesis currently with Prof Dr. Surhud More and Dr. Anupreeta More, at the Inter-University Centre for Astronomy and Astrophysics (IUCAA), Pune. In this work, I'm studying gravitational strong lensing of Type Ia supernovae (SNIa) and developing computational tools to detect such systems in the upcoming LSST survey by the Vera Rubin Observatory. Gravitational lensing is the phenomenon of bending of the light in the presence of a high gravitational potential. Multiply imaged strongly lensed SNIa are critical cosmological probes, as the study of their time delays can be used to obtain better constraints on the expansion rate of the universe i.e., the value of the Hubble constant.

Vera Rubin observatory, currently under construction in Chile, will conduct the Legacy Survey of Space and Time (LSST). The LSST survey is aimed to conduct a deep survey of the sky for ten years. Over this duration, it will image about 20,000 deg2 of sky in the optical wavelength every week. The goal of my thesis work is to construct a pipeline to identify the strongly lensed SNIa from the LSST data, to analyze the pipeline for its efficiency, and to explore the use of these lens systems to constrain the Hubble constant. I am also conducting color-magnitude analysis on the set of simulated multiply-imaged SNIa systems to look for a pattern that can act as an early-detection marker for multiple-imaged SNIa systems in future searches.


Study of Disk Winds in the X-ray Binary Systems
An X-ray binary system consists of an accreting compact object, like a black hole or a neutron star, and a stellar companion. It is characterized by extreme gravity, strong magnetic field, and strong particle and radiation densities. A significant mass transfer happens between the two components, and as the transferred matter falls onto the compact object, potential energy is released, which powers the generation of X-ray radiation.

This project consists of spectral analysis and high-resolution X-ray spectroscopy of X-ray binary systems to study the disk wind launching mechanism. Some high inclination X-ray binary systems have been reported in the literature to exhibit blue-shifted, highly ionized absorption lines, especially H- or He-like iron-K lines, on the X-ray continuum spectra. These features are understood to originate from disk winds, whose launching mechanism is still in debate. We analyse Chandra and NICER data for one such system and aim to model these absorption features using high-resolution spectroscopy packages, XSTAR and CLOUDY.


Study of the Tidal Disruption Events
For my INSPIRE project work in the summer of 2021, I worked with Dr Aru Beri on studying an astrophysical phenomenon called the tidal disruption events (TDEs). It is a phenomenon that occurs when the orbit of a star gets too close to some compact object, like a black hole, and the star gets disrupted by the tidal forces of the compact object, experiencing spaghettification. I thoroughly studied a few review papers from the literature to develop an understanding of the known properties of TDEs. We then moved on to exploring some of the reported candidates of the TDEs, specifically focussing on the candidates that were reported to accrete in X-ray. I analysed a specific TDE candidate system, WINGS J1348, with extensive archival observations available for Swift-XRT, NICER, NuSTAR, and Chandra. I performed spectral analysis on the Swift-XRT archival datasets of this system in XSPEC, an X-ray spectral fitting package in HEASOFT. I modeled the X-ray emission using a simple model, a combination of the power-law model, the blackbody model, and the galactic extinction model, available in XSPEC. Through this project, I learnt to perform the spectral analysis of accretion emission and about the different emission models available in XSPEC. This was also my first astronomy-related project and first experience working with the data of astrophysical sources.

In addition, this work also exposed me to a broader field of time-domain astronomy, which studies transient astrophysical objects, sources for which the duration of variability may be from milliseconds to days, to a few months. These include violent deep-sky objects like supernovae, gamma-ray bursts, and tidal disruption events. I remember being fascinated by the idea that I could study the variabilities in sources of astronomical scales in my lifetime, and that fascination hasn't faded since!

Application of Clustering Algorithms in RNA Velocity
In the summer of 2020, I worked on an exciting project in cell dynamics, which was to apply clustering algorithms to a newly discovered concept of RNA Velocity. In cancer cell biology, a concept called Single-cell Sequencing is extensively used to sequence the nucleic acids (DNA or RNA) to reveal information about mutations carried by small populations of cells or to study the existence and evolution of different cell types. In the case of RNAs, this method only allows the study of the cell behaviour at the static level. RNA Velocity technique overcomes this limitation of Single-cell Sequencing by studying the ratio of spliced to unspliced RNA. This ratio gives information about gene induction or repression, in turn revealing information about the future state of the cell and providing a way to study cell dynamics.

For this project, I worked on Glioblastoma (the most common type of cancer that originates in the brain) and Covid-19 Single-cell Sequencing data and Velocyto, Seurat packages in R and ScVelo package in python to study [to be added]. I applied dimension reduction techniques, UMAP, tSNE, and PCA, and used the K-Nearest neighbor clustering algorithm to visualize the results in a more meaningful way. This work was discontinued due to data-related restrictions at a later stage.