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1. Distributed Consensus on Manifolds using the Riemannian Center of Mass

   Spencer Kraisler, Shahriar Talebi (July 2023, Control Technology and Applications)

   In this paper, we develop a distributed consensus algorithm for agents whose states evolve on a manifold. This algorithm is complementary to traditional consensus, predominantly developed for systems with dynamics on vector spaces. We provide theoretical convergence guarantees for the proposed manifold consensus provided that agents are initialized within a geodesically convex (g-convex) set. This required condition on initialization is not restrictive as g-convex sets may be comparatively “large” for relevant Riemannian manifolds. Our approach to manifold consensus builds upon the notion of Riemannian Center of Mass (RCM) and the intrinsic structure of the manifold to avoid projections in the ambient space. We first show that on a g-convex ball, all states coincide if and only if each agent’s state is the RCM of its neighbors’ states. This observation facilitates our convergence guarantee to the consensus submanifold. Finally, we provide simulation results that exemplify the linear convergence rate of the proposed algorithm and illustrates its statistical properties over randomly generated problem instances. 

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2. Total mean curvatures of Riemannian hypersurfaces

   https://doi.org/10.1515/ans-2022-0029  

   Ghomi, Mohammad; Spruck, Joel (January 2023, Advanced Nonlinear Studies)

   Abstract We obtain a comparison formula for integrals of mean curvatures of Riemannian hypersurfaces via Reilly’s identities. As applications, we derive several geometric inequalities for a convex hypersurface Γ \Gamma in a Cartan-Hadamard manifold M M . In particular, we show that the first mean curvature integral of a convex hypersurface γ \gamma nested inside Γ \Gamma cannot exceed that of Γ \Gamma , which leads to a sharp lower bound for the total first mean curvature of Γ \Gamma in terms of the volume it bounds in M M in dimension 3. This monotonicity property is extended to all mean curvature integrals when γ \gamma is parallel to Γ \Gamma , or M M has constant curvature. We also characterize hyperbolic balls as minimizers of the mean curvature integrals among balls with equal radii in Cartan-Hadamard manifolds. 

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3. First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces

   Michael I. Jordan; Tianyi Lin; Emmanouil V. Vlatakis-Gkaragkounis  (April 2023, Advances in neural information processing systems)

   From optimal transport to robust dimensionality reduction, a plethora of machine learning applications can be cast into the min-max optimization problems over Riemannian manifolds. Though many min-max algorithms have been analyzed in the Euclidean setting, it has proved elusive to translate these results to the Riemannian case. Zhang et al. [2022] have recently shown that geodesic convex concave Riemannian problems always admit saddle-point solutions. Inspired by this result, we study whether a performance gap between Riemannian and optimal Euclidean space convex-concave algorithms is necessary. We answer this question in the negative—we prove that the Riemannian corrected extragradient (RCEG) method achieves last-iterate convergence at a linear rate in the geodesically strongly-convex-concave case, matching the Euclidean result. Our results also extend to the stochastic or non-smooth case where RCEG and Riemanian gradient ascent descent (RGDA) achieve near-optimal convergence rates up to factors depending on curvature of the manifold. 

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4. Local version of Courant’s nodal domain theorem

   https://doi.org/10.4310/jdg/1707767334  

   Chanillo, Sagun; Logunov, Alexander; Malinnikova, Eugenia; Mangoubi, Dan (January 2024, Journal of Differential Geometry)

   Let (M,g) be a compact n-dimensional Riemannian manifold without boundary, where the metric g is C^1-smooth. Consider the sequence of eigenfunctions u_k of the Laplace operator on M. Let B be a ball on M. We prove that the number of nodal domains of u_k that intersect B is not greater than C_1Volume(B)k+C_2k^{(n-1)/n}, where C_1 and C_2 depend on (M,g) only. The problem of local bounds for the volume and for the number of nodal domains was raised by Donnelly and Fefferman, who also proposed an idea how one can prove such bounds. We combine their idea with two ingredients: the recent sharp Remez type inequality for eigenfunctions and the Landis type growth lemma in narrow domains. 

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5. Inverting the local geodesic ray transform of higher rank tensors

   https://doi.org/10.1088/1361-6420/ab1ace  

   de Hoop, Maarten V; Uhlmann, Gunther; Zhai, Jian (January 2018, Inverse Problems)

   Consider a Riemannian manifold in dimension n ≥ 3 with strictly convex boundary. We prove the local invertibility, up to potential fields, of the geodesic ray transform on tensor fields of rank four near a boundary point. This problem is closely related with elastic qP-wave tomography. Under the condition that the manifold can be foliated with a continuous family of strictly convex hypersurfaces, the local invertibility implies a global result. One can straightforwardly adapt the proof to show similar results for tensor fields of arbitrary rank. 

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