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

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 $\Omega_{gw} > 2.2 \times 10^{-17}$.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

LISA Source Confusion

The Laser Interferometer Space Antenna (LISA) will detect thousands of gravitational wave sources. Many of these sources will be overlapping in the sense that their signals will have a non-zero cross-correlation. Such overlaps lead to source confusion, which adversely affects how well we can extract information about the individual sources. Here we study how source confusion impacts parameter estimation for galactic compact binaries, with emphasis on the effects of the number of overlaping sources, the time of observation, the gravitational wave frequencies of the sources, and the degree of the signal correlations. Our main findings are that the parameter resolution decays exponentially with the number of overlapping sources, and super-exponentially with the degree of cross-correlation. We also find that an extended mission lifetime is key to disentangling the source confusion as the parameter resolution for overlapping sources improves much faster than the usual square root of the observation time.Comment: 8 pages, 14 figure

Characterizing the Galactic Gravitational Wave Background with LISA

We present a Monte Carlo simulation for the response of the Laser Interferometer Space Antenna (LISA) to the galactic gravitational wave background. The simulated data streams are used to estimate the number and type of binary systems that will be individually resolved in a 1-year power spectrum. We find that the background is highly non-Gaussian due to the presence of individual bright sources, but once these sources are identified and removed, the remaining signal is Gaussian. We also present a new estimate of the confusion noise caused by unresolved sources that improves on earlier estimates.Comment: 32 pages, 14 figures. Version to appear in PR

Gravity Waves, Chaos, and Spinning Compact Binaries

Spinning compact binaries are shown to be chaotic in the Post-Newtonian expansion of the two body system. Chaos by definition is the extreme sensitivity to initial conditions and a consequent inability to predict the outcome of the evolution. As a result, the spinning pair will have unpredictable gravitational waveforms during coalescence. This poses a challenge to future gravity wave observatories which rely on a match between the data and a theoretical template.Comment: Final version published in PR

Flame detector operable in presence of proton radiation

A detector of ultraviolet radiation for operation in a space vehicle which orbits through high intensity radiation areas is described. Two identical ultraviolet sensor tubes are mounted within a shield which limits to acceptable levels the amount of proton radiation reaching the sensor tubes. The shield has an opening which permits ultraviolet radiation to reach one of the sensing tubes. The shield keeps ultraviolet radiation from reaching the other sensor tube, designated the reference tube. The circuitry of the detector subtracts the output of the reference tube from the output of the sensing tube, and any portion of the output of the sensing tube which is due to proton radiation is offset by the output of the reference tube. A delay circuit in the detector prevents false alarms by keeping statistical variations in the proton radiation sensed by the two sensor tubes from developing an output signal

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