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- Carl Sagan -

“Somewhere something incredible is waiting to be known.”

I am a theorist interested in developing novel statistical techniques to understand and analyse astrophysical data. I currently develop and run N-body simulations post-processed to add galaxy evolution and radiative transfer for Epoch of Reionization/Cosmic Dawn studies particularly by jointly modelling 21-cm signal observables along with JWST observations.
Below you can find information on my projects.

EoR

Epoch of Reionization

All the gas in the Universe went through two major events: recombination and reionization. While recombination led to the formation of neutral Hydrogen (and Helium!), most of the Universe's Hydrogen is now ionised. Hence it is theorised that there was a period in the Universe's history when Hydrogen was reionized. This period is known as the Epoch of Reionization (EoR).

However, the exact physics of reionization. The 21-cm line in Hydrogen is a good way to study this period, as it is a tracer for neutral Hydrogen.  This 21-cm signal, if detected, can thus give us an idea about structure formation and energy sources of reionisation. The LOFAR radio telescope is one of the telescopes used to detect this signal.

My work as a part of the LOFAR EoR team thus includes the following:

  • Testing improved techniques for signal detection: I built a template for the 21-cm signal using a Machine Learning based algorithm (Mertens et al. 2024) trained on the Grizzly simulations, and tested their performance across a range of different simulated signals, across redshifts and noise levels in Acharya et al. 2024a. I have also applied this to ≈ 10 nights of LOFAR observations at z ≈ 9.1, and report these results in an upcoming paper.

  • Testing improvements in signal modelling: With upcoming observations from LOFAR and eventually SKA, a detection of the 21-cm signal at EoR is imminent. Thus, it is important to maximise improvements in modelling of the signal with simulations. I tested the benefits of the Fixed & Paired scheme for initial conditions of simulations and show significant improvements in computational requirements over traditional simulations in Acharya et al. 2024c, where I ran a setup similar to the radiation-magnetohydrodynamic THESAN simulations.

  • The Polar simulations with alternative cosmologies: The training set of simulations used for the ML-based algorithm as well as simulations used for interpretation of observations are usually limited to a specific cosmology. This can lead to biases. To avoid this, I have built a setup to test a range of cosmologies with different values of the Hubble parameter and the σ8 parameter. I use GADGET-4 for Dark Matter N-body simulations, which are then post-processed with L-Galaxies for Semi-Analytic Modelling of galaxies and Grizzly for radiative transfer. I tune this to JWST observations and test the corresponding 21-cm signal observables generated. In the future, we intend to also include subgrid modelling to include the effect of minihalos. 

  • Generalised inference techniques: With the upcoming SKA observations, it is necessary to test whether inference of the observed 21-cm signal can be done using similar techniques as done for other telescopes. For this, I am leading the team COnstraining the SKA 21-cm Signal (COTSS-21) participating in the SKA Science Data Challenge 3b on Inference, where we shall be testing inference using Grizzly.

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The Circumgalactic Medium

The benefit of studying the Circumgalactic Medium (CGM) is twofold: 

  1. The CGM is the place where outflowing gases expelled from the galactic disk interact with the inflowing gases from the intergalactic medium and these interactions govern how star-formation proceeds in the galaxy. Thus, knowing more about the CGM (density, size, metallicity, etc.) allows us to know more about the overall structure and evolution of the galaxy. However, we cannot directly observe the CGM. Rather, we depend on absorption spectra, when the CGM of a galaxy obscures a UV background source, like a quasar. But if we only have the data on the absorption spectra, we are limited in our knowledge of the actual unabsorbed spectra emitted by the quasar in question. What we can do in this situation is to use a range of quasar models to predict the properties of the CGM, in order to know the maximum variability one can expect in the physical parameters of the CGM.

  2. Using a variety of models to predict the parameters of the CGM can be used as a tool to find which of the models is "closest" to the actual quasar in question. Thus, if we can successfully quantify how "good" or "bad" a model is in predicting the physical parameters of the CGM clouds, we can use it to predict the properties of more and more quasars!

I explored this in a project to quantify the extent of error possible on using different UV background models. Our work also indicates the possibility of obtaining measures of how "off" our chosen UVB model is, as compared to the true quasar spectra.

cgm

Other Research Interests

Having always been fascinated by the various aspects of astronomy, I have had my fair share of exploring a myriad of topics. Some of which are listed below:

  • Supermassive Black Holes, Galaxy Evolution: Numerical N-body simulations to study the behaviour and interactions of a Supermassive Black Hole binary formed during a galaxy merger event, with the stellar matter of the 2 galaxies can be a fascinating approach to understand and analyse the Final Parsec Problem. Working on this can also give us tighter constraints on the properties of the expected gravitational waves from the eventual merger of such an SMBH binary. I am interested in the development of such simulations, as well as in the analysis of data generated by them in order to study the individual interactions between stars and the black holes.

  • Observational X-ray Astronomy: Interactions can be of many forms, and to have an idea about the breadth of the same, I have explored observational data on the "small" scale of stellar X-ray astronomy for my Master's thesis. We focussed on the star system HD 179949, which has a Sun-like star with a Jupiter mass planet revolving around it, at an orbit of just ~0.04 AU (a tenth of a distance between Mercury and our Sun!). Such close distances suggest the strong possibility of Star-Planet Interactions (SPI). In particular, we found the possibility of interactions between their magnetic fields. We used archival data from Chandra, and built our phase coverage using data from XMM-Newton and Swift. We find multiple evidences pointing towards the existence of SPI, with variability tied to the planet's period of revolution, as well as its beat period with the polar rotation of the star. Even the abundance measurements of the stellar corona agree with results from similar stars with close-in Jupiter like planets, but not with similar stars with no detected planets. We also managed to model the stellar corona, by developing new methodologies to discriminate between fitting models and maximise our understanding of its structure, temperature and metallicity. Our goodness of fit estimator package can be found here: csresid.py

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