18,299 research outputs found
Detecting gravitational waves from highly eccentric compact binaries
In dense stellar regions, highly eccentric binaries of black holes and
neutron stars can form through various n-body interactions. Such a binary could
emit a significant fraction of its binding energy in a sequence of largely
isolated gravitational wave bursts prior to merger. Given expected black hole
and neutron star masses, many such systems will emit these repeated bursts at
frequencies within the sensitive band of contemporary ground-based
gravitational wave detectors. Unfortunately, existing gravitational wave
searches are ill-suited to detect these signals. In this work, we adapt a
"power stacking" method to the detection of gravitational wave signals from
highly eccentric binaries. We implement this method as an extension of the
Q-transform, a projection onto a multiresolution basis of windowed complex
exponentials that has previously been used to analyze data from the network of
LIGO/Virgo detectors. Our method searches for excess power over an ensemble of
time-frequency tiles. We characterize the performance of our method using Monte
Carlo experiments with signals injected in simulated detector noise. Our
results indicate that the power stacking method achieves substantially better
sensitivity to eccentric binary signals than existing localized burst searches.Comment: 17 pages, 20 figure
Separating Gravitational Wave Signals from Instrument Artifacts
Central to the gravitational wave detection problem is the challenge of
separating features in the data produced by astrophysical sources from features
produced by the detector. Matched filtering provides an optimal solution for
Gaussian noise, but in practice, transient noise excursions or ``glitches''
complicate the analysis. Detector diagnostics and coincidence tests can be used
to veto many glitches which may otherwise be misinterpreted as gravitational
wave signals. The glitches that remain can lead to long tails in the matched
filter search statistics and drive up the detection threshold. Here we describe
a Bayesian approach that incorporates a more realistic model for the instrument
noise allowing for fluctuating noise levels that vary independently across
frequency bands, and deterministic ``glitch fitting'' using wavelets as
``glitch templates'', the number of which is determined by a trans-dimensional
Markov chain Monte Carlo algorithm. We demonstrate the method's effectiveness
on simulated data containing low amplitude gravitational wave signals from
inspiraling binary black hole systems, and simulated non-stationary and
non-Gaussian noise comprised of a Gaussian component with the standard
LIGO/Virgo spectrum, and injected glitches of various amplitude, prevalence,
and variety. Glitch fitting allows us to detect significantly weaker signals
than standard techniques.Comment: 21 pages, 18 figure
Gravitational waves: search results, data analysis and parameter estimation
The Amaldi 10 Parallel Session C2 on gravitational wave (GW) search results, data analysis and parameter estimation included three lively sessions of lectures by 13 presenters, and 34 posters. The talks and posters covered a huge range of material, including results and analysis techniques for ground-based GW detectors, targeting anticipated signals from different astrophysical sources: compact binary inspiral, merger and ringdown; GW bursts from intermediate mass binary black hole mergers, cosmic string cusps, core-collapse supernovae, and other unmodeled sources; continuous waves from spinning neutron stars; and a stochastic GW background. There was considerable emphasis on Bayesian techniques for estimating the parameters of coalescing compact binary systems from the gravitational waveforms extracted from the data from the advanced detector network. This included methods to distinguish deviations of the signals from what is expected in the context of General Relativity
Automated detection of galaxy-scale gravitational lenses in high resolution imaging data
Lens modeling is the key to successful and meaningful automated strong
galaxy-scale gravitational lens detection. We have implemented a lens-modeling
"robot" that treats every bright red galaxy (BRG) in a large imaging survey as
a potential gravitational lens system. Using a simple model optimized for
"typical" galaxy-scale lenses, we generate four assessments of model quality
that are used in an automated classification. The robot infers the lens
classification parameter H that a human would have assigned; the inference is
performed using a probability distribution generated from a human-classified
training set, including realistic simulated lenses and known false positives
drawn from the HST/EGS survey. We compute the expected purity, completeness and
rejection rate, and find that these can be optimized for a particular
application by changing the prior probability distribution for H, equivalent to
defining the robot's "character." Adopting a realistic prior based on the known
abundance of lenses, we find that a lens sample may be generated that is ~100%
pure, but only ~20% complete. This shortfall is due primarily to the
over-simplicity of the lens model. With a more optimistic robot, ~90%
completeness can be achieved while rejecting ~90% of the candidate objects. The
remaining candidates must be classified by human inspectors. We are able to
classify lens candidates by eye at a rate of a few seconds per system,
suggesting that a future 1000 square degree imaging survey containing 10^7
BRGs, and some 10^4 lenses, could be successfully, and reproducibly, searched
in a modest amount of time. [Abridged]Comment: 17 pages, 11 figures, submitted to Ap
Efficient Estimation of Barycentered Relative Time Delays for Distant Gravitational Wave Sources
Accurate determination of gravitational wave source parameters relies on
transforming between the source and detector frames. All-sky searches for
continuous wave sources are computationally expensive, in part, because of
barycentering transformation of time delays to a solar system frame. This
expense is exacerbated by the complicated modulation induced in signal
templates. We investigate approximations for determining time delays of signals
received by a gravitational wave detector with respect to the solar system
barycenter. A highly non-linear conventional computation is transformed into
one that has a pure linear sum in its innermost loop. We discuss application of
these results to determination of the maximal useful integration time of
continuous wave searches
Facing the LISA Data Analysis Challenge
By being the first observatory to survey the source rich low frequency region
of the gravitational wave spectrum, the Laser Interferometer Space Antenna
(LISA) will revolutionize our understanding of the Cosmos. For the first time
we will be able to detect the gravitational radiation from millions of galactic
binaries, the coalescence of two massive black holes, and the inspirals of
compact objects into massive black holes. The signals from multiple sources in
each class, and possibly others as well, will be simultaneously present in the
data. To achieve the enormous scientific return possible with LISA,
sophisticated data analysis techniques must be developed which can mine the
complex data in an effort to isolate and characterize individual signals. This
proceedings paper very briefly summarizes the challenges associated with
analyzing the LISA data, the current state of affairs, and the necessary next
steps to move forward in addressing the imminent challenges.Comment: 4 pages, no figures, Proceedings paper for the TeV Particle
Astrophysics II conference held Aug 28-31 at the Univ. of Wisconsi
The Challenges in Gravitational Wave Astronomy for Space-Based Detectors
The Gravitational Wave (GW) universe contains a wealth of sources which, with
the proper treatment, will open up the universe as never before. By observing
massive black hole binaries to high redshifts, we should begin to explore the
formation process of seed black holes and track galactic evolution to the
present day. Observations of extreme mass ratio inspirals will allow us to
explore galactic centers in the local universe, as well as providing tests of
General Relativity and constraining the value of Hubble's constant. The
detection of compact binaries in our own galaxy may allow us to model stellar
evolution in the Milky Way. Finally, the detection of cosmic (super)strings and
a stochastic background would help us to constrain cosmological models.
However, all of this depends on our ability to not only resolve sources and
carry out parameter estimation, but also on our ability to define an optimal
data analysis strategy. In this presentation, I will examine the challenges
that lie ahead in GW astronomy for the ESA L3 Cosmic Vision mission, eLISA.Comment: 12 pages. Plenary presentation to appear in the Proceedings of the
Sant Cugat Forum on Astrophysics, Sant Cugat, April 22-25, 201
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