1999
DOI: 10.1046/j.1365-8711.1999.02951.x
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Higher order moments of the density field in a parametrized sequence of non-Gaussian theories

Abstract: We calculate the higher order moments in a sequence of models where the initial density fluctuations are drawn from a distribution with a power‐law power spectrum. For large values of ν, the distribution is approximately Gaussian, and we reproduce the values known from perturbation theory. As ν is lowered the distribution becomes progressively more non‐Gaussian, approximating models with rare, high‐amplitude peaks. The limit ν=1 is a realization of recently proposed isocurvature models for producing early g… Show more

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Cited by 23 publications
(24 citation statements)
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“…In addition, a number of studies considered the evolution of higher-order moments from non-Gaussian initial conditions given by cosmic strings [146,9] and texture models [252] using numerical simulations. Recently, measurements of higherorder moments in numerical simulations with χ 2 N initial conditions with N degrees of freedom were given in [689]. General properties of one-point moments evolved from non-Gaussian initial conditions were considered using PT in [238,333,124,255,195].…”
Section: Evolution From Non-gaussian Initial Conditionsmentioning
confidence: 99%
“…In addition, a number of studies considered the evolution of higher-order moments from non-Gaussian initial conditions given by cosmic strings [146,9] and texture models [252] using numerical simulations. Recently, measurements of higherorder moments in numerical simulations with χ 2 N initial conditions with N degrees of freedom were given in [689]. General properties of one-point moments evolved from non-Gaussian initial conditions were considered using PT in [238,333,124,255,195].…”
Section: Evolution From Non-gaussian Initial Conditionsmentioning
confidence: 99%
“…We assume, using the arguments of Refs. [41][42][43] (see also Ref. [39]), that PDF of the smoothed ζ field can be expressed in the form…”
Section: Pbh Constraintsmentioning
confidence: 99%
“…The chi-squared distribution has the added attractive feature that the reduced PDF remains approximately the same when smoothed on a variety of length-scales using either Gaussian (GAU) or top-hat (TH) windows (e.g. White 1999). The reduced PDF that results from the smoothing becomes increasingly different from the original as the number of degrees of freedom, n, gets smaller.…”
Section: R E S U Lt Smentioning
confidence: 99%