102 research outputs found
Frequency domain reduced order model of aligned-spin effective-one-body waveforms with generic mass-ratios and spins
I provide a frequency domain reduced order model (ROM) for the aligned-spin
effective-one-body (EOB) model "SEOBNRv2" for data analysis with second and
third generation ground based gravitational wave (GW) detectors. SEOBNRv2
models the dominant mode of the GWs emitted by the coalescence of black hole
(BH) binaries. The large physical parameter space (dimensionless spins and symmetric mass-ratios )
requires sophisticated reduced order modeling techniques, including patching in
the parameter space and in frequency. I find that the time window over which
the inspiral-plunge and the merger-ringdown waveform in SEOBNRv2 are connected
is discontinuous when the spin of the deformed Kerr BH or the
symmetric mass-ratio . This discontinuity increases resolution
requirements for the ROM. The ROM can be used for compact binary systems with
total masses of or higher for the advanced LIGO (aLIGO) design
sensitivity and a Hz lower cutoff frequency. The ROM has a worst mismatch
against SEOBNRv2 of , but in general mismatches are better than . The ROM is crucial for key data analysis applications for compact
binaries, such as GW searches and parameter estimation carried out within the
LIGO Scientific Collaboration (LSC).Comment: 14 pages, 14 figure
Measuring intermediate mass black hole binaries with advanced gravitational wave detectors
We perform a systematic study to explore the accuracy with which the
parameters of intermediate-mass black-hole binary systems can be measured from
their gravitational wave (GW) signatures using second-generation GW detectors.
We make use of the most recent reduced-order models containing inspiral, merger
and ringdown signals of aligned-spin effective-one-body waveforms (SEOBNR) to
significantly speed up the calculations. We explore the phenomenology of the
measurement accuracies for binaries with total masses between 50 and 500
and mass ratios between 0.1 and 1. We find that (i) at total masses
below ~200 , where the signal-to-noise-ratio is dominated by the
inspiral portion of the signal, the chirp mass parameter can be accurately
measured; (ii) at higher masses, the information content is dominated by the
ringdown, and total mass is measured more accurately; (iii) the mass of the
lower-mass companion is poorly estimated, especially at high total mass and
more extreme mass ratios; (iv) spin cannot be accurately measured for our
injection set with non-spinning components. Most importantly, we find that for
binaries with non-spinning components at all values of the mass ratio in the
considered range and at network signal-to-noise ratio of 15, analyzed with
spin-aligned templates, the presence of an intermediate-mass black hole with
mass >100 can be confirmed with 95% confidence in any binary that
includes a component with a mass of 130 or greater.Comment: 6 pages, 8 figures; published versio
Measuring neutron star tidal deformability with Advanced LIGO: a Bayesian analysis of neutron star - black hole binary observations
The discovery of gravitational waves (GW) by Advanced LIGO has ushered us
into an era of observational GW astrophysics. Compact binaries remain the
primary target sources for LIGO, of which neutron star-black hole (NSBH)
binaries form an important subset. GWs from NSBH sources carry signatures of
(a) the tidal distortion of the neutron star by its companion black hole during
inspiral, and (b) its potential tidal disruption near merger. In this paper, we
present a Bayesian study of the measurability of neutron star tidal
deformability using observation(s) of
inspiral-merger GW signals from disruptive NSBH coalescences, taking into
account the crucial effect of black hole spins. First, we find that if
non-tidal templates are used to estimate source parameters for an NSBH signal,
the bias introduced in the estimation of non-tidal physical parameters will
only be significant for loud signals with signal-to-noise ratios . For
similarly loud signals, we also find that we can begin to put interesting
constraints on (factor of 1-2) with individual
observations. Next, we study how a population of realistic NSBH detections will
improve our measurement of neutron star tidal deformability. For astrophysical
populations of NSBH mergers, we find 20-35 events to be sufficient
to constrain within , depending on the
chosen equation of state. In this we also assume that LIGO will detect black
holes with masses within the astrophysical -. If the mass-gap
remains preserved in NSBHs detected by LIGO, we estimate that
detections will furnish comparable tidal measurement accuracy. In
both cases, we find that the loudest 5-10 events to provide most of the tidal
information, thereby facilitating targeted follow-ups of NSBHs in the upcoming
LIGO-Virgo runs.Comment: 21 pages, 17 figure
Surrogate model for an aligned-spin effective one body waveform model of binary neutron star inspirals using Gaussian process regression
Fast and accurate waveform models are necessary for measuring the properties
of inspiraling binary neutron star systems such as GW170817. We present a
frequency-domain surrogate version of the aligned-spin binary neutron star
waveform model using the effective one body formalism known as SEOBNRv4T. This
model includes the quadrupolar and octopolar adiabatic and dynamical tides. The
version presented here is improved by the inclusion of the spin-induced
quadrupole moment effect, and completed by a prescription for tapering the end
of the waveform to qualitatively reproduce numerical relativity simulations.
The resulting model has 14 intrinsic parameters. We reduce its dimensionality
by using universal relations that approximate all matter effects in terms of
the leading quadrupolar tidal parameters. The implementation of the time-domain
model can take up to an hour to evaluate using a starting frequency of 20Hz,
and this is too slow for many parameter estimation codes that require
sequential waveform evaluations. We therefore construct a fast and faithful
frequency-domain surrogate of this model using Gaussian process regression. The
resulting surrogate has a maximum mismatch of for the
Advanced LIGO detector, and requires 0.13s to evaluate for a waveform with a
starting frequency of 20Hz. Finally, we perform an end-to-end test of the
surrogate with a set of parameter estimation runs, and find that the surrogate
accurately recovers the parameters of injected waveforms.Comment: 19 pages, 10 figures, submitted to PR
Statistical Gravitational Waveform Models: What to Simulate Next?
Models of gravitational waveforms play a critical role in detecting and
characterizing the gravitational waves (GWs) from compact binary coalescences.
Waveforms from numerical relativity (NR), while highly accurate, are too
computationally expensive to produce to be directly used with Bayesian
parameter estimation tools like Markov-chain-Monte-Carlo and nested sampling.
We propose a Gaussian process regression (GPR) method to generate accurate
reduced-order-model waveforms based only on existing accurate (e.g. NR)
simulations. Using a training set of simulated waveforms, our GPR approach
produces interpolated waveforms along with uncertainties across the parameter
space. As a proof of concept, we use a training set of IMRPhenomD waveforms to
build a GPR model in the 2-d parameter space of mass ratio and
equal-and-aligned spin . Using a regular, equally-spaced grid of
120 IMRPhenomD training waveforms in and ,
the GPR mean approximates IMRPhenomD in this space to mismatches below
. Our approach can alternatively use training waveforms
directly from numerical relativity. Beyond interpolation of waveforms, we also
present a greedy algorithm that utilizes the errors provided by our GPR model
to optimize the placement of future simulations. In a fiducial test case we
find that using the greedy algorithm to iteratively add simulations achieves
GPR errors that are order of magnitude lower than the errors from
using Latin-hypercube or square training grids
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