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 $z\sim13$ for a $10^6$m arm-length eLISA with four and six links, as well as a $2\times10^6$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 $z\sim4$, and a sky error box of $\leq10^2\,deg^2$ out to $z\sim0.1$. 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 $z\sim12$ and $\leq10^2\,deg^2$ out to $z\sim0.4$. 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 $z\sim20$ for luminosity distance and $z\sim0.9$ 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