514 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 $z\sim13$ 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

### A Time Domain Waveform for Testing General Relativity

Gravitational-wave parameter estimation is only as good as the theory the
waveform generation models are based upon. It is therefore crucial to test
General Relativity (GR) once data becomes available. Many previous works, such
as studies connected with the ppE framework by Yunes and Pretorius, rely on the
stationary phase approximation (SPA) to model deviations from GR in the
frequency domain. As Fast Fourier Transform algorithms have become considerably
faster and in order to circumvent possible problems with the SPA, we test GR
with corrected time domain waveforms instead of SPA waveforms. Since a
considerable amount of work has been done already in the field using SPA
waveforms, we establish a connection between leading-order-corrected waveforms
in time and frequency domain, concentrating on phase-only corrected terms. In a
Markov Chain Monte Carlo study, whose results are preliminary and will only be
available later, we will assess the ability of the eLISA detector to measure
deviations from GR for signals coming from supermassive black hole inspirals
using these corrected waveforms.Comment: 5 pages. Proceedings of LISA Symposium X, submitted to Journal of
Physics: Conference Serie

### Supermassive Black Hole Tests of General Relativity with eLISA

Motivated by the parameterized post-Einsteinian (ppE) scheme devised by Yunes
and Pretorius, which introduces corrections to the post-Newtonian coefficients
of the frequency domain gravitational waveform in order to emulate alternative
theories of gravity, we compute analytical time domain waveforms that, after a
numerical Fourier transform, aim to represent (phase corrected only) ppE
waveforms. In this formalism, alternative theories manifest themselves via
corrections to the phase and frequency, as predicted by General Relativity
(GR), at different post-Newtonian (PN) orders. In order to present a generic
test of alternative theories of gravity, we assume that the coupling constant
of each alternative theory is manifestly positive, allowing corrections to the
GR waveforms to be either positive or negative. By exploring the capabilities
of massive black hole binary GR waveforms in the detection and parameter
estimation of corrected time domain ppE signals, using the current eLISA
configuration (as presented for the ESA Cosmic Vision L3 mission), we
demonstrate that for corrections arising at higher than 1PN order in phase and
frequency, GR waveforms are sufficient for both detecting and estimating the
parameters of alternative theory signals. However, for theories introducing
corrections at the 0 and 0.5 PN order, GR waveforms are not capable of covering
the entire parameter space, requiring the use of non-GR waveforms for detection
and parameter estimation.Comment: 13 pages, 5 figure

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