3,892 research outputs found
Searching for Massive Black Hole Binaries in the first Mock LISA Data Challenge
The Mock LISA Data Challenge is a worldwide effort to solve the LISA data
analysis problem. We present here our results for the Massive Black Hole Binary
(BBH) section of Round 1. Our results cover Challenge 1.2.1, where the
coalescence of the binary is seen, and Challenge 1.2.2, where the coalescence
occurs after the simulated observational period. The data stream is composed of
Gaussian instrumental noise plus an unknown BBH waveform. Our search algorithm
is based on a variant of the Markov Chain Monte Carlo method that uses
Metropolis-Hastings sampling and thermostated frequency annealing. We present
results from the training data sets and the blind data sets. We demonstrate
that our algorithm is able to rapidly locate the sources, accurately recover
the source parameters, and provide error estimates for the recovered
parameters.Comment: 11 pages, 6 figures, Submitted to CQG proceedings of GWDAW 11, AEI,
Germany, Dec 200
Detecting Galactic Binaries with LISA
One of the main sources of gravitational waves for the LISA space-borne
interferometer are galactic binary systems. The waveforms for these sources are
represented by eight parameters, of which four are extrinsic, and four are
intrinsic to the system. Geometrically, these signals exist in an 8-d parameter
space. By calculating the metric tensor on this space, we calculate the number
of templates needed to search for such sources. We show in this study that
below a particular monochromatic frequency, we can ignore one of the intrinsic
parameters and search over a 7-d space. Beyond this frequency, we have a sudden
change in dimensionality of the parameter space from 7 to 8 dimensions, which
results in a change in the scaling of the growth of template number as a
function of monochromatic frequency.Comment: 7 pages-2 figures. One figure added and typos corrected. Accepted for
the proceedings of GWDAW 9, special edition of Classical and Quantum Gravit
The Multipole Vectors of WMAP, and their frames and invariants
We investigate the Statistical Isotropy and Gaussianity of the CMB
fluctuations, using a set of multipole vector functions capable of separating
these two issues. In general a multipole is broken into a frame and
ordered invariants. The multipole frame is found to be suitably sensitive to
galactic cuts. We then apply our method to real WMAP datasets; a coadded masked
map, the Internal Linear Combinations map, and Wiener filtered and cleaned
maps. Taken as a whole, multipoles in the range or show
consistency with statistical isotropy, as proved by the Kolmogorov test applied
to the frame's Euler angles. This result in {\it not} inconsistent with
previous claims for a preferred direction in the sky for . The
multipole invariants also show overall consistency with Gaussianity apart from
a few anomalies of limited significance (98%), listed at the end of this paper.Comment: 9 pages. Submitted to MNRA
Detecting the Cosmic Gravitational Wave Background with the Big Bang Observer
The detection of the Cosmic Microwave Background Radiation (CMB) was one of
the most important cosmological discoveries of the last century. With the
development of interferometric gravitational wave detectors, we may be in a
position to detect the gravitational equivalent of the CMB in this century. The
Cosmic Gravitational Background (CGB) is likely to be isotropic and stochastic,
making it difficult to distinguish from instrument noise. The contribution from
the CGB can be isolated by cross-correlating the signals from two or more
independent detectors. Here we extend previous studies that considered the
cross-correlation of two Michelson channels by calculating the optimal signal
to noise ratio that can be achieved by combining the full set of interferometry
variables that are available with a six link triangular interferometer. In
contrast to the two channel case, we find that the relative orientation of a
pair of coplanar detectors does not affect the signal to noise ratio. We apply
our results to the detector design described in the Big Bang Observer (BBO)
mission concept study and find that BBO could detect a background with
.Comment: 15 pages, 12 Figure
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
Catching Super Massive Black Hole Binaries Without a Net
The gravitational wave signals from coalescing Supermassive Black Hole
Binaries are prime targets for the Laser Interferometer Space Antenna (LISA).
With optimal data processing techniques, the LISA observatory should be able to
detect black hole mergers anywhere in the Universe. The challenge is to find
ways to dig the signals out of a combination of instrument noise and the large
foreground from stellar mass binaries in our own galaxy. The standard procedure
of matched filtering against a grid of templates can be computationally
prohibitive, especially when the black holes are spinning or the mass ratio is
large. Here we develop an alternative approach based on Metropolis-Hastings
sampling and simulated annealing that is orders of magnitude cheaper than a
grid search. We demonstrate our approach on simulated LISA data streams that
contain the signals from binary systems of Schwarzschild Black Holes, embedded
in instrument noise and a foreground containing 26 million galactic binaries.
The search algorithm is able to accurately recover the 9 parameters that
describe the black hole binary without first having to remove any of the bright
foreground sources, even when the black hole system has low signal-to-noise.Comment: 4 pages, 3 figures, Refined search algorithm, added low SNR exampl
LISA data analysis I: Doppler demodulation
The orbital motion of the Laser Interferometer Space Antenna (LISA) produces
amplitude, phase and frequency modulation of a gravitational wave signal. The
modulations have the effect of spreading a monochromatic gravitational wave
signal across a range of frequencies. The modulations encode useful information
about the source location and orientation, but they also have the deleterious
affect of spreading a signal across a wide bandwidth, thereby reducing the
strength of the signal relative to the instrument noise. We describe a simple
method for removing the dominant, Doppler, component of the signal modulation.
The demodulation reassembles the power from a monochromatic source into a
narrow spike, and provides a quick way to determine the sky locations and
frequencies of the brightest gravitational wave sources.Comment: 5 pages, 7 figures. References and new comments adde
Time-frequency analysis of extreme-mass-ratio inspiral signals in mock LISA data
Extreme-mass-ratio inspirals (EMRIs) of ~ 1-10 solar-mass compact objects
into ~ million solar-mass massive black holes can serve as excellent probes of
strong-field general relativity. The Laser Interferometer Space Antenna (LISA)
is expected to detect gravitational wave signals from apprxomiately one hundred
EMRIs per year, but the data analysis of EMRI signals poses a unique set of
challenges due to their long duration and the extensive parameter space of
possible signals. One possible approach is to carry out a search for EMRI
tracks in the time-frequency domain. We have applied a time-frequency search to
the data from the Mock LISA Data Challenge (MLDC) with promising results. Our
analysis used the Hierarchical Algorithm for Clusters and Ridges to identify
tracks in the time-frequency spectrogram corresponding to EMRI sources. We then
estimated the EMRI source parameters from these tracks. In these proceedings,
we discuss the results of this analysis of the MLDC round 1.3 data.Comment: Amaldi-7 conference proceedings; requires jpconf style file
MCMC Exploration of Supermassive Black Hole Binary Inspirals
The Laser Interferometer Space Antenna will be able to detect the inspiral
and merger of Super Massive Black Hole Binaries (SMBHBs) anywhere in the
Universe. Standard matched filtering techniques can be used to detect and
characterize these systems. Markov Chain Monte Carlo (MCMC) methods are ideally
suited to this and other LISA data analysis problems as they are able to
efficiently handle models with large dimensions. Here we compare the posterior
parameter distributions derived by an MCMC algorithm with the distributions
predicted by the Fisher information matrix. We find excellent agreement for the
extrinsic parameters, while the Fisher matrix slightly overestimates errors in
the intrinsic parameters.Comment: Submitted to CQG as a GWDAW-10 Conference Proceedings, 9 pages, 5
figures, Published Versio
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