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Unified Mathematics (Uni-Math) with Geometric Algebra (GA)
David Hestenes Arizona State University
Santalo 2016
“For geometry, you know, is the gateway to science,and that gate is so low and small that you can enteronly as a little child.”
William Kingdon Clifford
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To demonstrate how geometric algebra unifies and simplifiesØ geometry, algebra and trigonometry
at the elementary level,Ø thereby simplifying and facilitating mathematical
applications to physics and engineering at the most advanced levels.
Purpose of this Talk
References• Introductory survey: Oersted Medal Lecture 2002 (AJP)
<http://modelingnts.la.asu.edu>• Most thorough treatment of GA fundamentals:
New Foundations for Classical Mechanics (Springer)• Interactive presentation for high school:
GA Primer <http://geocalc.clas.asu.edu/GAPrimer/>
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• You must relearn how to multiply vectors
• Learn how vector multiplication is designed for optimal encoding of geometric structure.
To Enter the Gate to Geometric Algebra
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Basic geometric-algebraic objects (H. Grassmann, 1844)
a•Directedline segment vector (1-vector) a
•Point scalar (0-vector) αα
a
b
•
Directedplane segment
bivector (2-vector)
a
b
c
•
Directedvolume
trivector (3-vector)
pseudoscalar in 3D
Geometric object Algebraic object ⇔
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Orientation & antisymmetry of the outer product
=
a
b
a–bab a
–b
=
Parallelogram rule for multiplicationAnticommutivity
Orientation (–) of vectors determines orientation of products:
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What we have established so far:
Geometry is built out of basic geometric objects with dimensions 0, 1, 2, 3, . . . , namely:point, line segment, plane segment, space segment, . . .
Basic geometric objects are represented by algebraic objects withgrades 0, 1, 2, 3, . . . , namely: scalar, vector, bivector, trivector (pseudoscalar), . . .[0-vector, 1-vector, 2-vector, 3-vector, . . . (k-vectors)]
The outer product (wedge product) enables us to build k-vectors out of vectors, as in
To represent geometric concepts of magnitude and direction,we need to extend the rules for combining k-vectors.
Assume familiarity with vector addition & scalar multiplication!
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symmetric inner product (scalar-valued)
∧
antisymmetric outer product:
Geometric algebra = Clifford algebra (1878)with geometric meaning!
Combineto form a single geometric product:
Theorem:Collinear vectors commute:
Orthogonal vectors anticommute:
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Understanding the import of this formula:
is the single most important step in unifying the mathematicallanguage of physics.
This formula integrates the concepts of• vector• complex number• quaternion• spinor• Lorentz transformation
And much more!
We consider first how it integrates vectors and complex numbers into a powerful tool for 2D physics.
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Consider the important special case of a unit bivector i It has two kinds of geometric interpretation!
b
a
b
aSo • i ≈ oriented unit area for a plane
I. Object interpretation as an oriented area (additive)Can construct i from a pair of orthogonal unit vectors:
b
aII. Operator interpretation as rotation by 90o (multiplicative)
depicted as a directed arc
• i ≈ rotation by a right angle:So
a
b
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a2 = b2 = 1 ab = Uθ
The operator interpretation of i generalizes to the concept ofRotor , the entity produced by the geometric product ab
of unit vectors with relative angle θ.Rotor is depicted as a directed arc on the unit circle.
Reversion:
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Defining sine and cosine functionsfrom products of unit vectors
i = unit bivector
Rotor:
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The concept of rotor generalizes to the concept of complex number interpreted as a directed arc.
Modulus
Reversion = complex conjugation
This represention of complexnumbers in a real GA is a special case of spinors for 3D.
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• Our development of GA to this point is sufficient to formulate and solve any problem in 2D physicswithout resorting to coordinates.• Of course, like any powerful tool, it takes some skill toapply it effectively.• For example, every physicist knows that skillful use of complex numbers avoids decomposing them into real and imaginary parts whenever possible.• Likewise, skillful use of the geometric product avoidsdecomposing it into inner and outer products.
• In particular, note the one-to-one correspondencebetween algebraic operations and geometric depictions!
• In the next portion of this lecture I demonstrate how rotor algebra facilitates the treatment of 2D rotationsand mechanics.
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Properties of rotorsRotor equivalence of directed arcs
is likeVector equivalence of directed line segments
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Properties of rotorsRotor equivalence of directed arcs
is likeVector equivalence of directed line segments
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Properties of rotorsRotor equivalence of directed arcs
is likeVector equivalence of directed line segments
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Properties of rotorsProduct of rotors Addition of arcs
UθUϕUθ, Uϕ = Uθ+ϕ
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Properties of rotorsRotor-vector product = vector
Uθ, v Uθv = u
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Basis for Generated by orthonormal frame
Scalars(0-vectors}
Vectors(1-vectors)
Bivectors(2-vectors)
Pseudoscalar (3-vector):
Expanded form for any multivector M in
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Canonical form: if
Reflection in a plane with normal a
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Reflection in a plane with normal a
Canonical form: if
Proof:
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Reflection in a plane with normal a
Canonical form: if
Proof:
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Reflection in a plane with normal a
Canonical form: if
Proof:
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Reflection in a plane with normal a
Canonical form: if
Proof:
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Reflection in a plane with normal a
Canonical form: if
Proof:
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Rotation as double reflection represented by rotor:
Proof:
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Proof:
Rotation as double reflection represented by rotor:
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Proof:
Rotation as double reflection represented by rotor:
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Proof:
Rotation as double reflection represented by rotor:
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Proof:
Rotation as double reflection represented by rotor:
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U represents rotation through twice the angle between a and b.
Proof:
Rotation as double reflection represented by rotor:
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Summary: Orthogonal transformations in Euclidean space
Main advantage:
Orthogonal transformation
Defining property :
Unimodular versor:
Versor parity: if U odd (reflection)if U even (rotation)
Composition of transformations:
Canonical form:
Reduced to versor products:
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Rotor products ⇔ composition of rotations in 3D
U1
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U1 , U2
Rotor products ⇔ composition of rotations in 3D
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U1 , U2
U2U1
Rotor products ⇔ composition of rotations in 3D
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U1 , U2
U2U1 = (bc)(ca)
Rotor products ⇔ composition of rotations in 3D
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U1 , U2
U2U1 = (bc)(ca)
= ba = U3
U2 U1 = U3
Rotor products ⇔ composition of rotations in 3D
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Noncommutativity of Rotations
U2 (U1) = U2U1
U1 (U2) = U1U2
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Noncommutativity of Rotations
U2 (U1)
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Noncommutativity of Rotations
U2 (U1) = U2U1
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Noncommutativity of Rotations
U2 (U1) = U2U1
U1 (U2
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Noncommutativity of Rotations
U2 (U1) = U2U1
U1 (U2)
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Noncommutativity of Rotations
U2 (U1) = U2U1
U1 (U2) = U1U2
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What have we learned so far?• Rules for multiplying vectors that apply to
vector spaces of any dimension.
• Integration of complex numbers with vectors, and interpretation as directed arcs.
• Geometric meaning of the geometric product and its component parts in
• How rotor algebra clarifies and facilitatesthe treatment of rotations in 2D and 3D.
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Point symmetry groups of molecules & crystals
• Increasing in importance as we enter the ageof nanoscience and molecular biology
• Each finite symmetry group is generated multiplicatively by 3 vectors in GA
• GA makes point groups accessible to students early in the curriculum at no academic cost
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Symmetries of the Cube
Generators: a, b, c
Relations:
Symbol: {4, 3, 2}
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Generators: a, b, c
32 Lattice Point Groups
Crystallographic restriction:
Groups {p, q, r}
Tetrahedral group {3, 3, 3}
Octahedral group {4, 3, 2}
Icosahedral group {5, 3, 2}
Relations: Roots of –1
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230 distinct 3D Space Groups
D. Hestenes & J. Holt, The Crystallographic Space Groups in Geometric Algebra, Journal of Mathematical Physics . 48, 023514 (2007)
• Generated by reflections in 5D Minkowski space• wherein Euclidean points are represented by null vectors• the optimal representation for 3D Euclidean space
Echard Hitzer & Christian Perwass http://www.spacegroup.info
• Interactive Visualization of the 32 3D Point Groups• Interactive Visualization of the 17 2D Space Groups• Space Group Visualizer for the 230 3D Space Groups• Contacts with International Union of Crystallography (IUCr)Towards Official Adoption of The Space Group Visualizer Software• Great potential for molecular modeling and diffraction theory!
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Summary for rotations in 2D, 3D and beyond
Thm. II: Every rotation in 3D can be expressed as product of two reflections:
Generalizations:III. Thm I applies to Lorentz transformations of spacetimeIV. Cartan-Dieudonné Thm (Lipschitz, 1880): Every orthogonal
transformation can be represented in the form:
Advantages over matrix form for rotations:–– coordinate-free–– composition of rotations:–– parametrizations (see NFCM)
Thm. I: Every rotation can be expressed in the canonical form:
where and U is even
Note:
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Rotor vs. matrix representations for rotations
Matrix representation: ek =α kjσ j α kj = σ j ⋅U(σk )
Rotation U : σk → ek = U(σk )
Rotor representation: ek =UσkU†
Matrix from rotor: α kj = ek ⋅σ j = UσkU†σ j
�
αkj ↔ UEstablishes
But it is invariably simpler to use rotors without reference to matrices!
Rotor from matrix (NFCM, p. 286)
Result: Form
Normalize to:
�
ψ = 1+ ekσ k = 1+ αkjσkσ j
U = ψψψ †( )12
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Rotational Kinematics
Time dependent rotor U = U(t)
⇒ Rotating frame:
= rotational velocity (bivector) from dynamics
Rotor eqn. of motion:
⇒ Frame eqn. of motion:
• Rotor eqn. is easier to solve than vector or 3× 3 matrix eqns.• Quaternions used in aerospace industry• Rigid body solutions in NFCM, Chap.13
Proofs:
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[Ref. NFCM. p. 473]
Classical model of spin:
⇒
Magnetic resonance:
Solution:
Resonance at
• Produces spiraling spin reversal in time: • Can be tuned to γ for different materials
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Constant Acceleration without coordinates!
v0t
r
trajectory:
•
•
vv0
g
g
hodograph:
v0
v
gt
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2r/tv0
vgt
Constant Acceleration:
Vector algebraic model
v0
v0t
v
r
•
•
trajectory
r/t
vgt
hodograph
Reduces all projectile problems to solving a parallelogram!
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Solving a parallelogram with Geometric Algebra
2r/tv0
vgt
Problem: Determine (a) the range r of a target sighted in a direction that
has been hit by a projectile launched with velocity ;(b) launching angle for maximum range; (c) time of flight
General case: Elevated target.• Complicated solution with rectangular coordinates in AJP.• Much simpler GA solution in NFCM.
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Solving a parallelogram with GA2r/tv0
vgt
horizontal ⇒ 2r/t
v0
vgt
θθ
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A challenge to the math-science community!
• Research on the design and use of mathematical software isequally important for instruction and for applications.
• GA is ready to incorporate into the curriculum.
• GA can enhance student understanding and accelerate student learning.
• GA provides a unified mathematical languagethat is conceptually and computationally superior to alternative math systems in every application domain.
Critically examine the following claims:
• GA provides new insight into the structure and interpretation of quantum mechanics and relativity theory.
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Ø Geometry is the foundation for mathematical modeling in physicsand engineering and for the science of measurement in the real world.
Ø The computationally and conceptually superior methods of analyticgeometry with GA facilitate real world applications.
Ø Reformulated Euclidean geometry with vector methods emphasizes the natural connection to kinematics and rigid body motions.
Unification and simplification of the high school math-sciencecurriculum with Geometric Algebra should be centered on geometrybecause:
The effect will be to simplify theorems and proofs, and vastly increaseapplicability of mathematics to physics and engineering.Whether or not the high school geometry course can be reformed in practice, the course content deserves to be reformed to make it moreuseful in physics and engineering applications.
Reform of the high school math-science curriculum can be greatly deepened and accelerated by introducing GA modeling softwarethat is equally attractive to math and science teachers!
A proposal for GA in the curriculum
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References
• Introductory survey: Oersted Medal Lecture 2002 (AJP)<http://modelingnts.la.asu.edu>
• Most thorough treatment of GA fundamentals:New Foundations for Classical Mechanics (Springer)
• Interactive presentation for high school:GA Primer <http://geocalc.clas.asu.edu/GAPrimer/>
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Geometric Algebra (GA) software for modeling & simulation– to unify the math-art-science-technology (MAST) curriculum
EngineeringDesignPhysics
Art & Animation
GA modeling &simulation tools
AlgebraGeometry
Trigonometry
Chemistry Molecular Biology
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