Improved stability of optimal traffic paths

TL;DR

This paper improves the understanding of the stability of optimal traffic paths in Euclidean spaces, extending known results to a broader range of flow intensity exponents and measures.

Contribution

It addresses an open problem by extending stability results for optimal traffic paths to a wider range of the parameter , specifically for  > 1 - 1/(d-1), in Euclidean spaces.

Findings

Stability of optimal traffic paths is proven for  > 1 - 1/(d-1).

Results apply to a large class of measures ^-, ^+ in -dimensional space.

Extends known stability results from  > 1 - 1/d to  > 1 - 1/(d-1).

Abstract

Models involving branched structures are employed to describe several supply-demand systems such as the structure of the nerves of a leaf, the system of roots of a tree and the nervous or cardiovascular systems. Given a flow (traffic path) that transports a given measure $\mu^-$ onto a target measure $\mu^+$, along a 1-dimensional network, the transportation cost per unit length is supposed in these models to be proportional to a concave power $\alpha \in (0,1)$ of the intensity of the flow. In this paper we address an open problem in the book "Optimal transportation networks" by Bernot, Caselles and Morel and we improve the stability for optimal traffic paths in the Euclidean space $\mathbb{R}^d$, with respect to variations of the given measures $(\mu^-,\mu^+)$, which was known up to now only for $\alpha>1-\frac1d$. We prove it for exponents $\alpha>1-\frac1{d-1}$ (in particular, for every $\alpha \in (0,1)$ when $d=2$), for a fairly large class of measures $\mu^+$ and $\mu^-$.