Two dimensions
It is important to understand the frame of reference when discussing rotations. From one point of view, you may be discussing rotating a vector, keeping the axes fixed. From another point of view, you may be rotating the coordinates, while keeping the vector fixed.
In the first point of view, a counterclockwise rotation of a coordinate or vector about the origin, where is rotated and we want to know the coordinates after the rotation, :
or
In a counterclockwise rotation of the plane or axes about the origin, the coordinates in the new plane will be rotated clockwise in the new coordinates. In this case, if the coordinates in the old plane are and the coordinates of the same vector in the new plane are , then:
or
Then the magnitude of the vector (x, y) is the same as the magnitude of vector (x′, y′).
Complex plane
A complex number can be seen as a two-dimensional vector in the complex plane, with its tail at the origin and its head given by the complex number. Let
Then z can be rotated counterclockwise by an angle θ by pre-multiplying it with (see Euler's formula, §2), viz.
&= (x cos theta + i y cos theta + i x sin theta - y sin theta)
&= (x cos theta - y sin theta) + i (x sin theta + y cos theta)
&= x' + i y' .end{align}
This can be seen to correspond to the rotation described in § 1.
Because multiplication of complex numbers is commutative, rotation in 2 dimensions is commutative, unlike in higher dimensions.
Three dimensions
In ordinary three-dimensional space, a coordinate rotation can be defined by three Euler angles, or by a single angle of rotation and the direction of a vector about which to rotate.
Rotations about the origin are most easily calculated using a 3×3 matrix transformation called a rotation matrix. Rotations about another point can be described by a 4×4 matrix acting on the homogeneous coordinates.
Quaternions
An alternative approach to rotation in three dimensions uses quaternions.
Quaternions provide another way of representing rotations and orientations in three dimensions. They are applied in computer graphics, control theory, signal processing and orbital mechanics. For example, it is common for spacecraft attitude-control systems to be commanded in terms of quaternions, which are also used to telemeter their current attitude. The rationale is that combining many quaternion transformations is more numerically stable than combining many matrix transformations, and quaternions avoid the problem of gimbal lock.
Generalizations
Orthogonal matrices
The set of all matrices M(v,θ) described above together with the operation of matrix multiplication is called rotation group: SO(3).
More generally, coordinate rotations in any dimension are represented by orthogonal matrices. The set of all orthogonal matrices of the n-th dimension which describe proper rotations (determinant = +1), together with the operation of matrix multiplication, forms the special orthogonal group: SO(n). See also SO(4).
Orthogonal matrices have real elements. The analogous complex-valued matrices are the unitary matrices. The set of all unitary matrices in a given dimension n forms a unitary group of degree n, U(n); and the subgroup of U(n) representing proper rotations forms a special unitary group of degree n, SU(n). The elements of SU(2) are used in quantum mechanics to rotate spin.
Relativity
In special relativity a Lorentzian coordinate rotation which rotates the time axis is called a boost, and, instead of spatial distance, the interval between any two points remains invariant. Lorentzian coordinate rotations which do not rotate the time axis are three dimensional spatial rotations. See: Lorentz transformation, Lorentz group.
See also
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Last updated on Wednesday July 23, 2008 at 13:08:08 PDT (GMT -0700)
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