The Mock LISA Data Challenges are a programme to demonstrate and encourage the development of LISA data-analysis capabilities, tools and techniques. At the time of this workshop, three rounds of challenges had been completed, and the next was about to start. In this paper we provide a critical analysis of the entries to the latest completed round, Challenge 1B. The entries confirm the consolidation of a range of data-analysis techniques for galactic and massive-black-hole binaries, and they include the first convincing examples of detection and parameter estimation of extreme-mass-ratio inspiral sources. In this paper we also introduce the next round, Challenge 3. Its data sets feature more realistic waveform models (e.g., galactic binaries may now chirp, and massive-black-hole binaries may precess due to spin interactions), as well as new source classes (bursts from cosmic strings, isotropic stochastic backgrounds) and more complicated nonsymmetric instrument noise.PACS numbers: 04.80. Nn, 95.55.Ym
The Mock LISA Data Challenges are a program to demonstrate LISA dataanalysis capabilities and to encourage their development. Each round of challenges consists of one or more datasets containing simulated instrument noise and gravitational waves from sources of undisclosed parameters. Participants analyze the datasets and report best-fit solutions for the source parameters. Here we present the results of the third challenge, issued in April 2008, which demonstrated the positive recovery of signals from chirping galactic binaries, from spinning supermassive-black-hole binaries (with optimal SNRs between ∼10 and 2000), from simultaneous extreme-massratio inspirals (SNRs of 10-50), from cosmic-string-cusp bursts (SNRs of 10-100), and from a relatively loud isotropic background with gw (f ) ∼ 10 −11 , slightly below the LISA instrument noise.
The Mock LISA data challenges are a program to demonstrate LISA dataanalysis capabilities and to encourage their development. Each round of challenges consists of several data sets containing simulated instrument noise and gravitational waves from sources of undisclosed parameters. Participants are asked to analyze the data sets and report the maximum information about the source parameters. The challenges are being released in rounds of increasing complexity and realism: here we present the results of Challenge 2, issued in Jan 2007, which successfully demonstrated the recovery of signals from nonspinning supermassive-black-hole binaries with optimal SNRs between ∼10 and 2000, from ∼20 000 overlapping galactic white-dwarf binaries (among a realistically distributed population of 26 million), and from the extreme-massratio inspirals of compact objects into central galactic black holes with optimal SNRs ∼100.
We present data analysis methods used in detection and the estimation of parameters of gravitational wave signals from the white dwarf binaries in the mock LISA data challenge. Our main focus is on the analysis of challenge 3.1, where the gravitational wave signals from more than 6 × 10 7Galactic binaries were added to the simulated Gaussian instrumental noise. Majority of the signals at low frequencies are not resolved individually. The confusion between the signals is strongly reduced at frequencies above 5 mHz. Our basic data analysis procedure is the maximum likelihood detection method. We filter the data through the template bank at the first step of the search, then we refine parameters using the Nelder-Mead algorithm, we remove the strongest signal found and we repeat the procedure. We detect reliably and estimate parameters accurately of more than ten thousand signals from white dwarf binaries. PACS numbers: 95.55.Ym, 04.80.Nn, 95.75.Pq, 97.60.Gb
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