Enhancing gravitational waveform models through dynamic calibration

  title={Enhancing gravitational waveform models through dynamic calibration},
  author={Yoshinta Setyawati and Frank Ohme and Sebastian Khan},
  journal={Physical Review D},
Current gravitational-wave observations made by Advanced LIGO and Advanced Virgo use theoretical models that predict the signals generated by the coalescence of compact binaries. Detections to date have been in regions of the parameter space where systematic modeling biases have been shown to be small. However, we must now prepare for a future with observations covering a wider range of binary configurations, and ever increasing detector sensitivities placing higher accuracy demands on… 

Adding eccentricity to quasicircular binary-black-hole waveform models

The detection of gravitational-wave signals from coalescing eccentric binary black holes would yield unprecedented information about the formation and evolution of compact binaries in specific

Including higher order multipoles in gravitational-wave models for precessing binary black holes

Estimates of the source parameters of gravitational-wave (GW) events produced by compact binary mergers rely on theoretical models for the GW signal. We present the first frequency-domain model for

Phenomenological model for the gravitational-wave signal from precessing binary black holes with two-spin effects

The properties of compact binaries, such as masses and spins, are imprinted in the gravitational waves (GWs) they emit and can be measured using parametrized waveform models. Accurately and

Gravitational-wave surrogate models powered by artificial neural networks

This paper uses artificial neural networks and the parallelisation power of graphics processing units (GPUs) to improve the surrogate modelling method, which can produce accelerated versions of existing models, and builds a time-domain surrogate model of the spin-aligned binary black hole waveform model SEOBNRv4.

Multiwaveform inference of gravitational waves

This work provides a method to marginalize over the uncertainty in a set of waveform approximants by constructing a mixture-model multi-waveform likelihood, enabling the production of marginalized combined sample sets from independent runs.

Regression methods in waveform modeling: a comparative study

It is concluded that sophisticated regression methods are not necessarily needed in standard gravitational-wave modeling applications, although machine-learning techniques might be more suitable for problems with higher complexity than what is tested here.



Frequency domain reduced order models for gravitational waves from aligned-spin compact binaries

Black-hole binary coalescences are one of the most promising sources for the first detection of gravitational waves. Fast and accurate theoretical models of the gravitational radiation emitted from

Parameter estimation for compact binaries with ground-based gravitational-wave observations using the LALInference software library

This work describes the LALInference software library for Bayesian parameter estimation of compact binary signals, which builds on several previous methods to provide a well-tested toolkit which has already been used for several studies.

A Surrogate model of gravitational waveforms from numerical relativity simulations of precessing binary black hole mergers

We present the first surrogate model for gravitational waveforms from the coalescence of precessing binary black holes. We call this surrogate model NRSur4d2s. Our methodology significantly extends

Fast and accurate inference on gravitational waves from precessing compact binaries

The first reduced-order models of gravitational-wave signals that include the effects of spin precession, inspiral, merger, and ringdown in compact object binaries are constructed and that are valid for component masses describing binary neutron star, binary black hole, and mixed binary systems.

Numerical relativity waveform surrogate model for generically precessing binary black hole mergers

A generic, noneccentric binary black hole (BBH) system emits gravitational waves (GWs) that are completely described by seven intrinsic parameters: the black hole spin vectors and the ratio of their

Statistical Gravitational Waveform Models: What to Simulate Next?

A Gaussian process regression (GPR) method to generate accurate reduced-order-model waveforms based only on existing accurate (e.g. NR) simulations is proposed and a greedy algorithm is presented that utilizes the errors provided by the GPR model to optimize the placement of future simulations.

Fast and accurate prediction of numerical relativity waveforms from binary black hole mergers using surrogate models

An accurate surrogate model is constructed, which is evaluated in a millisecond to a second, for numerical relativity waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger.

Error-analysis and comparison to analytical models of numerical waveforms produced by the NRAR Collaboration

The Numerical–Relativity–Analytical–Relativity (NRAR) collaboration is a joint effort between members of the numerical relativity, analytical relativity and gravitational-wave data analysis

Frequency-domain gravitational waves from nonprecessing black-hole binaries. II. A phenomenological model for the advanced detector era

We present a new frequency-domain phenomenological model of the gravitational-wave signal from the inspiral, merger and ringdown of nonprecessing (aligned-spin) black-hole binaries. The model is

Frequency-domain gravitational waves from nonprecessing black-hole binaries. I. New numerical waveforms and anatomy of the signal

In this paper we discuss the anatomy of frequency-domain gravitational-wave signals from nonprecessing black-hole coalescences with the goal of constructing accurate phenomenological waveform models.