Constrained dynamics for searching saddle points on general Riemannian manifolds

Fuente: arXiv
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Main Authors: Hu, Yukuan, Grazioli, Laura
Format: Preprint
Published: 2026
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author Hu, Yukuan
Grazioli, Laura
author_facet Hu, Yukuan
Grazioli, Laura
contents Finding constrained saddle points on Riemannian manifolds is significant for analyzing energy landscapes arising in physics and chemistry. Existing works have been limited to special manifolds that admit global regular level-set representations, excluding applications such as electronic excited-state calculations. In this paper, we develop a constrained saddle dynamics applicable to smooth functions on general Riemannian manifolds. Our dynamics is formulated compactly over the Grassmann bundle of the tangent bundle. By analyzing the Grassmann bundle geometry, we achieve universality via incorporating the second fundamental form, which captures variations of tangent spaces along the trajectory. We rigorously establish the local linear stability of the dynamics and the local linear convergence of the resulting algorithms. Remarkably, our analysis provides the first convergence guarantees for discretized saddle-search algorithms in manifold settings. Moreover, by respecting the intrinsic quotient structure, we remove unnecessary nondegeneracy assumptions on the eigenvalues of the Riemannian Hessian that are present in existing works. We also point out that locating saddle points can be more ill-conditioning than finding local minimizers, and requires using nonredundant parametrizations. Finally, numerical experiments on linear eigenvalue problems and electronic excited-state calculations showcase the effectiveness of the proposed algorithms and corroborate the established local theory.
format Preprint
id arxiv_https___arxiv_org_abs_2601_03931
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Constrained dynamics for searching saddle points on general Riemannian manifolds
Hu, Yukuan
Grazioli, Laura
Numerical Analysis
Optimization and Control
Chemical Physics
Computational Physics
Finding constrained saddle points on Riemannian manifolds is significant for analyzing energy landscapes arising in physics and chemistry. Existing works have been limited to special manifolds that admit global regular level-set representations, excluding applications such as electronic excited-state calculations. In this paper, we develop a constrained saddle dynamics applicable to smooth functions on general Riemannian manifolds. Our dynamics is formulated compactly over the Grassmann bundle of the tangent bundle. By analyzing the Grassmann bundle geometry, we achieve universality via incorporating the second fundamental form, which captures variations of tangent spaces along the trajectory. We rigorously establish the local linear stability of the dynamics and the local linear convergence of the resulting algorithms. Remarkably, our analysis provides the first convergence guarantees for discretized saddle-search algorithms in manifold settings. Moreover, by respecting the intrinsic quotient structure, we remove unnecessary nondegeneracy assumptions on the eigenvalues of the Riemannian Hessian that are present in existing works. We also point out that locating saddle points can be more ill-conditioning than finding local minimizers, and requires using nonredundant parametrizations. Finally, numerical experiments on linear eigenvalue problems and electronic excited-state calculations showcase the effectiveness of the proposed algorithms and corroborate the established local theory.
title Constrained dynamics for searching saddle points on general Riemannian manifolds
topic Numerical Analysis
Optimization and Control
Chemical Physics
Computational Physics
url https://arxiv.org/abs/2601.03931