Determine the sharp dimension dependence of the trajectory-length bound

Determine the optimal dependence on the dimension d in the trajectory-length bound for exact Euclidean ball-proximal point trajectories, given that the lower-bound construction requires growth at least proportional to \(\sqrt d\) while the current upper bound has a larger dimension dependence.

Background

The paper proves that bounded self-contracted sequences in Rd\mathbb{R}^d have finite length, with an explicit upper-bound constant CdC_d whose dependence on dimension is large. For exact ball-proximal point iterations, this yields a constant-radius termination bound that is linear in the initial distance-to-solution ratio for each fixed dimension.

A polyhedral construction shows that the dimension dependence cannot be eliminated: the trajectory length and iteration count can scale quadratically in the distance-to-radius ratio as the dimension grows, and the relevant lower-bound constant must grow at least as d\sqrt d. The unresolved issue is to close the gap between this lower bound and the dimension dependence of the available upper bound.

References

Two sharpness questions remain open. The first concerns the dependence on dimension in the trajectory-length bound. \Cref{thm:hard} shows that the corresponding constant must grow at least as $\sqrt d$, while the upper bound in \Cref{lem:length} leaves a gap in its dependence on $d$.

— A Sharper Theory of Ball-Proximal Optimization: Convergence and Radius Selection  (2609.35147 - Richtárik et al., 28 Sep 2026) in Section 6, Discussion