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Quaternionic representations of Coxeter (reflection) groups of ranks 3 and 4, as well as those of E_8, have been used extensively in the literature. The present paper analyses such Coxeter groups in the Clifford Geometric Algebra framework,…

Mathematical Physics · Physics 2013-07-26 Pierre-Philippe Dechant

Real physical systems with reflective and rotational symmetries such as viruses, fullerenes and quasicrystals have recently been modeled successfully in terms of three-dimensional (affine) Coxeter groups. Motivated by this progress, we…

Mathematical Physics · Physics 2016-07-13 Pierre-Philippe Dechant

In this paper, we make the case that Clifford algebra is the natural framework for root systems and reflection groups, as well as related groups such as the conformal and modular groups: The metric that exists on these spaces can always be…

Mathematical Physics · Physics 2016-02-22 Pierre-Philippe Dechant

This paper considers the geometry of $E_8$ from a Clifford point of view in three complementary ways. Firstly, in earlier work, I had shown how to construct the four-dimensional exceptional root systems from the 3D root systems using…

Representation Theory · Mathematics 2017-02-22 Pierre-Philippe Dechant

We discuss a Clifford algebra framework for discrete symmetry groups (such as reflection, Coxeter, conformal and modular groups), leading to a surprising number of new results. Clifford algebras allow for a particularly simple description…

Representation Theory · Mathematics 2018-10-12 Pierre-Philippe Dechant

In this paper we discuss reflection groups and root systems, in particular non-crystallographic ones, and a Clifford algebra framework for both these concepts. A review of historical as well as more recent work on viral capsid symmetries…

Mathematical Physics · Physics 2022-04-13 Pierre-Philippe Dechant

We introduce Clifford Group Equivariant Neural Networks: a novel approach for constructing $\mathrm{O}(n)$- and $\mathrm{E}(n)$-equivariant models. We identify and study the $\textit{Clifford group}$, a subgroup inside the Clifford algebra…

Machine Learning · Computer Science 2023-10-24 David Ruhe , Johannes Brandstetter , Patrick Forré

We study the algebra of complex polynomials which remain invariant under the action of the local Clifford group under conjugation. Within this algebra, we consider the linear spaces of homogeneous polynomials degree by degree and construct…

Quantum Physics · Physics 2009-11-10 Maarten Van den Nest , Jeroen Dehaene , Bart De Moor

Contemporary large models often exhibit behaviors suggesting the presence of low-level primitives that compose into modules with richer functionality, but these fundamental building blocks remain poorly understood. We investigate this…

Machine Learning · Computer Science 2026-02-16 Travis Pence , Daisuke Yamada , Vikas Singh

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

We propose models of quantum neural networks through Clifford algebras, which are capable of capturing geometric features of systems and to produce entanglement. Due to their representations in terms of Pauli matrices, the Clifford algebras…

Quantum Physics · Physics 2022-06-07 Marco A. S. Trindade , Vinicius N. L. Rocha , S. Floquet

This paper introduces Lie groups in degenerate geometric (Clifford) algebras that preserve four fundamental subspaces determined by the grade involution and reversion under the adjoint and twisted adjoint representations. We prove that…

Rings and Algebras · Mathematics 2026-01-13 E. R. Filimoshina , D. S. Shirokov

This paper investigates centralizers and twisted centralizers in degenerate and non-degenerate Clifford (geometric) algebras. We provide an explicit form of the centralizers and twisted centralizers of the subspaces of fixed grades,…

Rings and Algebras · Mathematics 2024-12-24 E. R. Filimoshina , D. S. Shirokov

Clifford Group Equivariant Neural Networks (CGENNs) leverage Clifford algebras and multivectors as an alternative approach to incorporating group equivariance to ensure symmetry constraints in neural representations. In principle, this…

Machine Learning · Computer Science 2025-06-11 Riccardo Ali , Paulina Kulytė , Haitz Sáez de Ocáriz Borde , Pietro Liò

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

This paper explores the representation of quantum computing in terms of unitary reflections (unitary transformations that leave invariant a hyperplane of a vector space). The symmetries of qubit systems are found to be supported by…

Quantum Physics · Physics 2010-08-23 Michel Planat , Maurice R. Kibler

We introduce the Non-commutative Subset Convolution - a convolution of functions useful when working with determinant-based algorithms. In order to compute it efficiently, we take advantage of Clifford algebras, a generalization of…

Data Structures and Algorithms · Computer Science 2018-08-13 Michał Włodarczyk

Recently, there has been an increasing interest in the study of hypercomplex signals and their Fourier transforms. This paper aims to study such integral transforms from general principles, using 4 different yet equivalent definitions of…

Classical Analysis and ODEs · Mathematics 2011-01-11 H. De Bie , N. De Schepper , F. Sommen

Some connections between quadratic forms over the field of two elements, Clifford algebras of quadratic forms over the real numbers, real graded division algebras, and twisted group algebras will be highlighted. This allows to revisit real…

Rings and Algebras · Mathematics 2020-02-28 Alberto Elduque , Adrián Rodrigo-Escudero

Partial differential equations (PDEs) see widespread use in sciences and engineering to describe simulation of physical processes as scalar and vector fields interacting and coevolving over time. Due to the computationally expensive nature…

Machine Learning · Computer Science 2023-03-06 Johannes Brandstetter , Rianne van den Berg , Max Welling , Jayesh K. Gupta
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