Publication:

Mod-poisson convergence in probability and number theory

Date

Date

Date
2010
Journal Article
Published version

Citations

Citation copied

Kowalski, E., & Nikeghbali, A. (2010). Mod-poisson convergence in probability and number theory. International Mathematics Research Notices, 2010(18), 3549–3587. https://doi.org/10.1093/imrn/rnq019

Abstract

Abstract

Abstract

Building on earlier work introducing the notion of “mod-Gaussian” convergence of sequences of random variables, which arises naturally in Random Matrix Theory and number theory, we discuss the analogue notion of “mod-Poisson” convergence. We show in particular how it occurs naturally in analytic number theory in the classical Erdős– Kac Theorem. In fact, this case reveals deep connections and analogies with conjectures concerning the distribution of L functions on the critical line, which belong to the mod-Gaussian framework, and with

Additional indexing

Creators (Authors)

  • Kowalski, E
    affiliation.icon.alt
  • Nikeghbali, A
    affiliation.icon.alt

Journal/Series Title

Journal/Series Title

Journal/Series Title

Volume

Volume

Volume
2010

Number

Number

Number
18

Page range/Item number

Page range/Item number

Page range/Item number
3549

Page end

Page end

Page end
3587

Item Type

Item Type

Item Type
Journal Article

Dewey Decimal Classifikation

Dewey Decimal Classifikation

Dewey Decimal Classifikation

Language

Language

Language
English

Publication date

Publication date

Publication date
2010

Date available

Date available

Date available
2011-05-02

Publisher

Publisher

Publisher

ISSN or e-ISSN

ISSN or e-ISSN

ISSN or e-ISSN
1073-7928

OA Status

OA Status

OA Status
Green

Citations

Citation copied

Kowalski, E., & Nikeghbali, A. (2010). Mod-poisson convergence in probability and number theory. International Mathematics Research Notices, 2010(18), 3549–3587. https://doi.org/10.1093/imrn/rnq019

Green Open Access
Loading...
Thumbnail Image

Files

Files

Files
Files available to download:1

Files

Files

Files
Files available to download:1
Loading...
Thumbnail Image