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  • Notation
  • Transformation Matrices
  • Examples
  • Types of Transformations
  • Transformations - Generally
  • Linear Transformations
  • Operators

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  1. Linear Algebra

Transformations

A description of vector transformations and how they're preformed

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Last updated 5 years ago

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We can transform a vector to change it into another vector. In general, this vector can be in the same or in a different - for example, a vector along one plane could transform into a vector along another plane .

Notation

So, the expression...

Transformation Matrices

Examples

The Identity Matrix

If you preform the multiplication here you'll see that this transformation didn't do anything - we call this the identity transformation because it gives us the identity of the matrix we transform it by. This special matrix will come in handy later.

Rotational Matrix

Types of Transformations

Transformations - Generally

In general, any matrix which can be "applied" or multiplied to another matrix can be a transformation.

In the case of a column vector, we're affecting some kind of change on it, taking one thing and "making" it into another. The old vector and the new vector share a particular relationship, which is described by the transformation matrix.

Linear Transformations

A linear transformation is a transformation that affects a vector within the context of vector spaces.

Operators

Operators are special linear transformations that transform a vector within it's vector space.

In this case we can't change a vector in one plane into a vector in another plane, but we can rotate a vector along the same plane. This means all operators are linear transformations, but not vice versa.

Transformations are labeled with a letter wearing a little hat - like this: T^\hat{T}T^. To apply the transformation, we the vector by the transformation.

T^∣x⟩=∣y⟩\hat{T}|x\rangle = |y\rangleT^∣x⟩=∣y⟩

...describes ∣y⟩|y\rangle∣y⟩, which is a result of ∣x⟩|x\rangle∣x⟩transformed by (multiplied by the matrix represented by) T^\hat{T}T^.

In general, we can use a matrix to define the actions preformed which result in a given transformation. We a vector by the transformation to apply these operations in the proper order.

LetT^=[100010001],∣u⟩=[357]Let \hspace{8pt} \hat{T}=\begin{bmatrix}1&0&0\\0&1&0\\0&0&1\end{bmatrix}, |u\rangle = \begin{bmatrix}3\\5\\7\end{bmatrix}LetT^=​100​010​001​​,∣u⟩=​357​​
T^∣u⟩=[100010001]∗[357]=[357]\hat{T}|u\rangle=\begin{bmatrix}1&0&0\\0&1&0\\0&0&1\end{bmatrix}*\begin{bmatrix}3\\5\\7\end{bmatrix}=\begin{bmatrix}3\\5\\7\end{bmatrix}T^∣u⟩=​100​010​001​​∗​357​​=​357​​
LetR^=[0−110],∣v⟩=[35]Let \hspace{8pt} \hat{R}=\begin{bmatrix}0&-1\\1&0\end{bmatrix}, |v\rangle = \begin{bmatrix}3\\5\end{bmatrix}LetR^=[01​−10​],∣v⟩=[35​]
R^∣v⟩=[0−110]∗[35]=[−53]\hat{R}|v\rangle=\begin{bmatrix}0&-1\\1&0\end{bmatrix} * \begin{bmatrix}3\\5\end{bmatrix} =\begin{bmatrix}-5\\3\end{bmatrix} R^∣v⟩=[01​−10​]∗[35​]=[−53​]

This transformation rotated ∣v⟩|v\rangle∣v⟩ by 90∘90^\circ90∘.

For example, we take a vector along one plane and transform it to a vector along another plane. Or perhaps we take a vector and rotate it within the same plane. We're talking about transformations within the context of linear relationships .

Transformation matrix problems
More specific details about linear transformations and how they work
Fun transformation visualization tool
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(Das, R )
vector space
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A shear matrix - stretches the grid along the x axis.
A stretching and flipping two-dimensional linear transformation