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Report on the second Mock LISA Data Challenge

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arxiv 0711.2667 v1 pith:6DK575OJ submitted 2007-11-16 gr-qc

Stanislav Babak , John G. Baker , Matthew J. Benacquista , Neil J. Cornish , Jeff Crowder , Curt Cutler , Shane L. Larson , Tyson B. Littenberg
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Edward K. Porter Michele Vallisneri Alberto Vecchio (the Mock LISA Data Challenge task force) Gerard Auger Leor Barack Arkadiusz Blaut Ed Bloomer Duncan A. Brown Nelson Christensen James Clark Stephen Fairhurst Jonathan R. Gair Hubert Halloin Martin Hendry Arturo Jimenez Andrzej Krolak Ilya Mandel Chris Messenger Renate Meyer Soumya Mohanty Rajesh Nayak Antoine Petiteau Matt Pitkin Eric Plagnol Reinhard Prix Emma L. Robinson Christian Roever Pavlin Savov Alexander Stroeer Jennifer Toher John Veitch Jean-Yves Vinet Linqing Wen John T. Whelan Graham Woan (the Challenge 2 participants)
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The Mock LISA Data Challenges are a program to demonstrate LISA data-analysis capabilities and to encourage their development. Each round of challenges consists of several data sets containing simulated instrument noise and gravitational-wave sources of undisclosed parameters. Participants are asked to analyze the data sets and report the maximum information about source parameters. The challenges are being released in rounds of increasing complexity and realism: in this proceeding we present the results of Challenge 2, issued in January 2007, which successfully demonstrated the recovery of signals from supermassive black-hole binaries, from ~20,000 overlapping Galactic white-dwarf binaries, and from the extreme-mass-ratio inspirals of compact objects into central galactic black holes.

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Cited by 3 Pith papers

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  1. Time-frequency Imprints of Extreme Mass-Ratio Inspirals in Confusion Gravitational Wave Background

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    astro-ph.IM 2026-05 conditional novelty 6.0 of 10

    Inpainting allows recovery of pre-merger massive black hole binary signals in LISA data despite gaps and overlaps.

  3. Improving the resolution of double white dwarf systems with spaceborne gravitational wave observatories using a robust astrophysical prior

    gr-qc 2026-05 unverdicted novelty 4.0 of 10

    Adding a prior linking GW frequency f to its derivative ḏ from detached white dwarf mass limits to the GBSIEVER iterative pipeline raises resolved DWD sources by ~7.3% for LISA and ~14.6% for the LISA-Taiji network on...

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