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Related papers: Clifford Group Equivariant Neural Networks

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While the Clifford (geometric) algebra Fourier Transform (CFT) is global, we introduce here the local Clifford (geometric) algebra (GA) wavelet concept. We show how for $n=2,3 (\mod 4)$ continuous $Cl_n$-valued admissible wavelets can be…

Rings and Algebras · Mathematics 2013-06-10 Eckhard Hitzer

Clifford algebras are naturally associated with quadratic forms. These algebras are Z_2-graded by construction. However, only a Z_n-gradation induced by a choice of a basis, or even better, by a Chevalley vector space isomorphism Cl(V) <->…

Quantum Algebra · Mathematics 2007-05-23 Bertfried Fauser , Rafal Ablamowicz

Symmetries and equivariance are fundamental to the generalization of neural networks on domains such as images, graphs, and point clouds. Existing work has primarily focused on a small number of groups, such as the translation, rotation,…

Machine Learning · Computer Science 2021-04-20 Marc Finzi , Max Welling , Andrew Gordon Wilson

The Clifford group plays a central role in quantum information science. It is the building block for many error-correcting schemes and matches the first three moments of the Haar measure over the unitary group -a property that is essential…

Quantum Physics · Physics 2025-04-17 Lennart Bittel , Jens Eisert , Lorenzo Leone , Antonio A. Mele , Salvatore F. E. Oliviero

We describe stabilizer states and Clifford group operations using linear operations and quadratic forms over binary vector spaces. We show how the n-qubit Clifford group is isomorphic to a group with an operation that is defined in terms of…

Quantum Physics · Physics 2009-11-10 Jeroen Dehaene , Bart De Moor

Nebe, Rains and Sloane studied the polynomial invariants for real and complex Clifford groups and they relate the invariants to the space of complete weight enumerators of certain self-dual codes. The purpose of this paper is to show that…

Combinatorics · Mathematics 2020-06-02 Eiichi Bannai , Manabu Oura , Da Zhao

Recent work has constructed neural networks that are equivariant to continuous symmetry groups such as 2D and 3D rotations. This is accomplished using explicit Lie group representations to derive the equivariant kernels and nonlinearities.…

Machine Learning · Computer Science 2022-12-08 Noah Shutty , Casimir Wierzynski

Group equivariance (e.g. SE(3) equivariance) is a critical physical symmetry in science, from classical and quantum physics to computational biology. It enables robust and accurate prediction under arbitrary reference transformations. In…

Computational Engineering, Finance, and Science · Computer Science 2023-02-08 Weitao Du , He Zhang , Yuanqi Du , Qi Meng , Wei Chen , Bin Shao , Tie-Yan Liu

The Symmetric group $S_{n}$ manifests itself in large classes of quantum systems as the invariance of certain characteristics of a quantum state with respect to permuting the qubits. The subgroups of $S_{n}$ arise, among many other…

Quantum Physics · Physics 2024-11-19 Sreetama Das , Filippo Caruso

Reductive Lie Groups, such as the orthogonal groups, the Lorentz group, or the unitary groups, play essential roles across scientific fields as diverse as high energy physics, quantum mechanics, quantum chromodynamics, molecular dynamics,…

Machine Learning · Statistics 2023-06-02 Ilyes Batatia , Mario Geiger , Jose Munoz , Tess Smidt , Lior Silberman , Christoph Ortner

The geometric calculus based on Clifford algebra is a very useful tool for geometry and physics. It describes a geometric structure which is much richer than the ordinary geometry of spacetime. A Clifford manifold (C-space) consists not…

General Relativity and Quantum Cosmology · Physics 2011-08-17 Matej Pavsic

We present a novel application of category theory for deep learning. We show how category theory can be used to understand and work with the linear layer functions of group equivariant neural networks whose layers are some tensor power…

Machine Learning · Computer Science 2023-04-28 Edward Pearce-Crump

We recall the notions of Clifford and Clifford-like parallelisms in a $3$-dimensional projective double space. In a previous paper the authors proved that the linear part of the full automorphism group of a Clifford parallelism is the same…

Algebraic Geometry · Mathematics 2024-02-02 Hans Havlicek , Stefano Pasotti , Silvia Pianta

One particular approach to quantum groups (matrix pseudo groups) provides the Manin quantum plane. Assuming an appropriate set of non-commuting variables spanning linearly a representation space one is able to show that the endomorphisms on…

Quantum Algebra · Mathematics 2009-10-31 Bertfried Fauser

The power of Clifford or, geometric, algebra lies in its ability to represent geometric operations in a concise and elegant manner. Clifford algebras provide the natural generalizations of complex, dual numbers and quaternions into…

Numerical Analysis · Mathematics 2023-08-07 Dimiter Prodanov

In this study, we introduce a method for learning group (known or unknown) equivariant functions by learning the associated quadratic form $x^T A x$ corresponding to the group from the data. Certain groups, known as orthogonal groups,…

Machine Learning · Computer Science 2025-10-16 Pavan Karjol , Vivek V Kashyap , Rohan Kashyap , Prathosh A P

Based on a fact that complex Clifford algebras of even dimension are isomorphic to the matrix ones, we consider bundles in Clifford algebras whose structure group is a general linear group acting on a Clifford algebra by left…

Mathematical Physics · Physics 2016-02-12 G. Sardanashvily , A. Yarygin

In this article we construct a cochain complex of a complex Clifford algebra with coefficients in itself in a combinatorial fashion and we call the corresponding cohomology by {\it Clifford cohomology.} We show that {\it Clifford…

Algebraic Topology · Mathematics 2022-12-19 Bikram Banerjee , Goutam Mukherjee

This paper proposes an equivariant neural network that takes data in any semi-simple Lie algebra as input. The corresponding group acts on the Lie algebra as adjoint operations, making our proposed network adjoint-equivariant. Our framework…

Machine Learning · Computer Science 2024-06-10 Tzu-Yuan Lin , Minghan Zhu , Maani Ghaffari

In this paper, we utilize hyperspheres and regular $n$-simplexes and propose an approach to learning deep features equivariant under the transformations of $n$D reflections and rotations, encompassed by the powerful group of O$(n)$. Namely,…

Machine Learning · Computer Science 2024-05-31 Pavlo Melnyk , Michael Felsberg , Mårten Wadenbäck , Andreas Robinson , Cuong Le