### Abstract

In previous work Majda and McLaughlin, and Majda computed explicit expressions for the 2Nth moments of a passive scalar advected by a linear shear flow in the form of an integral over R_{N}. In this paper we first compute the asymptotics of these moments for large moment number. We are able to use this information about the large-N behavior of the moments, along with some basic facts about entire functions of finite order, to compute the asymptotics of the tails of the probability distribution function. We find that the probability distribution has Gaussian tails when the energy is concentrated in the largest scales. As the initial energy is moved to smaller and smaller scales we find that the tails of the distribution grow longer, and the distribution moves smoothly from Gaussian through exponential and "stretched exponential." We also show that the derivatives of the scalar are increasingly intermittent, in agreement with experimental observations, and relate the exponents of the scalar derivative to the exponents of the scalar.

Original language | English (US) |
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Pages (from-to) | 897-915 |

Number of pages | 19 |

Journal | Journal of Statistical Physics |

Volume | 98 |

Issue number | 3-4 |

DOIs | |

State | Published - Feb 2000 |

### Keywords

- Hamburger moment problem
- Passive scalar intermittency
- Turbulence

### ASJC Scopus subject areas

- Statistical and Nonlinear Physics
- Mathematical Physics

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## Cite this

*Journal of Statistical Physics*,

*98*(3-4), 897-915. https://doi.org/10.1023/a:1018639928526