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We show that for every symmetric space G/K of compact type with K connected, the K-action on G/K by left translations is equivariantly formal.

Differential Geometry · Mathematics 2012-03-01 Oliver Goertsches

In this note we prove the following theorem: Let $G$ be a compact Lie group acting on a compact symplectic manifold $M$ in a Hamiltonian fashion. If $L$ is an $l$-dimensional closed invariant submanifold of $M$, on which the $G$-action is…

Symplectic Geometry · Mathematics 2007-05-23 Yildiray Ozan

Fix a scheme $X$ over a field of characteristic zero that is equipped with an action of a reductive algebraic group $G$. We give necessary and sufficient conditions for a $G$-equivariant coherent sheaf on $X$ or a bounded-above complex of…

Algebraic Geometry · Mathematics 2008-04-21 Thomas Nevins

When the action of a reductive group on a projective variety has a suitable linearisation, Mumford's geometric invariant theory (GIT) can be used to construct and study an associated quotient variety. In this article we describe how…

Algebraic Geometry · Mathematics 2017-03-16 Gergely Bérczi , Brent Doran , Frances Kirwan

We consider the action of a finite subgroup of the mapping class group $Mod(S)$ of an oriented compact surface $S$ of genus $g \geq 2$ on the moduli space $\mathcal{R}(S,G)$ of representations of $\pi_1(S)$ in a connected semisimple real…

Algebraic Geometry · Mathematics 2020-07-01 Oscar Garcia-Prada , Graeme Wilkin

Let a differential 4D-manifold with a smooth coframe field be given. Consider the operators on it that are linear in the second order derivatives or quadratic in the first order derivatives of the coframe, both with coefficients that depend…

General Relativity and Quantum Cosmology · Physics 2015-06-25 Yakov Itin , Shmuel Kaniel

Incorporating equivariance to symmetry groups as a constraint during neural network training can improve performance and generalization for tasks exhibiting those symmetries, but such symmetries are often not perfectly nor explicitly…

Machine Learning · Computer Science 2023-02-09 Kaitlin Maile , Dennis G. Wilson , Patrick Forré

Let G be a locally compact group, let X be a universal proper G-space, and let Z be a G-equivariant compactification of X that is H-equivariantly contractible for each compact subgroup H of G. Let W be the resulting boundary. Assuming the…

K-Theory and Homology · Mathematics 2015-10-23 Heath Emerson , Ralf Meyer

This paper presents a differential geometric control approach that leverages SE(3) group invariance and equivariance to increase transferability in learning robot manipulation tasks that involve interaction with the environment.…

The idea that the cohomology of finite groups might be fruitfully approached via the cohomology of ambient semisimple algebraic groups was first shown to be viable in the papers [CPS75] and [CPSvdK77]. The second paper introduced, through a…

Representation Theory · Mathematics 2012-05-08 Brian J. Parshall , Leonard L. Scott , David I. Stewart

Let $M$ be a compact, orientable, $n$-dimensional Riemannian manifold, $n\geq2$, and let $F$ be the energy functional acting on the space $\Xi (M)$ of $C^{\infty }$ vector fields of $M$, \[ F(X):=\frac{\int_{M}\left\Vert \nabla X\right\Vert…

Differential Geometry · Mathematics 2025-04-29 Giovanni da Silva Nunes , Jaime Ripoll

The smooth action of a compact Lie group on a compact manifold can be resolved to an iterated space, as made explicit by Pierre Albin and the second author. On the resolution the lifted action has fixed isotropy type corresponding to the…

K-Theory and Homology · Mathematics 2021-01-05 Panagiotis Dimakis , Richard Melrose

We propose a metric learning framework for the construction of invariant geometric functions of planar curves for the Eucledian and Similarity group of transformations. We leverage on the representational power of convolutional neural…

Computer Vision and Pattern Recognition · Computer Science 2017-02-20 Gautam Pai , Aaron Wetzler , Ron Kimmel

We introduce Group equivariant Convolutional Neural Networks (G-CNNs), a natural generalization of convolutional neural networks that reduces sample complexity by exploiting symmetries. G-CNNs use G-convolutions, a new type of layer that…

Machine Learning · Computer Science 2016-06-06 Taco S. Cohen , Max Welling

Let $G$ be a simple algebraic group of adjoint type over $\mathbb C$, and let $M$ be the wonderful compactification of a symmetric space $G/H$. Take a $\widetilde G$--equivariant principal $R$--bundle $E$ on $M$, where $R$ is a complex…

Algebraic Geometry · Mathematics 2015-01-13 Indranil Biswas , S. Senthamarai Kannan , D. S. Nagaraj

The group invariance of entanglement is obtained within a very general and simple setup of the latter, given by a recently introduced considerably extended concept of tensor products. This general approach to entanglement - unlike the usual…

General Mathematics · Mathematics 2008-08-04 Elemer E Rosinger

Let $G$ be a subgroup of $S_6$, the symmetric group of degree 6. For any field $k$, $G$ acts naturally on the rational function field $k(x_1,...,x_6)$ via $k$-automorphisms defined by $\sigma\cdot x_i=x_{\sigma(i)}$ for any $\sigma\in G$,…

Algebraic Geometry · Mathematics 2015-11-03 Ming-chang Kang , Baoshan Wang , Jian Zhou

Let $G$ be a unimodular Lie group, $X$ a compact manifold with boundary, and $M$ the total space of a principal bundle $G\to M\to X$ so that $M$ is also a strongly pseudoconvex complex manifold. In this work, we show that if $G$ acts by…

Complex Variables · Mathematics 2009-12-17 Joe J. Perez

Let G = SL(n,R) (or, more generally, let G be a connected, noncompact, simple Lie group). For any compact Lie group K, it is easy to find a compact manifold M, such that there is a volume-preserving, connection-preserving, ergodic action of…

Differential Geometry · Mathematics 2007-05-23 Dave Witte , Robert J. Zimmer

This paper studies separating invariants: mappings on $D$ dimensional domains which are invariant to an appropriate group action, and which separate orbits. The motivation for this study comes from the usefulness of separating invariants in…

Machine Learning · Computer Science 2023-11-22 Nadav Dym , Steven J. Gortler
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