95 research outputs found
Detecting extreme mass ratio inspirals with LISA using time–frequency methods
The inspirals of stellar-mass compact objects into supermassive black holes are some of the most important sources for LISA. Detection techniques based on fully coherent matched filtering have been shown to be computationally intractable. We describe an efficient and robust detection method that utilizes the time–frequency evolution of such systems. We show that a typical extreme mass ratio inspiral (EMRI) source could possibly be detected at distances of up to ~2 Gpc, which would mean ~tens of EMRI sources can be detected per year using this technique. We discuss the feasibility of using this method as a first step in a hierarchical search
Photons with sub-Planckian Energy Cannot Efficiently Probe Space-Time Foam
Extra-galactic sources of photons have been used to constrain space-time
quantum fluctuations in the Universe. In these proposals, the fundamental
"fuzziness" of distance caused by space-time quantum fluctuations has been
directly identified with fluctuations in optical paths. Phase-front
corrugations deduced from these optical-path fluctuations are then applied to
light from extra-galactic point sources, and used to constrain various models
of quantum gravity. However, when a photon propagates in three spatial
dimensions, it does not follow a specific ray, but rather samples a finite,
three-dimensional region around that ray --- thereby averaging over space-time
quantum fluctuations all through that region. We use a simple, random-walk type
model to demonstrate that, once the appropriate wave optics is applied, the
averaging of neighboring space-time fluctuations will cause much less
distortion to the phase front. In our model, the extra suppression factor due
to diffraction is the wave length in units of the Planck length, which is at
least for astronomical observations.Comment: This is a revised version of arXiv:gr-qc/060509
Application of graphics processing units to search pipelines for gravitational waves from coalescing binaries of compact objects
We report a novel application of a graphics processing unit (GPU) for the purpose of accelerating the search pipelines for gravitational waves from coalescing binaries of compact objects. A speed-up of 16-fold in total has been achieved with an NVIDIA GeForce 8800 Ultra GPU card compared with one core of a 2.5 GHz Intel Q9300 central processing unit (CPU). We show that substantial improvements are possible and discuss the reduction in CPU count required for the detection of inspiral sources afforded by the use of GPUs
Detection of Binary Black Hole Mergers from the Signal-to-Noise Ratio Time Series Using Deep Learning
Gravitational wave detection has opened up new avenues for exploring and
understanding some of the fundamental principles of the universe. The optimal
method for detecting modelled gravitational-wave events involves template-based
matched filtering and doing a multi-detector search in the resulting
signal-to-noise ratio time series. In recent years, advancements in machine
learning and deep learning have led to a flurry of research into using these
techniques to replace matched filtering searches and for efficient and robust
parameter estimation. This paper presents a novel approach that utilizes deep
learning techniques to detect gravitational waves from the signal-to-noise
ratio time series produced from matched filtering. We do this to investigate if
an efficient deep-learning model could replace the computationally expensive
post-processing in current search pipelines. We present a feasibility study
where we look to detect gravitational waves from binary black hole mergers in
simulated stationary Gaussian noise from the LIGO detector in Hanford,
Washington. We show that our model can match the performance of a
single-detector matched filtering search and that the ranking statistic from
the output of our model was robust over unseen noise, exhibiting promising
results for practical online implementation in the future. We discuss the
possible implications of this work and its future applications to
gravitational-wave detection.Comment: 9 pages, 4 figure
Gravitational wave astronomy
We are entering a new era of gravitational-wave astronomy. The ground-based interferometers have reached their initial design sensitivity in the audio band. Several upper limits have been set for anticipated astrophysical sources from the science data. The advanced detectors in the US and in Europe are expected to be operational around 2015. New advanced detectors are also planned in Japan and in India. The first direct detections of gravitational waves are expected within this decade. In the meanwhile, three pulsar timing array projects are forming an international collaboration to detect gravitational waves directly in the nanoHertz range using timing data from millisecond pulsars. The first direct detection of nanoHertz gravitational waves are also expected within this decade. In this paper, we review the status of current gravitational-wave detectors, possible types of sources, observational upper limits achieved, and future prospects for direct detection of gravitational waves
Geometrical Expression for the Angular Resolution of a Network of Gravitational-Wave Detectors
We report for the first time general geometrical expressions for the angular
resolution of an arbitrary network of interferometric gravitational-wave (GW)
detectors when the arrival-time of a GW is unknown. We show explicitly elements
that decide the angular resolution of a GW detector network. In particular, we
show the dependence of the angular resolution on areas formed by projections of
pairs of detectors and how they are weighted by sensitivities of individual
detectors. Numerical simulations are used to demonstrate the capabilities of
the current GW detector network. We confirm that the angular resolution is poor
along the plane formed by current LIGO-Virgo detectors. A factor of a few to
more than ten fold improvement of the angular resolution can be achieved if the
proposed new GW detectors LCGT or AIGO are added to the network. We also
discuss the implications of our results for the design of a GW detector
network, optimal localization methods for a given network, and electromagnetic
follow-up observations.Comment: 13 pages, for Phys. Rev.
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