Rochester Institute of Technology

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Black Hole Mergers: from simulation to detection
PI: Carlos Lousto; Co-PI(s): Manuela Campanelli, Warren Anderson (Former Principal Investigator)
Award: NSF PHY-0140326 Dates: 09/01/2002โ€”08/31/2006; Funds: $300,000

Description

Organization:The University of Texas at Brownsville

Gravitational waves are ripples of gravity thrown off by violent interactions of astrophysical bodies. They were first predicted to exist by Einstein in 1916, but because they are weakened by traveling incredibly large distances before reaching Earth, they have not yet been detected. Presently, a number of countries are completing the construction of detectors which might finally see gravitational waves, including the NSF-funded LIGO detectors. The gravitational waves which should be most easily detected by such instruments will come from colliding black holes. Unfortunately, even these events are likely to be undetectable without powerful techniques to extract the gravitational wave data from the instrumental noise. The research funded by this award will use cutting-edge computer simulations to provide partial, but vital, information about the gravitational waves from colliding black holes. This information will then be used to develop powerful new techniques for detecting the gravitational wave signals.

The confirmation of Einstein's prediction of gravitational waves is a laudable scientific objective in itself. However, there is also a much greater promise. Gravitational waves can be produced by objects, like black holes, that cannot be directly observed in any other way. Because so little is known about such objects, it is almost certain that new insights into their origins and workings will result from observing them directly for the first time. Furthermore, it is widely believed that gravitational waves will reveal aspects of the universe that have not yet even been conceived of, thus revolutionizing the current picture of the nature of the cosmos itself. While this revolution will take years to realize, this award enables the important

first step of predicting what should be sought and how to seek it.

CCRG Investigators

Campanelli, Manuela โ€” Lousto, Carlos O.

Research Areas

Binary Black Holes