Avinash SinghResearcher
About me
I am a postdoctoral researcher at Stockholm University, working in time-domain astronomy and understanding the physics of stellar explosions. I primarily work on observationally investigating the death of massive stars, how they lose mass and eventually explode as a core-collapse supernova. I am also interested in investigating how the environments of these supernovae eventually affects the progenitor of these events.
I am passionate about Astrophotography being an Observational Astronomer by profession. Scroll down to have a look at some of my compositions. If you like what you see, head over to my Instagram.
Research
I work primarily on core-collapse supernovae (CCSNe), particularly their photometric, spectroscopic, and polarimetric evolution across time. I am an active member of the Zwicky Transient Facility (ZTF) collaboration and its transient working group, contributing to the discovery, classification, and follow-up of young and interesting transients.
My research interest spans investigation of flash spectroscopy, polarimetric evolution, late-time nebular-phase diagnostics, with an emphasis on probing explosion asymmetries, nucleosynthetic yields, and the role of circumstellar interaction. I also study dust formation in CCSNe, using multi-wavelength datasets to characterize the thermal emission and dust mass evolution. These efforts help constrain the physical mechanisms driving diversity in nebular phase light curves and skewness in emission line profiles. I also posses experience on simulating transient rates using unbiased surveys such as ZTF to better understand progenitor populations and selection effects for Type I superluminous SNe.
Briefly I summarise my areas of expertise here:
1) Coordinated follow-up strategies for interesting transients.
2) Understanding Core-collapse supernova physics and diversity through Multi-band photometry, spectroscopy, and polarimetry
3) Nebular-phase spectroscopy and explosion asymmetry
4) Dust formation and infrared signatures in CCSNe
5) Transient rate modeling and survey selection biases
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