Search arXiv⌕ Search

arXiv · 2609.40017

On Lorentzian Lie groups of Nonzero Constant Curvature

Abstract

We investigate Lie groups endowed with left-invariant Lorentzian metrics of nonzero constant sectional curvature. We first revisit Heintze's theory and obtain a characterization of the Lie algebras of Riemannian Lie groups of negative constant curvature. We also extend classical results of Nomizu and Barnet to the pseudo-Riemannian setting by constructing a large family of Lie groups carrying incomplete left-invariant metrics of constant sectional curvature. We then describe Lorentzian Lie algebras of nonzero constant curvature according to the causal nature of their center and derived ideal. This description is complete except when the derived ideal is Lorentzian, for which we obtain a complete classification in dimension four. We show that every left-invariant Lorentzian metric of nonzero constant curvature on \(\mathrm{SL}(2,\mathbb R)\) is bi-invariant and complete. Moreover, a semisimple Lie group admits a complete left-invariant Lorentzian metric of nonzero constant curvature if and only if it is locally isomorphic to \(\mathrm{SL}(2,\mathbb R)\). We also characterize \(\mathrm{SL}(2,\mathbb R)\) through the existence of a noncentral spacelike left-invariant Killing vector field. Finally, we classify Lorentzian Lie algebras of nonzero constant curvature in dimensions at most four.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Mohamed Boucetta. 2026-09-30. On Lorentzian Lie groups of Nonzero Constant Curvature. https://arxiv.org/abs/2609.40017

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

A duality theorem for a four dimensional Willmore energy

We prove an analogue of the energy identities underlying Bryant's duality theorem for a four-dimensional Willmore energy $\mathcal{E}_{\rm GR}$ obtained by Graham--Reichert and Zhang in codimension one. We show that, for an immersion $Φ$ of a compact four-dimensional manifold without boundary $Σ$ into $\mathbb{R}^5$, the energy $\mathcal{E}_{\rm GR}(Φ)$ is equal to two energies associated with its conformal Gauss map $Y$: one defined only in terms of the image of $Y$, which is the analogue of the area functional for Willmore surfaces, and another defined on maps from $Σ$ into the de Sitter space $\mathbb{S}^{5,1}$, which is the analogue of the Dirichlet energy for Willmore surfaces. We prove that, even when restricted to immersions of a given topological manifold $Σ^4$, $\mathcal{E}_{\rm GR}$ is not bounded below on the set of immersions from $Σ$ into $\mathbb{R}^5$. We exhibit a second conformally invariant energy $\mathcal{E}_{\rm P}$ that is bounded below and whose construction is closer to that of the two-dimensional Willmore energy.

math.DG↗

Barycentric subspace analysis of network-valued data

Certain data are naturally modeled by networks or weighted graphs, be they biological networks or mobility networks. When there is no canonical labeling of the nodes across the dataset, we talk about unlabeled networks. In this paper, we focus on the question of exploratory analysis of this type of data. More specifically, we address the issue of interpreting the feature subspace constructed by dimensionality reduction methods. Most existing methods for network-valued data are derived from principal component analysis (PCA) and therefore rely on subspaces generated by a set of vectors, which we identify as a major limitation in terms of interpretability. Instead, we propose to implement the method called barycentric subspace analysis (BSA), which relies on subspaces generated by a set of points, which we choose, in practice, to be samples. In order to provide a computationally feasible framework for BSA, we introduce a novel embedding for unlabeled networks where we replace their usual representation by equivalence classes of isomorphic networks with that by equivalence classes of cospectral networks. In a simulated study, we demonstrate the improved interpretability of BSA compared to tangent PCA. We then illustrate through two real-world datasets how BSA can be used both to visualize known patterns and to discover new ones in network-valued distributions.

math.DG↗

Isoparametric Hypersurfaces in Products of Simply Connected Space Forms

For $i\in\{1,2\}, $ let $\mathbb Q_{ε_i}^{n_i}$ denote the simply connected space form of dimension $n_i\ge 2$ and constant sectional curvature $ε_i\in\mathbb R$, $(ε_1,ε_2)\ne (0,0)$. We prove that any connected isoparametric hypersurface of $\mathbb Q_{ε_1}^{n_1}\times\mathbb Q_{ε_2}^{n_2}$ has constant angle function. We use this property to classify both the isoparametric and homogeneous hypersurfaces of $\mathbb Q_{ε_1}^{n_1}\times\mathbb Q_{ε_2}^{n_2}$ when $ε_1ε_2\le 0$. Under additional hypotheses, we obtain a similar classification result in the case $ε_1ε_2>0$.

math.DG↗