36,029 research outputs found
The effect of different eLISA-like configurations on massive black hole parameter estimation
As the theme for the future L3 Cosmic Vision mission, ESA has recently chosen
the `Gravitational Wave Universe'. Within this call, a mission concept called
eLISA has been proposed. This observatory has a current initial configuration
consisting of 4 laser links between the three satellites, which are separated
by a distance of one million kilometers, constructing a single channel
Michelson interferometer. However, the final configuration for the observatory
will not be fixed until the end of this decade. With this in mind, we
investigate the effect of different eLISA-like configurations on massive black
hole detections. This work compares the results of a Bayesian inference study
of 120 massive black hole binaries out to a redshift of for a m
arm-length eLISA with four and six links, as well as a m
arm-length observatory with four links. We demonstrate that the original eLISA
configuration should allow us to recover the luminosity distance of the source
with an error of less than 10% out to a redshift of , and a sky error
box of out to . In contrast, both alternative
configurations suggest that we should be able to conduct the same parameter
recovery with errors of less than 10% in luminosity distance out to
and out to . Using the information from these
studies, we also infer that if we were able to construct a 2Gm, 6-link
detector, the above values would shift to for luminosity distance and
for sky error. While the final configuration will also be dependent
on both technological and financial considerations, our study suggests that
increasing the size of a two arm detector is a viable alternative to the
inclusion of a third arm in a smaller detector. More importantly, this work
further suggests no clear scientific loss between either choice.Comment: 9 pages, 5 figure
An Overview of LISA Data Analysis Algorithms
The development of search algorithms for gravitational wave sources in the
LISA data stream is currently a very active area of research. It has become
clear that not only does difficulty lie in searching for the individual
sources, but in the case of galactic binaries, evaluating the fidelity of
resolved sources also turns out to be a major challenge in itself. In this
article we review the current status of developed algorithms for galactic
binary, non-spinning supermassive black hole binary and extreme mass ratio
inspiral sources. While covering the vast majority of algorithms, we will
highlight those that represent the state of the art in terms of speed and
accuracy.Comment: 21 pages. Invited highlight article appearing in issue 01 of
Gravitational Waves Notes, "GW Notes", edited by Pau Amaro-Seoane and Bernard
F. Schutz at: http://brownbag.lisascience.org/lisa-gw-notes
Detecting compact galactic binaries using a hybrid swarm-based algorithm
Compact binaries in our galaxy are expected to be one of the main sources of
gravitational waves for the future eLISA mission. During the mission lifetime,
many thousands of galactic binaries should be individually resolved. However,
the identification of the sources, and the extraction of the signal parameters
in a noisy environment are real challenges for data analysis. So far,
stochastic searches have proven to be the most successful for this problem. In
this work we present the first application of a swarm-based algorithm combining
Particle Swarm Optimization and Differential Evolution. These algorithms have
been shown to converge faster to global solutions on complicated likelihood
surfaces than other stochastic methods. We first demonstrate the effectiveness
of the algorithm for the case of a single binary in a 1 mHz search bandwidth.
This interesting problem gave the algorithm plenty of opportunity to fail, as
it can be easier to find a strong noise peak rather than the signal itself.
After a successful detection of a fictitious low-frequency source, as well as
the verification binary RXJ0806.3+1527, we then applied the algorithm to the
detection of multiple binaries, over different search bandwidths, in the cases
of low and mild source confusion. In all cases, we show that we can
successfully identify the sources, and recover the true parameters within a
99\% credible interval.Comment: 19 pages, 5 figure
A Hamiltonian Monte Carlo method for Bayesian Inference of Supermassive Black Hole Binaries
We investigate the use of a Hamiltonian Monte Carlo to map out the posterior
density function for supermassive black hole binaries. While previous Markov
Chain Monte Carlo (MCMC) methods, such as Metropolis-Hastings MCMC, have been
successfully employed for a number of different gravitational wave sources,
these methods are essentially random walk algorithms. The Hamiltonian Monte
Carlo treats the inverse likelihood surface as a "gravitational potential" and
by introducing canonical positions and momenta, dynamically evolves the Markov
chain by solving Hamilton's equations of motion. We present an implementation
of the Hamiltonian Markov Chain that is faster, and more efficient by a factor
of approximately the dimension of the parameter space, than the standard MCMC.Comment: 16 pages, 8 figure
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
Yoga practice in the UK: a cross- sectional survey of motivation, health benefits and behaviours
Objectives Despite the popularity of yoga and evidence of its positive effects on physical and mental health, little is known about yoga practice in the UK. This study investigated the characteristics of people who practise yoga, reasons for initiating and maintaining practice, and perceived impact of yoga on health and well-being.
Design, setting and participants A cross-sectional online anonymous survey distributed through UK-based yoga organisations, studios and events, through email invites and flyers. 2434 yoga practitioners completed the survey, including 903 yoga teachers: 87% were women, 91% white and 71% degree educated; mean age was 48.7 years.
Main outcome measures Perceived impact of yoga on health conditions, health outcomes and injuries. Relationships between yoga practice and measures of health, lifestyle, stress and well-being.
Results In comparison with national population norms, participants reported significantly higher well-being but also higher anxiety; lower perceived stress, body mass index and incidence of obesity, and higher rates of positive health behaviours. 47% reported changing their motivations to practise yoga, with general wellness and fitness key to initial uptake, and stress management and spirituality important to current practice. 16% of participants reported starting yoga to manage a physical or mental health condition. Respondents reported the value of yoga for a wide range of health conditions, most notably for musculoskeletal and mental health conditions. 20.7% reported at least one yoga-related injury over their lifetime. Controlling for demographic factors, frequency of yoga practice accounted for small but significant variance in health-related regression models (p<0.001).
Conclusion The findings of this first detailed UK survey were consistent with surveys in other Western countries. Yoga was perceived to have a positive impact on physical and mental health conditions and was linked to positive health behaviours. Further investigation of yoga’s role in self-care could inform health-related challenges faced by many countries
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
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