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Content archived on 2024-04-30

The detection of gravitational waves

Objective



Research objectives and content
The detection of gravitational waves from astrophysical sources is probably one of the most keenly awaited events in the history of astrophysics. Our purpose is to study phenomenological aspects of gravitational radiation detection and to develop techniques for analyzing data. Our study will be primarily devoted to binary systems and pulsars which are among the most promising sources of the gravitational waves. We will work in the development of more efficient algorithms for the choice of an optimal set of templates to detect a known waveform buried in noisy data. We will investigate such techniques with the aid of differential geometry which provides geometric insight into the problem. Another problem is that the search for long-lived binary systems and pulsars involves making corrections for Doppler effects from the motion of the Earth. These corrections must be done differently for different places on the sky. This gives detectors good angular resolution but presents formidable data-analysis problems because there are 1013 different resolvable positions on the sky in a 1-year observation at 1 KHz. This is important because these sources may be the first to be seen by ground-based detectors.
Training content (objective, benefit and expected impact)
The training aspect of this proposal focuses in getting a deeper knowledge in the main scientific area of the applicant to acquire new methods and techniques or analysis for the problem described and to learn and apply various computer languages and computer algorithms for parallel processing. Links with industry / industrial relevance (22)

Fields of science (EuroSciVoc)

Programme(s)

Topic(s)

Call for proposal

Data not available

Funding Scheme

RGI - Research grants (individual fellowships)

Coordinator

MAX-PLANCK-GESELLSCHAFT ZUR FOERDERUNG DER WISSENSCHAFTEN E.V.
EU contribution
No data
Address
1,Am Muelenberg 1
14476 GOLM
Germany
Total cost
No data

Participants (1)