The divisible sandpile with heavy-tailed variables

Alessandra Cipriani; Rajat Hazra; W.M. Ruszel

doi:10.1016/j.spa.2017.10.013

The divisible sandpile with heavy-tailed variables

Alessandra Cipriani
, Rajat Hazra
, W.M. Ruszel

Indian Institute of Science Education and Research, Kolkata
Delft University of Technology

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

This work deals with the divisible sandpile model when an initial configuration sampled from a heavy-tailed distribution. Extending results of Levine et al. (2015) and Cipriani et al. (2016) we determine sufficient conditions for stabilization and non-stabilization on infinite graphs. We determine furthermore that the scaling limit of the odometer on the torus is an α-stable random distribution.

Original language	English
Pages (from-to)	3054-3081
Number of pages	28
Journal	Stochastic Processes and their Applications
Volume	128
Issue number	9
DOIs	https://doi.org/10.1016/j.spa.2017.10.013
Publication status	Published - 2018
Externally published	Yes

Keywords

Divisible sandpile
Heavy-tailed variables
α-stable random distribution

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10.1016/j.spa.2017.10.013

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title = "The divisible sandpile with heavy-tailed variables",

abstract = "This work deals with the divisible sandpile model when an initial configuration sampled from a heavy-tailed distribution. Extending results of Levine et al. (2015) and Cipriani et al. (2016) we determine sufficient conditions for stabilization and non-stabilization on infinite graphs. We determine furthermore that the scaling limit of the odometer on the torus is an α-stable random distribution.",

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author = "Alessandra Cipriani and Rajat Hazra and W.M. Ruszel",

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AU - Cipriani, Alessandra

AU - Hazra, Rajat

AU - Ruszel, W.M.

PY - 2018

Y1 - 2018

N2 - This work deals with the divisible sandpile model when an initial configuration sampled from a heavy-tailed distribution. Extending results of Levine et al. (2015) and Cipriani et al. (2016) we determine sufficient conditions for stabilization and non-stabilization on infinite graphs. We determine furthermore that the scaling limit of the odometer on the torus is an α-stable random distribution.

AB - This work deals with the divisible sandpile model when an initial configuration sampled from a heavy-tailed distribution. Extending results of Levine et al. (2015) and Cipriani et al. (2016) we determine sufficient conditions for stabilization and non-stabilization on infinite graphs. We determine furthermore that the scaling limit of the odometer on the torus is an α-stable random distribution.

KW - Divisible sandpile

KW - Heavy-tailed variables

KW - α-stable random distribution

U2 - 10.1016/j.spa.2017.10.013

DO - 10.1016/j.spa.2017.10.013

M3 - Article

SN - 0304-4149

VL - 128

SP - 3054

EP - 3081

JO - Stochastic Processes and their Applications

JF - Stochastic Processes and their Applications

IS - 9

ER -

The divisible sandpile with heavy-tailed variables

Abstract

Keywords

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