The overarching theme of the thesis is to improve and apply high-fidelity gravitational wave (GW) surrogate models that will enable high-precision GW astronomy. One of the main goals is the application of state-of-the-art numerical relativity (NR) based surrogate waveforms to perform parameter estimation studies. This includes re-analyzing GW data from the recent LIGO-Virgo observing runs, carrying out mock data analysis studies to quantify the improvements afforded by surrogate models, and using the surrogate’s dynamical model to better quantify the binary’s orbital precession using GW datasets. I also discuss developments on constructing error estimators for GW surrogate models built on NR simulations. The error bounds provided by these models may allow for the identification of high error regions in the parameter space, as well as improve the constraints on parameters obtained from Bayesian inference. Lastly, I also discuss the potential application of sparse grids on the interpolation of marginalized log-likelihoods, which is a crucial (yet computationally expensive) step in the parameter estimation software RIFT. In summary, the thesis will discuss developments made towards addressing several challenging problems in GW data science.
- High-precision gravitational wave data analysis
- Feroz Hussain Shaik
- 0000-0003-4006-4300
- Scott E Field (Advisor) - University of Massachusetts Dartmouth, Department of MathematicsGaurav Khanna (Committee Member) - University of Rhode IslandSigal Gottlieb (Committee Member) - University of Massachusetts Dartmouth, Department of MathematicsAlfa Heryudono (Committee Member) - University of Massachusetts Dartmouth, Department of MathematicsVadapalli Vijay Subrahmanya Varma (Committee Member) - University of Massachusetts Dartmouth, Department of Mathematics
- xiv, 198 pages
- illustrations (chiefly color)
- List of figures -- List of tables -- Chapter 1. Introduction -- Chapter 2. Preliminaries -- Newtonian gravity -- Principle of relativity -- General relativity -- Gravitational-wave detection -- Gravitational-wave modeling -- Data analysis with GW models -- Chapter 3. Impact of subdominant modes on the interpretation of gravitational-wave signals from heavy binary black hole systems -- Abstract -- Introduction -- Preliminaries -- Intrinsic-parameter biases -- Discussion -- Conclusions -- Chapter 4. Evidence of large recoil velocity from a black hole merger signal -- Abstract -- Introduction -- Methods -- GW200129 spin measurements -- GW200129 kick velocity -- Remnant mass and Doppler shifts -- Conclusions -- Chapter 5. Analysis of GWTC-3 with fully precessing numerical relativity surrogate models -- Abstract -- Introduction -- Data analysis framework -- Selection of events -- Binary source parameter inference -- Model selection -- Inference of the remnant properties -- Conclusion -- Chapter 6. Ongoing and future projects -- Abstract -- Error estimation and bounds for gravitational-wave surrogate models -- Novel measurement of spin precession -- Sparse grid interpolation for improving gravitational-wave parameter estimation -- Chapter 7. Conclusions -- Bibliography.
- Includes bibliographical references (pages 173-198).
- University of Massachusetts Dartmouth
- Doctor of Philosophy (PHD)
- Engineering and Applied Science
- College of Engineering
- English
- Dissertation
- Copyright 2025 Feroz Hussain Shaik
- https://doi.org/10.62791/20477
- 9914504160701301