The Mock LISA Data Challenges (MLDCs) 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 signals from 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, and they have already demonstrated the recovery of model signals from supermassive black-hole binaries of SNRs between 10 and 200, from ~ 20,000 overlapping Galactic white-dwarf binaries (among a realistically distributed population of 26 million), and from the extreme--mass-ratio inspirals of compact objects into central galactic black holes with SNRs ~ 100.
I am co-chair of the MLDC taskforce that has been formulating the challenge problems, producing the data sets, administering the challenge rounds, collecting and evaluating results. In collaboration with Curt Cutler, Jeff Crowder, Pavlin Savov, and others, I am also participating in the challenges as a contestant, concentrating especially on the searches for supermassive--black-hole binary inspirals.
Go back to my research page.