Time-frequency analysis of extreme-mass-ratio inspiral signals in mock LISA data
arXiv:0710.5250 · doi:10.1088/1742-6596/122/1/012037
Abstract
Extreme-mass-ratio inspirals (EMRIs) of ~ 1-10 solar-mass compact objects into ~ million solar-mass massive black holes can serve as excellent probes of strong-field general relativity. The Laser Interferometer Space Antenna (LISA) is expected to detect gravitational wave signals from apprxomiately one hundred EMRIs per year, but the data analysis of EMRI signals poses a unique set of challenges due to their long duration and the extensive parameter space of possible signals. One possible approach is to carry out a search for EMRI tracks in the time-frequency domain. We have applied a time-frequency search to the data from the Mock LISA Data Challenge (MLDC) with promising results. Our analysis used the Hierarchical Algorithm for Clusters and Ridges to identify tracks in the time-frequency spectrogram corresponding to EMRI sources. We then estimated the EMRI source parameters from these tracks. In these proceedings, we discuss the results of this analysis of the MLDC round 1.3 data.
Amaldi-7 conference proceedings; requires jpconf style files
References in corpus (2)
Cited by in corpus (12)
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- An algorithm for detection of extreme mass ratio inspirals in LISA data
- A Constrained Metropolis-Hastings Search for EMRIs in the Mock LISA Data Challenge 1B
- Improved time-frequency analysis of extreme-mass-ratio inspiral signals in mock LISA data
- A LISA Data-Analysis Primer
- Dilated convolutional neural network for detecting extreme-mass-ratio inspirals
- Verifying black hole orbits with gravitational spectroscopy
- Scalable data-analysis framework for long-duration gravitational waves from compact binaries using short Fourier transforms
- A source-free integration method for black hole perturbations and self-force computation: Radial fall
- Astrophysics with the Laser Interferometer Space Antenna
- Constructing a gravitational wave analysis pipeline for extremely large mass ratio inspirals
- Searching for gravitational waves emitted by binaries with spinning components