English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  The search for black hole binaries using a genetic algorithm

Petiteau, A., Shang, Y., Babak, S., & Feroz, F. (2009). The search for black hole binaries using a genetic algorithm. Classical and quantum gravity, 26: 204011. doi:10.1088/0264-9381/26/20/204011.

Item is

Files

show Files
hide Files
:
CQG_26_20_204011.pdf (Any fulltext), 243KB
Name:
CQG_26_20_204011.pdf
Description:
-
OA-Status:
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Petiteau, Antoine, Author
Shang, Yu, Author
Babak, Stanislav1, Author           
Feroz, Farhan, Author
Affiliations:
1Astrophysical Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society, ou_24013              

Content

show
hide
Free keywords: General Relativity and Quantum Cosmology, gr-qc
 Abstract: In this work, we use a genetic algorithm to search for the gravitational wave signal from the inspiralling massive black hole binaries in the simulated Laser Interferometer Space Antenna (LISA) data. We consider a single signal in the Gaussian instrumental noise. This is a first step in preparation for analysis of the third round of the mock LISA data challenge. We have extended a genetic algorithm utilizing the properties of the signal and the detector response function. The performance of this method is comparable, if not better, to already existing algorithms.

Details

show
hide
Language(s):
 Dates: 2010-01-292009
 Publication Status: Issued
 Pages: 25 pages, 9 figures
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1088/0264-9381/26/20/204011
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Classical and quantum gravity
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Bristol, U.K. : Institute of Physics
Pages: - Volume / Issue: 26 Sequence Number: 204011 Start / End Page: - Identifier: -