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Eigenvalues and eigenvectors

Print eigenvalues summary
The system   (λI − A) = 0   has a non trivial solution if and only if det |λI − A| = 0.   If P  denote the matrix of the eigenvectors and   B   denote the diagonal matrix with diagonal elements being the eigenvalues   λi   of   A.
We can write: AP = PB
P − 1 AP = B         or         A = PBP − 1
In this case,   A   is said to be similar to   B.
Similar matrices
Example:   Find the eigenvalues and the eigenvectors of the       matrix A = Eigenvalues example
From the eigenvalues equation we get the characteristic polynomial:
characteristic polinomial characteristic polinomial result
Eigenvalues
The eigenvalues are the roots of the characteristic polynomial, and are: − 2, − 2,   4   this values are the diagonal values and has the same determinant value as matrix     A.  In order to find the eigenvectors, substitute first solution λ =− 2   into the characteristic matrix, the result is:
Matrices eigenvector
Those MathCalc reduce to one independent equation: x − y + z = 0
Choose arbitrary   y = 0   to receive the first eigenvector x = 1,       y = 0,       z = − 1
Choose arbitrary   z = 0   to get the second vector: x = 1,       y = 1,       z = 0
Perform the same process with the third solution   λ = 4   to get:
Matrices eigenvector
The result is two independent equations: x + y − z = 0         and         2y − z = 0
Choose arbitrary   y = 1   to receive the vector x = 1,         y = 1,         z = 2
The three eigenvectors are: Matrices eigenvectors
We can see that the result is matching to the definition of the eigenvectors and eigenvalues:
Result eigenvalues

Rotation Matrices

Print rotation matrices
Rotation of a vector is performed by applying the rotation matrix   R on the vector   V.           V' = R × V If the rows and columns of a rotation matrix R are orthogonal to each other and of unit length then the following relations are true:
RT = R− 1             RT R = RRT = I             detR = 1
Two-dimensional rotation
Rotation by θ counterclockwise Matrices rotation +θ counterclockwise
−θ clockwise
Rotation by θ clockwise Rotation by  θ  clockwise sin(−θ) = −sinθ
cos(−θ) = cosθ
Rotation by 90° counterclockwise Rotation by 90° counterclockwise
Rotation by 180° counterclockwise Rotation by 180° counterclockwise
Rotation by 270° counterclockwise Rotation by 270° counterclockwise
Three dimensional rotation (θ − x axis,       ϕ − y axis,       φ − z axis)
Rotation about
x axis
Rotation about x axis
Rotation about x axis Rotation about x axis
Rotation about>
y axis
Rotation about> y axis
Rotation about> y axis Rotation about> y axis
Rotation about
z axis
Rotation about z axis
Rotation about z axis Rotation about z axis
Rotation table
Combined rotation in the direction of all axes can be done by multiplying the three rotation matrices in the x,y and z direction
Counterclockwise: Rxyz = Rx(θ)∙Ry(ϕ)∙Rz(φ)
Mixed direction: Rxyz = Rx(−θ)∙Ry(−ϕ)∙Rz(φ)
Rotation in the direction of two axes can be done by:
Rxy = Rx Ry or Rxz = Rx Rz or Ryz = Ry Rz
clockwise rotation matrix of the axes (vector is moved counterclockwise)
Note: the order of the rotation is important as rotation Rx (θ) Ry (ϕ) Rz (φ)   is not equal to rotation
Rz (φ) Ry (ϕ) Rx (θ).
Clockwise rotation
Counterclockwise rotation matrix of the axes (vector is moved clockwise)
Counterclockwise rotation
Example:
Rotate the vector V = 2i + j
by 30° counterclockwise. Matrices rotation by 30° counterclockwise
(Rotated vector) V ' = R × V           (R - Rotation matrix)
Rotation matrices
V' = [2 cos(30°) − sin(30°)]i + [2 sin(30°) + cos(30°)]j
V' = 1.23i + 1.87j
Example:
Rotate the vector   V = i + j + k   by an angle of   30°   counterclockwise about the x axis,   45°   clockwise about the   y   axis and   60°   clockwise about   z   axis.
Step 1: rotation θ = 30° about x axis counterclockwise:
rotation θ = 30° about x axis counterclockwise
Step 2: rotation ϕ = 45° about y axis clockwise:
rotation ϕ = 45° about y axis clockwise
Step 3: rotation φ = 60° about z axis clockwise:
rotation φ = 60° about z axis clockwise