Effective search templates for a primordial stochastic gravitational wave background
Journal Article
·
· Physical Review. D, Particles Fields
- Department of Physics, College of Humanities and Sciences, Nihon University, Tokyo 156-8550 (Japan)
We calculate the signal-to-noise ratio (SNR) of the stochastic gravitational-wave background in an extreme case that its spectrum has a sharp falloff with its amplitude close to the detection threshold. Such a spectral feature is a characteristic imprint of the change in the number of relativistic degrees of freedom on the stochastic background generated during inflation in the early Universe. We find that, although SNR is maximal with the correct template which is proportional to the assumed real spectrum, its sensitivity to the shape of template is fairly weak indicating that a simple power-law template is sufficient to detect the signature.
- OSTI ID:
- 21027581
- Journal Information:
- Physical Review. D, Particles Fields, Vol. 76, Issue 4; Other Information: DOI: 10.1103/PhysRevD.76.043516; (c) 2007 The American Physical Society; Country of input: International Atomic Energy Agency (IAEA); ISSN 0556-2821
- Country of Publication:
- United States
- Language:
- English
Similar Records
Search templates for stochastic gravitational-wave backgrounds
Using a primordial gravitational wave background to illuminate new physics
Bose-Einstein-condensed scalar field dark matter and the gravitational wave background from inflation: New cosmological constraints and its detectability by LIGO
Journal Article
·
Fri Apr 15 00:00:00 EDT 2005
· Physical Review. D, Particles Fields
·
OSTI ID:21027581
Using a primordial gravitational wave background to illuminate new physics
Journal Article
·
Tue Aug 06 00:00:00 EDT 2019
· Physical Review D
·
OSTI ID:21027581
Bose-Einstein-condensed scalar field dark matter and the gravitational wave background from inflation: New cosmological constraints and its detectability by LIGO
Journal Article
·
Fri Sep 08 00:00:00 EDT 2017
· Physical Review. D.
·
OSTI ID:21027581