Geometric Algebra and Its Application to Mathematical Physics
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Geometric Algebra for Vector Fields Analysis and Visualization: Mathematical Settings, Overview and Applications Chantal Oberson Ausoni, Pascal Frey
Geometric algebra for vector fields analysis and visualization: mathematical settings, overview and applications Chantal Oberson Ausoni, Pascal Frey To cite this version: Chantal Oberson Ausoni, Pascal Frey. Geometric algebra for vector fields analysis and visualization: mathematical settings, overview and applications. 2014. hal-00920544v2 HAL Id: hal-00920544 https://hal.sorbonne-universite.fr/hal-00920544v2 Preprint submitted on 18 Sep 2014 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Geometric algebra for vector field analysis and visualization: mathematical settings, overview and applications Chantal Oberson Ausoni and Pascal Frey Abstract The formal language of Clifford’s algebras is attracting an increasingly large community of mathematicians, physicists and software developers seduced by the conciseness and the efficiency of this compelling system of mathematics. This contribution will suggest how these concepts can be used to serve the purpose of scientific visualization and more specifically to reveal the general structure of complex vector fields. We will emphasize the elegance and the ubiquitous nature of the geometric algebra approach, as well as point out the computational issues at stake. 1 Introduction Nowadays, complex numerical simulations (e.g. in climate modelling, weather fore- cast, aeronautics, genomics, etc.) produce very large data sets, often several ter- abytes, that become almost impossible to process in a reasonable amount of time. -
Exploring Physics with Geometric Algebra, Book II., , C December 2016 COPYRIGHT
peeter joot [email protected] EXPLORINGPHYSICSWITHGEOMETRICALGEBRA,BOOKII. EXPLORINGPHYSICSWITHGEOMETRICALGEBRA,BOOKII. peeter joot [email protected] December 2016 – version v.1.3 Peeter Joot [email protected]: Exploring physics with Geometric Algebra, Book II., , c December 2016 COPYRIGHT Copyright c 2016 Peeter Joot All Rights Reserved This book may be reproduced and distributed in whole or in part, without fee, subject to the following conditions: • The copyright notice above and this permission notice must be preserved complete on all complete or partial copies. • Any translation or derived work must be approved by the author in writing before distri- bution. • If you distribute this work in part, instructions for obtaining the complete version of this document must be included, and a means for obtaining a complete version provided. • Small portions may be reproduced as illustrations for reviews or quotes in other works without this permission notice if proper citation is given. Exceptions to these rules may be granted for academic purposes: Write to the author and ask. Disclaimer: I confess to violating somebody’s copyright when I copied this copyright state- ment. v DOCUMENTVERSION Version 0.6465 Sources for this notes compilation can be found in the github repository https://github.com/peeterjoot/physicsplay The last commit (Dec/5/2016), associated with this pdf was 595cc0ba1748328b765c9dea0767b85311a26b3d vii Dedicated to: Aurora and Lance, my awesome kids, and Sofia, who not only tolerates and encourages my studies, but is also awesome enough to think that math is sexy. PREFACE This is an exploratory collection of notes containing worked examples of more advanced appli- cations of Geometric Algebra (GA), also known as Clifford Algebra. -
An Algorithmic Approach to Operator Product Expansions, W-Algebras
Katholieke Universiteit Leuven Faculteit Wetenschappen Instituut voor Theoretische Fysica An Algorithmic Approach to Operator Product Expansions, -Algebras and -Strings W W Promotor: Dr. W. Troost Proefschrift ingediend tot het behalen van de graad van Doctor in de Wetenschappen door Kris Thielemans Leuven, juni 1994. arXiv:hep-th/9506159v1 23 Jun 1995 Jun 23 arXiv:hep-th/9506159v1 Notations ¯ d d Abstract ∂, ∂ : dz , dz¯. δ : infinitesimal transformation with ε(x) an infinitesimal parameter. String theory is currently the most promising theory to explain ε the spectrum of the elementary particles and their interactions. : T1T2 : : normal ordening. One of its most important features is its large symmetry group, which contains the conformal transformations in two dimensions OPA : Operator Product Algebra, subsection 2.3.3. as a subgroup. At quantum level, the symmetry group of a theory OPE : Operator Product Expansions, section 2.3. gives rise to differential equations between correlation functions of observables. We show that these Ward-identities are equiva- [T1(z)T2(z0)] : the complete OPE. lent to Operator Product Expansions (OPEs), which encode the T1(z)T2(z0) : singular part of an OPE. short-distance singularities of correlation functions with symme- try generators. The OPEs allow us to determine algebraically −n [T1T2]n : coefficient of (z z0) in the OPE [T1(z)T2(z0)], eq. (2.3.3). many properties of the theory under study. We analyse the calcu- − << c 0 2T ∂T >> : list of the operators at the singular poles in an OPE. High- lational rules for OPEs, give an algorithm to compute OPEs, and 2 | | | discuss an implementation in Mathematica. -
Multivector Differentiation and Linear Algebra 0.5Cm 17Th Santaló
Multivector differentiation and Linear Algebra 17th Santalo´ Summer School 2016, Santander Joan Lasenby Signal Processing Group, Engineering Department, Cambridge, UK and Trinity College Cambridge [email protected], www-sigproc.eng.cam.ac.uk/ s jl 23 August 2016 1 / 78 Examples of differentiation wrt multivectors. Linear Algebra: matrices and tensors as linear functions mapping between elements of the algebra. Functional Differentiation: very briefly... Summary Overview The Multivector Derivative. 2 / 78 Linear Algebra: matrices and tensors as linear functions mapping between elements of the algebra. Functional Differentiation: very briefly... Summary Overview The Multivector Derivative. Examples of differentiation wrt multivectors. 3 / 78 Functional Differentiation: very briefly... Summary Overview The Multivector Derivative. Examples of differentiation wrt multivectors. Linear Algebra: matrices and tensors as linear functions mapping between elements of the algebra. 4 / 78 Summary Overview The Multivector Derivative. Examples of differentiation wrt multivectors. Linear Algebra: matrices and tensors as linear functions mapping between elements of the algebra. Functional Differentiation: very briefly... 5 / 78 Overview The Multivector Derivative. Examples of differentiation wrt multivectors. Linear Algebra: matrices and tensors as linear functions mapping between elements of the algebra. Functional Differentiation: very briefly... Summary 6 / 78 We now want to generalise this idea to enable us to find the derivative of F(X), in the A ‘direction’ – where X is a general mixed grade multivector (so F(X) is a general multivector valued function of X). Let us use ∗ to denote taking the scalar part, ie P ∗ Q ≡ hPQi. Then, provided A has same grades as X, it makes sense to define: F(X + tA) − F(X) A ∗ ¶XF(X) = lim t!0 t The Multivector Derivative Recall our definition of the directional derivative in the a direction F(x + ea) − F(x) a·r F(x) = lim e!0 e 7 / 78 Let us use ∗ to denote taking the scalar part, ie P ∗ Q ≡ hPQi. -
Geometric-Algebra Adaptive Filters Wilder B
1 Geometric-Algebra Adaptive Filters Wilder B. Lopes∗, Member, IEEE, Cassio G. Lopesy, Senior Member, IEEE Abstract—This paper presents a new class of adaptive filters, namely Geometric-Algebra Adaptive Filters (GAAFs). They are Faces generated by formulating the underlying minimization problem (a deterministic cost function) from the perspective of Geometric Algebra (GA), a comprehensive mathematical language well- Edges suited for the description of geometric transformations. Also, (directed lines) differently from standard adaptive-filtering theory, Geometric Calculus (the extension of GA to differential calculus) allows Fig. 1. A polyhedron (3-dimensional polytope) can be completely described for applying the same derivation techniques regardless of the by the geometric multiplication of its edges (oriented lines, vectors), which type (subalgebra) of the data, i.e., real, complex numbers, generate the faces and hypersurfaces (in the case of a general n-dimensional quaternions, etc. Relying on those characteristics (among others), polytope). a deterministic quadratic cost function is posed, from which the GAAFs are devised, providing a generalization of regular adaptive filters to subalgebras of GA. From the obtained update rule, it is shown how to recover the following least-mean squares perform calculus with hypercomplex quantities, i.e., elements (LMS) adaptive filter variants: real-entries LMS, complex LMS, that generalize complex numbers for higher dimensions [2]– and quaternions LMS. Mean-square analysis and simulations in [10]. a system identification scenario are provided, showing very good agreement for different levels of measurement noise. GA-based AFs were first introduced in [11], [12], where they were successfully employed to estimate the geometric Index Terms—Adaptive filtering, geometric algebra, quater- transformation (rotation and translation) that aligns a pair of nions. -
Determinants in Geometric Algebra
Determinants in Geometric Algebra Eckhard Hitzer 16 June 2003, recovered+expanded May 2020 1 Definition Let f be a linear map1, of a real linear vector space Rn into itself, an endomor- phism n 0 n f : a 2 R ! a 2 R : (1) This map is extended by outermorphism (symbol f) to act linearly on multi- vectors f(a1 ^ a2 ::: ^ ak) = f(a1) ^ f(a2) ::: ^ f(ak); k ≤ n: (2) By definition f is grade-preserving and linear, mapping multivectors to mul- tivectors. Examples are the reflections, rotations and translations described earlier. The outermorphism of a product of two linear maps fg is the product of the outermorphisms f g f[g(a1)] ^ f[g(a2)] ::: ^ f[g(ak)] = f[g(a1) ^ g(a2) ::: ^ g(ak)] = f[g(a1 ^ a2 ::: ^ ak)]; (3) with k ≤ n. The square brackets can safely be omitted. The n{grade pseudoscalars of a geometric algebra are unique up to a scalar factor. This can be used to define the determinant2 of a linear map as det(f) = f(I)I−1 = f(I) ∗ I−1; and therefore f(I) = det(f)I: (4) For an orthonormal basis fe1; e2;:::; eng the unit pseudoscalar is I = e1e2 ::: en −1 q q n(n−1)=2 with inverse I = (−1) enen−1 ::: e1 = (−1) (−1) I, where q gives the number of basis vectors, that square to −1 (the linear space is then Rp;q). According to Grassmann n-grade vectors represent oriented volume elements of dimension n. The determinant therefore shows how these volumes change under linear maps. -
PBW Deformations of Artin-Schelter Regular Algebras and Their Omogeh Nizations Jason D
University of Wisconsin Milwaukee UWM Digital Commons Theses and Dissertations May 2013 PBW Deformations of Artin-Schelter Regular Algebras and Their omogeH nizations Jason D. Gaddis University of Wisconsin-Milwaukee Follow this and additional works at: https://dc.uwm.edu/etd Part of the Mathematics Commons Recommended Citation Gaddis, Jason D., "PBW Deformations of Artin-Schelter Regular Algebras and Their omoH genizations" (2013). Theses and Dissertations. 98. https://dc.uwm.edu/etd/98 This Dissertation is brought to you for free and open access by UWM Digital Commons. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of UWM Digital Commons. For more information, please contact [email protected]. PBW deformations of Artin-Schelter regular algebras and their homogenizations by Jason D. Gaddis A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Mathematics at The University of Wisconsin-Milwaukee May 2013 ABSTRACT PBW deformations of Artin-Schelter regular algebras and their homogenizations by Jason D. Gaddis The University of Wisconsin-Milwaukee, 2013 Under the Supervision of Professor Allen Bell A central object in the study of noncommutative projective geometry is the (Artin-Schelter) regular algebra, which may be considered as a noncommutative version of a polynomial ring. We extend these ideas to algebras which are not necessarily graded. In particular, we define an algebra to be essentially regular of dimension d if its homogenization is regular of dimension d + 1. Essentially regular algebras are described and it is shown that that they are equivalent to PBW deformations of regular algebras. -
Finite Projective Geometries 243
FINITE PROJECTÎVEGEOMETRIES* BY OSWALD VEBLEN and W. H. BUSSEY By means of such a generalized conception of geometry as is inevitably suggested by the recent and wide-spread researches in the foundations of that science, there is given in § 1 a definition of a class of tactical configurations which includes many well known configurations as well as many new ones. In § 2 there is developed a method for the construction of these configurations which is proved to furnish all configurations that satisfy the definition. In §§ 4-8 the configurations are shown to have a geometrical theory identical in most of its general theorems with ordinary projective geometry and thus to afford a treatment of finite linear group theory analogous to the ordinary theory of collineations. In § 9 reference is made to other definitions of some of the configurations included in the class defined in § 1. § 1. Synthetic definition. By a finite projective geometry is meant a set of elements which, for sugges- tiveness, are called points, subject to the following five conditions : I. The set contains a finite number ( > 2 ) of points. It contains subsets called lines, each of which contains at least three points. II. If A and B are distinct points, there is one and only one line that contains A and B. HI. If A, B, C are non-collinear points and if a line I contains a point D of the line AB and a point E of the line BC, but does not contain A, B, or C, then the line I contains a point F of the line CA (Fig. -
New Foundations for Geometric Algebra1
Text published in the electronic journal Clifford Analysis, Clifford Algebras and their Applications vol. 2, No. 3 (2013) pp. 193-211 New foundations for geometric algebra1 Ramon González Calvet Institut Pere Calders, Campus Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Spain E-mail : [email protected] Abstract. New foundations for geometric algebra are proposed based upon the existing isomorphisms between geometric and matrix algebras. Each geometric algebra always has a faithful real matrix representation with a periodicity of 8. On the other hand, each matrix algebra is always embedded in a geometric algebra of a convenient dimension. The geometric product is also isomorphic to the matrix product, and many vector transformations such as rotations, axial symmetries and Lorentz transformations can be written in a form isomorphic to a similarity transformation of matrices. We collect the idea Dirac applied to develop the relativistic electron equation when he took a basis of matrices for the geometric algebra instead of a basis of geometric vectors. Of course, this way of understanding the geometric algebra requires new definitions: the geometric vector space is defined as the algebraic subspace that generates the rest of the matrix algebra by addition and multiplication; isometries are simply defined as the similarity transformations of matrices as shown above, and finally the norm of any element of the geometric algebra is defined as the nth root of the determinant of its representative matrix of order n. The main idea of this proposal is an arithmetic point of view consisting of reversing the roles of matrix and geometric algebras in the sense that geometric algebra is a way of accessing, working and understanding the most fundamental conception of matrix algebra as the algebra of transformations of multiple quantities. -
Josiah Willard Gibbs
GENERAL ARTICLE Josiah Willard Gibbs V Kumaran The foundations of classical thermodynamics, as taught in V Kumaran is a professor textbooks today, were laid down in nearly complete form by of chemical engineering at the Indian Institute of Josiah Willard Gibbs more than a century ago. This article Science, Bangalore. His presentsaportraitofGibbs,aquietandmodestmanwhowas research interests include responsible for some of the most important advances in the statistical mechanics and history of science. fluid mechanics. Thermodynamics, the science of the interconversion of heat and work, originated from the necessity of designing efficient engines in the late 18th and early 19th centuries. Engines are machines that convert heat energy obtained by combustion of coal, wood or other types of fuel into useful work for running trains, ships, etc. The efficiency of an engine is determined by the amount of useful work obtained for a given amount of heat input. There are two laws related to the efficiency of an engine. The first law of thermodynamics states that heat and work are inter-convertible, and it is not possible to obtain more work than the amount of heat input into the machine. The formulation of this law can be traced back to the work of Leibniz, Dalton, Joule, Clausius, and a host of other scientists in the late 17th and early 18th century. The more subtle second law of thermodynamics states that it is not possible to convert all heat into work; all engines have to ‘waste’ some of the heat input by transferring it to a heat sink. The second law also established the minimum amount of heat that has to be wasted based on the absolute temperatures of the heat source and the heat sink. -
Notices of the American Mathematical Society 35 Monticello Place, Pawtucket, RI 02861 USA American Mathematical Society Distribution Center
ISSN 0002-9920 Notices of the American Mathematical Society 35 Monticello Place, Pawtucket, RI 02861 USA Society Distribution Center American Mathematical of the American Mathematical Society February 2012 Volume 59, Number 2 Conformal Mappings in Geometric Algebra Page 264 Infl uential Mathematicians: Birth, Education, and Affi liation Page 274 Supporting the Next Generation of “Stewards” in Mathematics Education Page 288 Lawrence Meeting Page 352 Volume 59, Number 2, Pages 257–360, February 2012 About the Cover: MathJax (see page 346) Trim: 8.25" x 10.75" 104 pages on 40 lb Velocity • Spine: 1/8" • Print Cover on 9pt Carolina AMS-Simons Travel Grants TS AN GR EL The AMS is accepting applications for the second RAV T year of the AMS-Simons Travel Grants program. Each grant provides an early career mathematician with $2,000 per year for two years to reimburse travel expenses related to research. Sixty new awards will be made in 2012. Individuals who are not more than four years past the comple- tion of the PhD are eligible. The department of the awardee will also receive a small amount of funding to help enhance its research atmosphere. The deadline for 2012 applications is March 30, 2012. Applicants must be located in the United States or be U.S. citizens. For complete details of eligibility and application instructions, visit: www.ams.org/programs/travel-grants/AMS-SimonsTG Solve the differential equation. t ln t dr + r = 7tet dt 7et + C r = ln t WHO HAS THE #1 HOMEWORK SYSTEM FOR CALCULUS? THE ANSWER IS IN THE QUESTIONS. -
Introduction to Clifford's Geometric Algebra
解説:特集 コンピューテーショナル・インテリジェンスの新展開 —クリフォード代数表現など高次元表現を中心として— Introduction to Clifford’s Geometric Algebra Eckhard HITZER* *Department of Applied Physics, University of Fukui, Fukui, Japan *E-mail: [email protected] Key Words:hypercomplex algebra, hypercomplex analysis, geometry, science, engineering. JL 0004/12/5104–0338 C 2012 SICE erty 15), 21) that any isometry4 from the vector space V Abstract into an inner-product algebra5 A over the field6 K can Geometric algebra was initiated by W.K. Clifford over be uniquely extended to an isometry7 from the Clifford 130 years ago. It unifies all branches of physics, and algebra Cl(V )intoA. The Clifford algebra Cl(V )is has found rich applications in robotics, signal process- the unique associative and multilinear algebra with this ing, ray tracing, virtual reality, computer vision, vec- property. Thus if we wish to generalize methods from tor field processing, tracking, geographic information algebra, analysis, calculus, differential geometry (etc.) systems and neural computing. This tutorial explains of real numbers, complex numbers, and quaternion al- the basics of geometric algebra, with concrete exam- gebra to vector spaces and multivector spaces (which ples of the plane, of 3D space, of spacetime, and the include additional elements representing 2D up to nD popular conformal model. Geometric algebras are ideal subspaces, i.e. plane elements up to hypervolume ele- to represent geometric transformations in the general ments), the study of Clifford algebras becomes unavoid- framework of Clifford groups (also called versor or Lip- able. Indeed repeatedly and independently a long list of schitz groups). Geometric (algebra based) calculus al- Clifford algebras, their subalgebras and in Clifford al- lows e.g., to optimize learning algorithms of Clifford gebras embedded algebras (like octonions 17))ofmany neurons, etc.