Interpolating compact binary waveforms using the singular value decomposition

Compact binary systems with total masses between tens and hundreds of solar masses will produce gravitational waves during their merger phase that are detectable by second-generation ground-based gravitational-wave detectors. In order to model the gravitational waveform of the merger epoch of compact binary coalescence, the full Einstein equations must be solved numerically for the entire mass and spin parameter space. However, this is computationally expensive. Several models have been proposed to interpolate the results of numerical relativity simulations. In this paper we propose a numerical interpolation scheme that stems from the singular value decomposition. This algorithm shows promise in allowing one to construct arbitrary waveforms within a certain parameter space given a sufficient density of numerical simulations covering the same parameter space. We also investigate how similar approaches could be used to interpolate waveforms in the context of parameter estimation.Comment: 5 pages, 3 figures, presented at the joint 9th Edoardo Amaldi Conference on Gravitational Waves and 2011 Numerical Relativity - Data Analysis (NRDA) meetin

A method to estimate the significance of coincident gravitational-wave observations from compact binary coalescence

Coalescing compact binary systems consisting of neutron stars and/or black holes should be detectable with upcoming advanced gravitational-wave detectors such as LIGO, Virgo, GEO and {KAGRA}. Gravitational-wave experiments to date have been riddled with non-Gaussian, non-stationary noise that makes it challenging to ascertain the significance of an event. A popular method to estimate significance is to time shift the events collected between detectors in order to establish a false coincidence rate. Here we propose a method for estimating the false alarm probability of events using variables commonly available to search candidates that does not rely on explicitly time shifting the events while still capturing the non-Gaussianity of the data. We present a method for establishing a statistical detection of events in the case where several silver-plated (3--5$\sigma$) events exist but not necessarily any gold-plated ($>5\sigma$) events. We use LIGO data and a simulated, realistic, blind signal population to test our method

Interpolation in waveform space: enhancing the accuracy of gravitational waveform families using numerical relativity

Matched-filtering for the identification of compact object mergers in gravitational-wave antenna data involves the comparison of the data stream to a bank of template gravitational waveforms. Typically the template bank is constructed from phenomenological waveform models since these can be evaluated for an arbitrary choice of physical parameters. Recently it has been proposed that singular value decomposition (SVD) can be used to reduce the number of templates required for detection. As we show here, another benefit of SVD is its removal of biases from the phenomenological templates along with a corresponding improvement in their ability to represent waveform signals obtained from numerical relativity (NR) simulations. Using these ideas, we present a method that calibrates a reduced SVD basis of phenomenological waveforms against NR waveforms in order to construct a new waveform approximant with improved accuracy and faithfulness compared to the original phenomenological model. The new waveform family is given numerically through the interpolation of the projection coefficients of NR waveforms expanded onto the reduced basis and provides a generalized scheme for enhancing phenomenological models.Comment: 10 pages, 7 figure

LADEE Satellite Modeling and Simulation Development

As human activity on and around the Moon increases, so does the likelihood that our actions will have an impact on its atmosphere. The Lunar Atmosphere and Dust Environment Explorer (LADEE), a NASA satellite scheduled to launch in 2013, will orbit the Moon collecting composition, density, and time variability data to characterize the current state of the lunar atmosphere. LADEE will also test the concept of the "Modular Common Bus" spacecraft architecture, an effort to reduce both development time and cost by designing reusable, modular components for use in multiple missions with similar requirements. An important aspect of this design strategy is to both simulate the spacecraft and develop the flight code in Simulink, a block diagram-style programming language that allows easy algorithm visualization and performance testing. Before flight code can be tested, however, a realistic simulation of the satellite and its dynamics must be generated and validated. This includes all of the satellite control system components such as actuators used for force and torque generation and sensors used for inertial orientation reference. My primary responsibilities have included designing, integrating, and testing models for the LADEE thrusters, reaction wheels, star trackers, and rate gyroscopes

Application of a Zero-latency Whitening Filter to Compact Binary Coalescence Gravitational-wave Searches

Joint electromagnetic and gravitational-wave (GW) observation is a major goal of both the GW astronomy and electromagnetic astronomy communities for the coming decade. One way to accomplish this goal is to direct follow-up of GW candidates. Prompt electromagnetic emission may fade quickly, therefore it is desirable to have GW detection happen as quickly as possible. A leading source of latency in GW detection is the whitening of the data. We examine the performance of a zero-latency whitening filter in a detection pipeline for compact binary coalescence (CBC) GW signals. We find that the filter reproduces signal-to-noise ratio (SNR) sufficiently consistent with the results of the original high-latency and phase-preserving filter for both noise and artificial GW signals (called "injections"). Additionally, we demonstrate that these two whitening filters show excellent agreement in $\chi^2$ value, a discriminator for GW signals.Comment: 8 pages, 12 figure

Efficiently enclosing the compact binary parameter space by singular-value decomposition

Gravitational-wave searches for the merger of compact binaries use matched-filtering as the method of detecting signals and estimating parameters. Such searches construct a fine mesh of filters covering a signal parameter space at high density. Previously it has been shown that singular value decomposition can reduce the effective number of filters required to search the data. Here we study how the basis provided by the singular value decomposition changes dimension as a function of template bank density. We will demonstrate that it is sufficient to use the basis provided by the singular value decomposition of a low density bank to accurately reconstruct arbitrary points within the boundaries of the template bank. Since this technique is purely numerical it may have applications to interpolating the space of numerical relativity waveforms.Comment: 5 pages, 6 figure

Singular value decomposition applied to compact binary coalescence gravitational-wave signals

We investigate the application of the singular value decomposition to compact-binary, gravitational-wave data-analysis. We find that the truncated singular value decomposition reduces the number of filters required to analyze a given region of parameter space of compact binary coalescence waveforms by an order of magnitude with high reconstruction accuracy. We also compute an analytic expression for the expected signal-loss due to the singular value decomposition truncation.Comment: 4 figures, 6 page

Second Einstein Telescope mock data and science challenge: Low frequency binary neutron star data analysis

The Einstein Telescope is a conceived third generation gravitational-wave detector that is envisioned to be an order of magnitude more sensitive than advanced LIGO, Virgo and Kagra, which would be able to detect gravitational-wave signals from the coalescence of compact objects with waveforms starting as low as 1Hz. With this level of sensitivity, we expect to detect sources at cosmological distances. In this paper we introduce an improved method for the generation of mock data and analyse it with a new low latency compact binary search pipeline called gstlal. We present the results from this analysis with a focus on low frequency analysis of binary neutron stars. Despite compact binary coalescence signals lasting hours in the Einstein Telescope sensitivity band when starting at 5 Hz, we show that we are able to discern various overlapping signals from one another. We also determine the detection efficiency for each of the analysis runs conducted and and show a proof of concept method for estimating the number signals as a function of redshift. Finally, we show that our ability to recover the signal parameters has improved by an order of magnitude when compared to the results of the first mock data and science challenge. For binary neutron stars we are able to recover the total mass and chirp mass to within 0.5% and 0.05%, respectively

Composite gravitational-wave detection of compact binary coalescence

The detection of gravitational waves from compact binaries relies on a computationally burdensome processing of gravitational-wave detector data. The parameter space of compact-binary-coalescence gravitational waves is large and optimal detection strategies often require nearly redundant calculations. Previously, it has been shown that singular value decomposition of search filters removes redundancy. Here we will demonstrate the use of singular value decomposition for a composite detection statistic. This can greatly improve the prospects for a computationally feasible rapid detection scheme across a large compact binary parameter space.Comment: 6 pages, 3 figure