Matrices in more than 2 dimensions

In summary, 2D matrices are a fundamental concept in algebra, but higher dimensional matrices, also known as tensors, exist and can be represented by arrays. However, the laws of addition and multiplication for matrices do not apply to higher dimensional arrays. A third order tensor, for example, would be represented by a cube of numbers with 3 layers consisting of 3 rows and 3 columns. While tensors may seem more complex, they can be simplified and represented by 2D arrays in certain situations.
  • #1
The Rev
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I've been learning about 2D matrices in algebra, like the one below, and was wondering if there were matrices in higher maths that used 3 or more dimensions, and if someone would describe or provide an example. Just curious.

[tex]\left[\begin{array}{ccc}1&0&0\\0&1&0\\0&0&1\end{array}\right][/tex]

Thanks.

[tex]\psi[/tex]

The Rev
 
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  • #2
The matrix above is called the identity matrix. Furthermore, it's a 3-rd order square matrix. In general, a matrix can be of the order (m,n) , where m is the number of rows and n the number of columns. I guess we could call this 3-rd order a 3-d matrix, because it's columns or rows can be interpreted as vectors in space. The same goes for matrixes of higher order, but we cannot 'draw' these vectors in space - the function of these vectors is important in solving linear albegar equations.
 
  • #3
But what the Rev is asking about is a "matrix" that would be a cube of numbers rather than a square. That is, with an underlying 3 dimensional space, 3 layers, each consisting of 3 rows and 3 columns: 27 numbers.

Yes, such things do exist but I think it would be more appropriate to call it an "array" rather than a matrix- matrices assume specific laws for addition and multiplication that would not apply here. With a given coordinate system, a third order tensor could be represented by such an array.
 
  • #4
I was thinking of a matrix like the one above, with rows and columns (x & y vertices) AND some kind of z vertex (depths?) so the matrix formed a cube instead of a square (or a hypercube, etc.). Is this what you mean? (I'm inferring from your post that you're a few textbooks ahead of where I am in your math studies, so don't be shy about dumbing down your responses. :blushing: ).

[tex]\psi[/tex]

The Rev
 
  • #5
HallsofIvy said:
But what the Rev is asking about is a "matrix" that would be a cube of numbers rather than a square. That is, with an underlying 3 dimensional space, 3 layers, each consisting of 3 rows and 3 columns: 27 numbers.

Yes, such things do exist but I think it would be more appropriate to call it an "array" rather than a matrix- matrices assume specific laws for addition and multiplication that would not apply here. With a given coordinate system, a third order tensor could be represented by such an array.

Tensors, eh? Well, that's a ways off. Thanks!

[tex]\psi[/tex]

The Rev
 
  • #6
An interesting thing, though, is that 2-D arrays can be good enough to do things that would seem more natural to do with a higher dimensional array.

For example, suppose I have a collection of n matrices and n vectors. The n matrices would be most naturally represented by a three dimensional array, but if the thing I'm most interested is the sum A1 v1 + A2 v2 + ... + An vn, then this partitioned matrix is good enough:


[A1 | A2 | ... | An] [v1 | v2 | ... | vn]^T

In other words, the matrix on the left is formed by placing the individual matrices side by side, and the vector on the right is formed by stacking the individual vectors on top of each other.


Note that we may think of the one on the left as being a row vector whose entries are matrices, and the one on the right being a column vector whose entries are column vectors!
 

What is a matrix in more than 2 dimensions?

A matrix in more than 2 dimensions is a collection of numbers arranged in rows and columns, similar to a 2D matrix. However, a 3D matrix has an additional dimension, making it a three-dimensional array. This can be extended to higher dimensions, such as a 4D matrix or a 5D matrix.

What are the applications of matrices in more than 2 dimensions?

Matrices in more than 2 dimensions have various applications in fields such as computer graphics, computer vision, and engineering. They are used to represent and manipulate data in multiple dimensions, making them useful for tasks such as image processing, data compression, and data analysis.

How are matrices in more than 2 dimensions represented?

A matrix in more than 2 dimensions is represented by using square brackets to enclose the elements, with each dimension separated by a comma. For example, a 3D matrix with dimensions 3x3x3 would be represented as [ [ [a, b, c], [d, e, f], [g, h, i] ], [ [j, k, l], [m, n, o], [p, q, r] ], [ [s, t, u], [v, w, x], [y, z, 1] ] ]

What are the basic operations that can be performed on matrices in more than 2 dimensions?

Basic operations on matrices in more than 2 dimensions include addition, subtraction, and multiplication. These operations follow similar rules as 2D matrices, with corresponding elements in each dimension being operated on. However, for multiplication, the dimensions of the matrices must be compatible, such as a 3x3x3 matrix multiplied by a 3x3 matrix, resulting in a 3x3x3 matrix.

What are some advantages of using matrices in more than 2 dimensions?

Using matrices in more than 2 dimensions allows for the representation and manipulation of complex data in a concise and efficient manner. It also allows for easier visualization and analysis of data in multiple dimensions, making it a valuable tool in various scientific and technical fields.

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