# Sect. 4.7: Finite Rotations

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08-Jan-2018Category

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### Transcript of Sect. 4.7: Finite Rotations

Sect. 4.7: Finite Rotations

So far: Have used various representations todescribe the relative orientation of 2 Cartesian coord systems with common origin: Weve shown the transformation matrix A in terms of: The Euler Angles:A = A(,,) The Cayley-Klein parameters: A = A(,,,) Euler parameters: A = A(e0,e1,e2,e3) Single rotation about a given directionA = A() Here: We seek another representation: A vector relationship between an initial vector r & the vector r which results from the orthogonal transformation (rotation) r = Ar.Representation in terms of the rotation angle & direction cosines of rotation axis. Get result using figure &

vector algebra. Treat transformation asactive Counterclockwise coord rotation = Clockwise rotation of vectors in the fixed coord system. Fig: Initial position of vector r = OP. Final position r = OQ. Rotation axis along ON. Unit vector along ON = n. Rotation angle = .|ON| = nr ON = n(nr). NP =OP - ON = r - n(nr). |NP| =|NQ| = |rn| OQ = r = ON + NV + VQ Taking all of these together:

r = n(nr) + [r - n(nr)]cos + (rn)sin Or: r = r cos + n(nr)(1 - cos) + (rn)sin The Rotation Formula Holds for any rotation! Worth mentioning: Can easily express rotation angle in terms of Euler angles ,, by comparing representations of the transformation matrix A in termsof one & the other. For A = A(,,) we had: For A = A() we had: cos sin 0 A=-sin cos 0 The trace of A is invariant under a change of representation:

TrA() = TrA(,,) Use some trig identities (student exercise!): cos[())] = cos[()( + )]cos[()] Sign fixed by requiring 0 as ,, 0 Sect. 4.8: Infinitesimal Rotations

Summary: Representations to describe relative orientation of 2 Cartesian coord systems with common origin: r = Ar Euler angles:A = A(,,) Cayley-Klein parameters: A = A(,,,) Euler parameters: A = A(e0,e1,e2,e3) Single rotation about a given direction A = A() Direct vector relationship between r & r r = r cos + n(nr)(1 - cos) + (rn)sin In all cases discussed for the transformation A, the number of matrix elements is > # independent variables (=3) Had a number constraints between variables to reduce # indep ones to 3. In proof of Eulers Theorem weve shown: Any given orientation r = Ar can be obtained by a single rotation about some axis. It would be nice if we could associate a vector (with 3 independent components) with a finite rotation of a rigid body about a fixed point. Direction of vector is obvious: Direction of axis of rotation. That is, direction of eigenvector R. Magnitude: A suitably chosen function of rotation angle could possibly be used as magnitude of this vector. However, we cannot do this (for finite rotations!). Vectors Addition must be commutative: A + B = B + A

Why? Let A & B be 2 vectors associated with transformations A & B. Vectors Addition must be commutative: A + B = B + A But, weve seen, the addition of 2 rotations (one, followed by a 2nd) corresponds to product AB Matrix multiplication is NOT commutative: AB BA A & B are not commutative & cannot be represented as vectors. That is, the sum of finite rotations depends on the order of rotations. See figure for illustration: A finite rotation cannot be represented by a vector.

However, we can show that infinitesimal rotations CAN be represented by a vector! Infinitesimal rotation An orthogonal transformation of coordinate axes x = Ax in which components of the vector are almost the same with respect toboth sets of axes (infinitesimal change). That is, xi xi + small corrections (i = 1,2,3) Write: xi =xi + i1x1 + i2x2 + i3x (i = 1,2,3) Where the ij are infinitesimals. In calculations only terms linear in ij are kept, higher powers are neglected. Using summation convention, write infinitesimal transformation as: xi =(ij+ ij)xj (i = 1,2,3)

In matrix notation (defining infinitesimal matrix & relating it to transformation matrix A) this is: x (1+ )x Ax That is: (1+ ) A Note that the sequence of operations doesnt matter for infinitesimal transformations 1 + 2 (they commute because powers of higher than 1st are neglected): (1+ 1)(1+ 2) = 11 + 21+ 121 Or: (1+ 1) (1+ 2) 1 + 1 + 2 The order of infinitesimal rotations doesnt matter! Infinitesimal rotations: (1+ ) A

In terms of Euler angles ,,, orthogonal matrixA is represented as: For infinitesimal Euler angles: d,d,d: cos(d) cos(d) cos(d) 1 sin(d) d, sin(d) d,sin(d) d For infinitesimal rotations: (d + d) 0 A= - (d + d) d d Infinitesimal rotations: (1+ ) A, = A - 1 Where: 1 (d + d) 0

A= - (d + d) d d (d + d)0 = A = - (d + d) d d Euler angle representation of General properties of & A: = A - 1, 1+ = A

Clearly, A-1 = = 1- Proof: AA-1 = (1+ )(1- )= 12 + 1 Also: = - . is antisymmetric! Proof: = 1- = 1 + = - Convenient to write in form: 0 d d2 = - d d1 d2 - d d1, d2, d3 3 infinitesimal parameters identified with 3 independent parameters needed to specify rotation. We had: r (1+ )r Ar (or x = (1+ )x = Ax) r - r = r dr

Using the matrix, this becomes: dx1 = x2d3 - x3d2 dx2 = x3d1 - x1d3 dx3 = x1d2 - x2d1 These expressions should remind us of components of the cross product of 2 vectors. Define the vector: d vector with components d1, d2, d3 Text emphasizes that d differential of a vector! Instead, it is a vector of differential magnitude. That is a vector which has a differential d does not exist!!!! So, we can write: dr = r r d

r is a vector Transforms under an orthogonal transformation B according to r =Br or: xi =bijxj If d is a vector, it must also transform like this under an orthogonal transformation B. Will now look at the transformation properties of d To look at this, first look at transformation properties of matrix under the transformation B. Previous discussion = BB-1 It is shown in Prob. 3, p 180, that the property that is antisymmetric is preserved in this similarity transformation. So similar to , can also be written as:

0 d3 - d2 = -d3 d1 d2- d1 Skipping some tedious steps, can show that di are related to dj by (|B| determinant of B) : di =|B|bijdj This transformation is ALMOST the same as for a vector (xi =bijxj) but differs by the factor of |B|. Before discussing the details of the difference between d and a vector, look at its properties another way. For FINITE rotations, we had: r = r cos + n(nr)(1 - cos) + (rn)sin The Rotation Formula (1) To get the present INFINITESIMAL rotation case from this, let d in (1). cos(d) 1, sin(d) d (1) becomes: r = r + (rn)d Or: r - r dr = (rn)d We had:dr r d d nd d = nd under the orthogonal transformation B:

Now, discuss transformation properties of d = nd under the orthogonal transformation B: We had: di =|B|bijdj (1) Ordinary vectors transform like: xi =bijxj(2) Define: (property under the transformation B): Polar Vector Any quantity for which thecomponents transform according to (2) Axial Vector Any quantity for which the components transform according to (1) (also called a pseudovector) Properties under inversion Sij = -ij: Polar Vector: All components change sign Axial Vector: Components do not change sign. Sect. 4.8: Polar & Axial Vectors

Example of an axial vector: A vector which is the cross product of 2 polar vectors. If D, F are polar vectors: V* = D F is an axial vector. Clearly, Vi* = DjFk -DkFj (i,j,k cyclic) By definition of polar vectors, components Dj, Fk, Dk, Fj change sign on inversion Vi* does not. Physical quantities which are polar vectors: Position r, velocity v, momentum p = mv, acceleration a, force F = ma, electric field E,... Physical quantities which are axial (pseudo) vectors:Angular momentum L = r p, torque N = r F, magnetic field B, ... S = scalar, V = vector, V* = axial (pseudo) vector

Define a Parity Operator P (actually ~ same as inversion operator of earlier): P converts x, y, z to -x,-y, -z S = scalar, V = vector,V* = axial (pseudo) vector PS = S, PV = -V, PV* = V* Suppose, we have a scalar (like) quantity S* VV* PS* = P(VV*) = -(VV*) = -S* Pseudoscalar Any otherwise scalar quantity which behaves like S* under inversion. Any quantity which can be written as the scalar product of a polar vector and an axial (pseudo) vector. Physical quantities which are pseudoscalars: Magnetic flux, . Polar vectors: The vector itself remains unchanged on inversion, the components change sign.

Axial vectors: Carry a handedness property with them (consistent with the cross product!).Cross product (the vector itself!) clearly changes sign with coordinate inversion. Back to infinitesimal rotations: We had: di =|B|bijdj (1) Ordinary vectors transform like: xi =bijxj(2) Also: dr r d. Both r & dr are polar vectors & transform according to (2). d must be an axial vector, transforming according to (1). d nd. Inversion n changes direction. Some comments on cross product. C = D F

Introduce the Levi-Civita density ijk Write Cartesian components of C: Cij,kijkDjFk ijk permutation symbol or Levi-Civita density ijk 0, if any 2 indices equal 1, ifi, j, k are even permutation of 1,2,3 -1, ifi, j, k are an odd permutation of 1,2,3 122= 313 = 211 = 0 , etc. 123= 231 = 312=1,132= 213= 321 =-1 Formalism developed so far (r = Ar) to represent the orientation of a rigid body. Transformation involves rotation of the coordinate system. That is, usually assumed passive interpretation of transformation A. Counterclockwise rotation about some axis. Often need active interpretation of r = Ar. Physical system & the associated vectors are rotating in the clockwise direction. Often also, need rotation formulas explicitly for this but for vectors rotating in counterclockwise direction. If careful, can use formulas just derived. But, need to let direction of rotation be opposite & also axis of rotation to be opposite. Figure illustrates passive, active transformations: Formulas for Counterclockwise Rotations (note sign changes in , di)

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