On the coming down from infinity of continuous-state branching processes with drift-interaction.

We study the phenomenon of coming down from infinity – that is, when the process starts from infinity and never returns to it – for continuous-state branching processes with generalized drift. We provide sufficient conditions on the drift term and the branching mechanism to ensure both non-explosion and coming down from infinity, without requir- ing the associated jump measure to have a finite first moment. Assuming the process comes down from infinity and the drift satisfies a one-sided Lipschitz condition, we show that, as the initial values tend to infinity, the process converges locally uniformly almost surely to the strong solution of a stochastic differential equation. The main techniques employed are comparison principles for solutions of stochastic equations and the method of Lyapunov functions, the latter being briefly reviewed in a broader setting.

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Publication Details

Journal
ESAIM Probability and Statistics
Published
2026-08-26
DOI
https://doi.org/10.1051/ps/2026014
Primary Topic
Stochastic processes and statistical mechanics
Type
article
Field-Weighted Citation Impact
0.00

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article

On the coming down from infinity of continuous-state branching processes with drift-interaction.

Félix Rebotier
ESAIM Probability and Statistics
Stochastic processes and statistical mechanics
article

On the coming down from infinity of continuous-state branching processes with drift-interaction.

Félix Rebotier
article en

Abstract

We study the phenomenon of coming down from infinity – that is, when the process starts from infinity and never returns to it – for continuous-state branching processes with generalized drift. We provide sufficient conditions on the drift term and the branching mechanism to ensure both non-explosion and coming down from infinity, without requir- ing the associated jump measure to have a finite first moment. Assuming the process comes down from infinity and the drift satisfies a one-sided Lipschitz condition, we show that, as the initial values tend to infinity, the process converges locally uniformly almost surely to the strong solution of a stochastic differential equation. The main techniques employed are comparison principles for solutions of stochastic equations and the method of Lyapunov functions, the latter being briefly reviewed in a broader setting.

ESAIM Probability and Statistics
HORIZON EUROPE European Research Council
Openalex Percentile: Top 91%
Stochastic processes and statistical mechanics
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