(Jay) Digvijay Wadekar

Here is a brief description of a few selected projects.

1. Gravitational wave data analysis
Current GW searches could be overlooking some black hole mergers in LVK data because most template banks include waveforms with only the quadrupole mode
\((\ell, m) = (2, 2)\), i.e., omitting higher modes (HM) such as \((\ell,m) = (3,3), (4,4)\). In particular, templates with HM can be important for detecting high-mass systems with asymmetric mass-ratios. I worked on an approach of using a combination of post-Newtonian formulae and machine learning tools to model HM waveforms based on information contained in the quadrupole waveform. This enables reusing a quadrupole-only template bank to efficiently search for GWs with HM. Using our new pipeline, we found new events in the LIGO-VIRGO O3 data, especially in the IMBH regime.

Our new template banks are much better at catching gravitational-waves with higher-order harmonics from BBH mergers.

2. Interpretable ML techniques for cosmology and astrophysics
Finding low-scatter relationships in properties of complex systems (e.g., stars, supernovae, galaxies) is important to gain physical insights into them and/or to estimate their distances/masses. As the size of simulation/observational datasets grow, finding low-scatter relationships in the data becomes extremely arduous using manual data analysis methods. We used machine learning techniques to expeditiously search for such relations in abstract high-dimensional data-spaces. Focusing on clusters of galaxies, we found new scaling relations between their properties obtained using ML. Our relations can enable more accurate inference of cosmology and baryonic feedback from upcoming surveys of galaxy clusters such as ACT, SO, eROSITA and CMB-S4. We also explored the use of ML tools to model the galaxy-halo connection.

New equations for mass estimation of galaxy clusters/groups found using symbolic regression.

The video below is from one of my online talks

3. Using gas-rich dwarf galaxies to probe alternatives to cold, collisionless dark matter
Gas-rich dwarf galaxies located outside the virial radius of their host are relatively pristine systems. Due to the ultra-low radiative cooling rate of gas in these dwarfs, they are very strong calorimetric probes of energy injection by alternative dark matter (DM) candidates. We used these dwarfs to obtain strong constraints on popular DM models like millicharged DM, axion like particles (ALPs) and primordial black holes (PBHs). For dark photon DM and for some DM decay models, these dwarfs gives stronger constraints than all the previous literature. Observations of gas-rich dwarfs from current and upcoming 21cm and optical surveys (e.g., Rubin observatory, Roman telescope) therefore open a new way of probing DM.

Constraints from the gas-rich dwarf Leo T on decay lifetime of DM to e+e-

Here is the link to the PDF of a recent talk and below is the video

4. Analytic covariance matrices for upcoming spectroscopic galaxy surveys

In order to infer cosmological parameters from galaxy survey data, we typically use summary statistics such as the power spectrum and need an accurate estimate of their covariance matrix for the likelihood. The traditional process of obtaining the covariance involves simulating thousands of mock catalogs. We developed a novel analytic method to compute the covariance matrix which is more than four orders of magnitude faster and has excellent agreement with the state-of-the-art mock simulations upto non-linear scales (k~0.6 h/Mpc). We also validated our analytic method by using it to analyze the full-shape SDSS-BOSS survey data.

The video below is from one of my online talks