Reproducing the Results for Neutron Star Interior Composition Explorer Observation of PSR J0030 + 0451
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79 ASTRONOMY AND ASTROPHYSICS↗
Engineering topics
Capano, Collin D.
Publications and source records attributed to Capano, Collin D..
Stringent constraints on neutron-star radii from multimessenger observations and nuclear theory
The properties of neutron stars are determined by the nature of the matter that they contain. These properties can be constrained by measurements of the star’s size. We obtain stringent constraints on neutron-star radii by combining multimessenger observations of the binary neutron-star merger GW170817 with nuclear theory that best accounts for density-dependent uncertainties in the equation of state. We construct equations of state constrained by chiral effective field theory and marginalize over these using the gravitational-wave observations. Combining this with the electromagnetic observations of the merger remnant that imply the presence of a short-lived hypermassive neutron star, we find that the radius of a 1.4 M⊙ neutron star is $R_{1.4M_⊙} = 11.0^{+0.9}_{-0.6} km$ (90% credible interval). Finally, using this constraint, we show that neutron stars are unlikely to be disrupted in neutron star–black hole mergers; subsequently, such events will not produce observable electromagnetic emission.
79 ASTRONOMY AND ASTROPHYSICS↗
Posterior samples of the parameters of binary black holes from Advanced LIGO, Virgo’s second observing run
This paper presents a parameter estimation analysis of the seven binary black hole mergers—GW170104, GW170608, GW170729, GW170809, GW170814, GW170818, and GW170823—detected during the second observing run of the Advanced LIGO and Virgo observatories using the gravitational-wave open data. We describe the methodology for parameter estimation of compact binaries using gravitational-wave data, and we present the posterior distributions of the inferred astrophysical parameters. We release our samples of the posterior probability density function with tutorials on using and replicating our results presented in this paper.
79 ASTRONOMY AND ASTROPHYSICS↗
PyCBC Inference: A Python-based Parameter Estimation Toolkit for Compact Binary Coalescence Signals
We introduce new modules in the open-source PyCBC gravitational-wave astronomy toolkit that implement Bayesian inference for compact-object binary mergers. We review the Bayesian inference methods implemented and describe the structure of the modules. Here, we demonstrate that the PyCBC Inference modules produce unbiased estimates of the parameters of a simulated population of binary black hole mergers. We show that the parameters' posterior distributions obtained using our new code agree well with the published estimates for binary black holes in the first Advanced LIGO–Virgo observing run.
79 ASTRONOMY AND ASTROPHYSICS↗