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Published September 21, 2010 | public
Journal Article

Searches for cosmic-string gravitational-wave bursts in Mock LISA Data

Abstract

A network of observable, macroscopic cosmic (super-)strings may well have formed in the early Universe. If so, the cusps that generically develop on cosmic-string loops emit bursts of gravitational radiation that could be detectable by gravitational-wave interferometers, such as the ground-based LIGO/Virgo detectors and the planned, space-based LISA detector. Here we report on two versions of a LISA-oriented string-burst search pipeline that we have developed and tested within the context of the Mock LISA Data Challenges. The two versions rely on the publicly available MultiNest and PyMC software packages, respectively. To reduce the effective dimensionality of the search space, our implementations use the F-statistic to analytically maximize over the signal's amplitude and polarization, A and ψ, and use the FFT to search quickly over burst arrival times t_C. The standard F-statistic is essentially a frequentist statistic that maximizes the likelihood; we also demonstrate an approximate, Bayesian version of the F-statistic that incorporates realistic priors on A and ψ. We calculate how accurately LISA can expect to measure the physical parameters of string-burst sources, and compare to results based on the Fisher-matrix approximation. To understand LISA's angular resolution for string-burst sources, we draw maps of the waveform fitting factor (maximized over (A, ψ, t_C)) as a function of the sky position; these maps dramatically illustrate why (for LISA) inferring the correct sky location of the emitting string loop will often be practically impossible. In addition, we identify and elucidate several symmetries that are imbedded in this search problem, and we derive the distribution of cut-off frequencies f_(max) for observable bursts.

Additional Information

© 2010 IOP Publishing Ltd. Received 22 February 2010, in final form 6 July 2010. Published 29 July 2010. This research relied crucially on the hard work of the developers of open-source scientific software: we thank the authors and maintainers the of NumPy and SciPy Python libraries, and especially F Feroz and colleagues (MultiNest) and C Fonnesbeck and colleagues (PyMC).We thank J Gair, N Cornish and J Shapiro Key for useful interactions. The numerical computation for this work was performed primarily with computing resources from the Caltech Center for Advanced Computing Research. Much of the research described in this paper was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. MC, CC and MV also gratefully acknowledge support from the NASA grant NNX07AM80G.

Additional details

Created:
August 19, 2023
Modified:
October 20, 2023