Matrices in more than 2 dimensions

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Discussion Overview

The discussion revolves around the concept of matrices in higher dimensions, specifically exploring the existence and representation of matrices beyond two dimensions, including potential examples and applications. Participants examine the differences between traditional matrices and higher-dimensional structures such as arrays and tensors.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant inquires about the existence of matrices in three or more dimensions, providing an example of a 2D identity matrix.
  • Another participant identifies the 2D identity matrix as a 3rd order square matrix and suggests that matrices can be interpreted as vectors in space, but acknowledges limitations in visualizing higher-order matrices.
  • A different participant clarifies that the inquiry pertains to a "matrix" that represents a cube of numbers, consisting of 27 elements arranged in three dimensions, and suggests that such structures are better termed "arrays" rather than matrices due to differing mathematical properties.
  • Further, a participant proposes that a matrix could be visualized as having rows, columns, and a depth component, indicating a misunderstanding of dimensionality in the context of matrices.
  • Another participant notes that 2D arrays can effectively represent operations typically associated with higher-dimensional arrays, providing an example of how matrices and vectors can be combined in a partitioned format.

Areas of Agreement / Disagreement

Participants express differing views on the terminology and conceptualization of higher-dimensional matrices versus arrays and tensors. There is no consensus on the appropriate definitions or representations, and the discussion remains open-ended.

Contextual Notes

Participants exhibit varying levels of familiarity with the concepts of matrices, arrays, and tensors, leading to potential misunderstandings about dimensionality and mathematical operations. The discussion reflects a range of assumptions and interpretations regarding the nature of higher-dimensional structures.

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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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.
 
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.
 
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
 
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
 
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!
 

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