Research Area

I primarily work on investigating the death of massive stars, how they lose mass and die as a core-collapse supernovae. I'm also interested in investigating how the environments of these supernovae eventually affects the progenitor stars. I graduated from Indian Institute of Astrophysics, Bengaluru (in association with Indian Institute of Science, Bengaluru) and studied supernovae through ultra-violet, optical and near-infrared observational data with Prof. GC Anupama. I help built various reduction and analysis scripts such as RedPipe and NightSkyPlan. I'm also interested in investigating volumetric rates of transiens and explain their dust budget and nucleosynthesis yield seen in the present universe. See my research summary and list of publications on NASA ADS and ORCID. You can find a copy of my CV here .

Circumstellar Interaction and 56Ni-mixing in Type II SN 2016gfy

Optical follow-up of Type II SN 2016gfy was performed and supplemented with data from Ultra Violet data from Swift Telescope. SN~2016gfy is a luminous, slow-declining Type II SN in comparison to the extensive sample of Type II SNe in Anderson et al. (2014). The spectrum of the parent HII region of the SN yielded an oxygen abundance of 8.50+/-0.11, indicating a sub-solar metallicity for a Type II SN progenitor. The spectral evolution of SN~2016gfy features metal-poor spectra compared to normal Type II SNe and the theoretical models of Dessart et al. (2013a), signifyies a low-metallicity of the progenitor. The P-Cygni profile of Halpha in the early phase spectra displayed a boxy emission feature. It is inferred that the progenitor underwent a recent episode (30 - 80 years before the explosion) of enhanced mass loss. Numerical modeling suggested that the early light curve peak is reproduced better with an existing CSM of 0.15 solar mass spread out to 70 AU. A late-plateau bump is seen in the VRI light curves of SN 2016gfy during ~50 - 95 d. This bump was explained as a result of the continuing CSM interaction and partial mixing of radioactive 56-Ni in the outer ejecta of the SN.

1987A-like SN 2018hna

Theoretical and observational studies have shown that red supergiants are the progenitor of Type II SNe. However, the nearest naked-eye supernova in our lifetime, SN 1987A, displayed that a blue supergiant are also a progenitor to Type II SNe. We performed high-cadence UVOIR observations of one such peculiar object, i.e., SN 2018hna. The rise to the maximum in the light curves of 1987A-like events is slow, as is seen for SN 2018hna (~88 days). The early light curves of SN~2018hna distinctly displays the adiabatic cooling of the shock heated SN ejecta, referred to as the cooling envelope emissiom ensues from the 'shock breakout' Gezari et al. (2015). SN~2018hna is only the second 1987A-like SN caught within a few days from the explosion. Hydrodynamical modelling of the cooling emission suggested a progenitor of radius ~50 solar radii confirming the blue supergiant nature of SN~2018hna. We computed a sub-solar metallicity (0.3 solar metallicity) for the host galaxy of this event, which is in congruence with the environments of 1987A-like events indicating a progenitor channel associated with the low metallcity of these hosts.

Volumetric Rates of Transients

To shed light on determination of the volumetric rate of Superluminous Supernovae (SLSNe), I worked in collaboration with Dr. Lin Yan and Dr. Christoffer Fremling of CalTech, Pasadena. Volumetric rate is the sum of Supernovae (SNe) that exploded in a given time span of the survey and a fixed co-moving volume (dependent on the redshift limit specified) that can be detected with a 5-sigma confidence. Understanding these rates through the high-cadence Zwicky Transient Facility (ZTF) survey facilitates the build-up of a homogeneous sample of SLSNe due to its untargeted essence. ZTF comprises of a wide-field imager (47 deg2 field of view) on the 48-inch Palomar Oschin telescope. The intrinsic brightness range of a type of SNe determines its luminosity function (LF) and is immediately connected to its physical process of formation which currently are explained with the spin-down of a magnetar (Kasen et al. 2010). LF can also help compute the completeness of a survey to remove the unknown observational biases involved in determining rates. A working simulation code simsurvey was used for the project work.

More will be updated soon ...