Approximating Simulated Stochastic Gravitational Wave Background with Broken Splines and Power Laws via MCMC Fitting
- Document #:
- LIGO-T2200252-v1
- Document type:
- T - Technical notes
Other Versions:
- Abstract:
- The Stochastic Gravitational Wave Background (SGWB) is the combination of assumed isotropic, stationary, unpolarized, and Gaussian sources of gravitational waves. We expect a large contribution of neutron star and black hole binaries to this unresolved signal. Current LIGO detectors are not sensitive enough to the SGWB strain regime but we anticipate future observing runs to have the required sensitivity for the SGWB. The promise of future detectors registering the SGWB requires the introduction of detection and fitting algorithms to understand future observation results. A Reverse Jump Markov Chain Monte Carlo (RJMCMC) algorithm permits us to probe the fitting parameters for SGWB signals via spline and power law fittings. The versatility of the RJMCMC can be applied to the astrophysical case of recovering the energy density spectra based on injected mass distributions and merger rates for binary black hole mergers (BBHs). Accurately fitting the SGWB profiles and parametrizing profiles via spline and broken power laws will aid in identifying various components of the SGWB in data from upcoming LIGO observing runs.
- Files in Document:
-
- Final Report (SURF_Final_Report.pdf, file is not accessible)
- Other Files:
- Final Presentation Slides (LIGO SURF Final Talk.pdf, file is not accessible)
- Interim Report I (SURF_Interim_Report_1.pdf, file is not accessible)
- Interim Report II (SURF_Interim_Report_2.pdf, file is not accessible)
- Proposal (CalTech_SURF_Project_Proposal.pdf, file is not accessible)
- Topics:
- Authors:
- Keywords:
- SURF2022
- Notes and Changes:
- Google Slides (https://docs.google.com/presentation/d/1wW0qfLdBxsHsu3gy8w7W8wAvwwuGdPNNbZiRKMf_7e0/edit?usp=sharing)
- Referenced by:
- LIGO-T2200355: Final reports from LIGO SURF program, Summer 2022