Dr. Sumit K. Sarbadhicary

Hello visitor! I am an Assistant Research Scientist at Johns Hopkins University with broad interests in supernovae, in particular how they regulate star-formation in galaxies, and the properties of the progenitor star that exploded. I am primarily an observational astronomer, and work a lot with multi-wavelength surveys of nearby galaxies, while occasionally dabbling with analytical modeling. Check out my research below for more details!

Email: ssarbad1 (at) jh (dot) edu

Research

Supernova Progenitors

Deep VLA observations of SN 1885A in M31, an old thermonuclear supernova, from Sarbadhicary et al (2019)
Much of my work is connected to understanding the progenitors (or the original exploding star(s)) of supernovae. For thermonuclear supernovae, we know the progenitor is a white dwarf, but whether its companion is generally another white dwarf or a Sun-like star (or more evolved star) is an open question. For core-collapse supernovae, we know the progenitors are stars heavier than 8 solar masses, but the mass range where successful explosions occur is an open question, and is intricately related to the uncertain effects of binary evolution, rotation, and metallicity. A lot of my work in this area involves observing supernovae, and measuring the amount of material present around the star at the time of explosion. I have led efforts to make radio surveys a standalone wavelength for transient discovery with the CHILES VERDES survey. I am now involved in multi-wavelength follow-ups of supernovae with JWST, HST and ground-based observatories.

Relevant Publications : Sarbadhicary et al (2019), Pellegrino et al (2020), Cendes et al (2020), Sand et al (2021), Harris et al (2023), Hosseinzadeh et al (2023)

Supernova Remnants

Synchrotron radio emission versus age of supernova remnant predicted by the model of Sarbadhicary et al (2017)
Supernova remnants are the structures formed by interaction of shocks from a past supernova, with the interstellar medium. They are very unique tools for studying how stars heat and disperse gas in a galaxy, and often has hidden clues about the progenitor. A lot of my work in this area involved developing models of how supernova remnants evolve, so we can better use them to study progenitors and feedback. I have developed a model of supernova remnant emitting radio emission, using particle acceleration and synchrotron emission models, supplemented by maps of the interstellar medium and stars in the Local Group galaxies. This model (available online) can be used to understand the statistical properties of supernova remnants and cosmic rays. Recently I also applied this work to understand the recently-discovered phenomena of mysterious Odd Radio Circles. I am currently in the process of assembling the largest and most statistically complete catalogs of supernova remnants in the Local Group galaxies and the PHANGS survey of galaxies within 23 Mpc.

Relevant Publications : Sarbadhicary et al (2017), Sarbadhicary et al (2023b),

Supernova Feedback

A complex region of the interstellar medium in M33, showing overlapping supernova remnant, a feedback-driven cavity and a Wolf-Rayet star, surrounding by dense molecular clouds. Data obtained from ALMA (PI: E Koch) and JWST (PI: E Rosolowsky). Figure adapted from Sarbadhicary et al (2023)
A major area of my present research is connecting observations of stars, supernova remnants and interstellar medium) in nearby galaxies to models of supernova feedback. This feedback (i.e. the energy deposited from stellar explosions in the interstellar medium) is a major source of heat and kinetic energy that slows down the conversion of gas into stars. The physics of how this happens is not entirely clear and is a major uncertainty of our understanding of galaxy formation. With observations in nearby galaxies, I am investigating how often supernovae occur in diffuse vs dense gas, and how much energy do they deposit in the surrounding gas.

Relevant Publications : Sarbadhicary et al (2022), Sarbadhicary et al (2023a), Mayker Chen et al (2023), Egorov et al (2023)




Stellar Evolution from Stellar Population Surveys

I specialize in a novel method of studying stellar evolution models from photometric maps of stars in nearby galaxies, called the delay-time distribution. The quantity is basically the rate at which objects (e.g. supernovae) form per unit mass of stars, versus time-elapsed since star-formation. One can measure this quantity for any category of stars or stellar phenomena, using a catalog of those objects, and star-formation histories derived from photometric maps of galaxies, and compare with similar predictions from population synthesis models. This can be a very useful technique for stellar evolution research in the upcoming Rubin/Roman era.

Relevant Publications : Sarbadhicary et al (2021) Dong et al (2022)