Constraints on the Dynamical Environments of Supermassive Black-Hole Binaries Using Pulsar-Timing Arrays
Abstract
We introduce a technique for gravitational-wave analysis, where Gaussian process regression is used to emulate the strain spectrum of a stochastic background by training on population-synthesis simulations. This leads to direct Bayesian inference on astrophysical parameters. For pulsar timing arrays specifically, we interpolate over the parameter space of supermassive black-hole binary environments, including three-body stellar scattering, and evolving orbital eccentricity. We illustrate our approach on mock data, and assess the prospects for inference with data similar to the NANOGrav 9-yr data release.
- Publication:
-
Physical Review Letters
- Pub Date:
- May 2017
- DOI:
- 10.1103/PhysRevLett.118.181102
- arXiv:
- arXiv:1612.02817
- Bibcode:
- 2017PhRvL.118r1102T
- Keywords:
-
- Astrophysics - Astrophysics of Galaxies;
- Astrophysics - Instrumentation and Methods for Astrophysics;
- General Relativity and Quantum Cosmology
- E-Print:
- Published in Physical Review Letters. 7 pages, 5 figures. Jupyter notebook and synthesized supermassive black-hole binary populations are available at https://github.com/stevertaylor/gw_pta_emulator