Astronomy and Astrophysics – Astrophysics
Scientific paper
1997-08-02
Phys.Rev. D56 (1997) 4503-4510
Astronomy and Astrophysics
Astrophysics
10 pages, Latex (uses revtex), 1 postscript figure included. Accepted for publication in Physical Review D
Scientific paper
10.1103/PhysRevD.56.4503
In the context of inflationary scenarios, the observed large angle anisotropy of the Cosmic Microwave Background (CMB) temperature is believed to probe the primordial metric perturbations from inflation. Although the perturbations from inflation are expected to be gaussian random fields, there remains the possibility that nonlinear processes at later epochs induce ``secondary'' non-gaussian features in the corresponding CMB anisotropy maps. The non-gaussianity induced by nonlinear gravitational instability of scalar (density) perturbations has been investigated in existing literature. In this paper, we highlight another source of non-gaussianity arising out of higher order scattering of CMB photons off the metric perturbations. We provide a simple and elegant formalism for deriving the CMB temperature fluctuations arising due to the Sachs-Wolfe effect beyond the linear order. In particular, we derive the expression for the second order CMB temperature fluctuations. The multiple scattering effect pointed out in this paper leads to the possibility that tensor metric perturbation, i.e., gravity waves (GW) which do not exhibit gravitational instability can still contribute to the skewness in the CMB anisotropy maps. We find that in a flat $\Omega =1$ universe, the skewness in CMB contributed by gravity waves via multiple scattering effect is comparable to that from the gravitational instability of scalar perturbations for equal contribution of the gravity waves and scalar perturbations to the total rms CMB anisotropy. The secondary skewness is found to be smaller than the cosmic variance leading to the conclusion that inflationary scenarios do predict that the observed CMB anisotropy should be statistically consistent with a gaussian random distribution.
Bharadwaj Somnath
Munshi Dipak
Souradeep Tarun
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