Research

Fast and Trustworthy Models for Gravitational-Wave Inference

Gravitational-wave parameter estimation can require millions of waveform evaluations. The most faithful numerical models are often too expensive to evaluate directly at that scale. My doctoral research addressed this gap by building compact surrogate models that learn the structure of high-fidelity simulations and return accurate waveforms quickly enough for inference workflows.

One part of this work focused on black-hole binaries in challenging regions of parameter space, including intermediate mass ratios, spin, and inclined orbits. I combined reduced-order bases, empirical interpolation, and Gaussian process regression to create reusable waveform models and integrated them with community software used by gravitational-wave researchers.

A second part addressed model uncertainty. Approximate waveform models can introduce systematic errors into inferred source parameters, especially for high signal-to-noise observations. I developed a probabilistic extension to the SEOBNRv4 waveform model that represents calibration uncertainty and propagates it through Bayesian parameter estimation. Tests on simulated signals showed that accounting for this uncertainty reduced normalized parameter bias and prevented overly confident estimates.

This research supports both current ground-based detectors such as LIGO and future space-based observatories such as LISA. It also reflects the kind of work I want to continue: building numerical tools that are scientifically defensible, computationally practical, and usable by a broader research community.

Publications

I have authored or co-authored five peer-reviewed publications spanning gravitational-wave modeling, uncertainty quantification, numerical relativity, reduced-order methods, X-ray timing, and spectral analysis.

  1. Incorporating waveform calibration error in gravitational-wave modeling and inference for SEOBNRv4 — Ritesh Bachhar, Michael Pürrer, Stephen R. Green. Physical Review D 111, 084050 (2025). [Journal] [arXiv]
  2. Gravitational wave surrogate model for spinning, intermediate mass-ratio binaries based on perturbation theory and numerical relativity — Katie Rink, Ritesh Bachhar, Tousif Islam, et al.. Physical Review D 110, 124069 (2024). [Journal] [arXiv]
  3. Binary Black Hole Coalescence Phenomenology from Numerical Relativity — Richard H. Price, Ritesh Bachhar, Gaurav Khanna. Physical Review D 113, 044013 (2026). [Journal] [arXiv]
  4. Angular Momentum for Black Hole Binaries in Numerical Relativity — Ritesh Bachhar, Richard H. Price, Gaurav Khanna. Physical Review D 108, 064019 (2023). [Journal] [arXiv]
  5. Timing and spectral studies of Cen X-3 in multiple luminosity states using AstroSat — Ritesh Bachhar, Gayathri Raman, Varun Bhalerao, et al.. Monthly Notices of the Royal Astronomical Society 517, 4138–4149 (2022). [Journal] [arXiv]