Matrix multiplication of an nxn matrix is the scaling

AI Thread Summary
Matrix multiplication of an nxn matrix is indeed associated with the scaling and rotation of vectors in n-dimensional space. Finding the inverse of a matrix corresponds to determining a transformation that converts a vector into a unit vector in a transformed space. The inverse matrix (A^{-1}) does not directly reflect the original matrix (A) in a simple manner, as both exist in different dimensional spaces, complicating their graphical representation. While the relationship between A and A^{-1} can be understood through the concept of reflection in higher dimensions, visualizing this relationship is challenging. Ultimately, the discussion emphasizes the complexity of relating matrices and their inverses geometrically.
chaoseverlasting
Messages
1,050
Reaction score
3
Geometrically, matrix multiplication of an nxn matrix is the scaling, and rotation of a vector in n dimensions true? So when you find the inverse of a matrix, what you're actually doing is finding a transformation such that in the 'transformed space' the vector is a unit vector.

If the inverse matrix (A^{-1})is plotted in the original space, then does it have any relation to the original matrix(A)?

What I mean by that is, if you have a function y=f(x) in 2 D space, and you find the inverse function x=f^{-1}(y) the inverse function is a reflection of the function y=f(x) about the line y=x. Does the inverse matrix (A^{-1}) have any such relation to the original matrix(A)?
 
Mathematics news on Phys.org


The relation between A^{-1} & A^... the inverse of A^, where it exists, is denoted by A^{-1} and AA^{-1} is equal to I ie. identity matrix = A^{-1}A
 


roam said:
The relation between A^{-1} & A^... the inverse of A^, where it exists, is denoted by A^{-1} and AA^{-1} is equal to I ie. identity matrix = A^{-1}A
True, but I don't believe that was the question he was asking.

chaoseverlasting said:
Geometrically, matrix multiplication of an nxn matrix is the scaling, and rotation of a vector in n dimensions true? So when you find the inverse of a matrix, what you're actually doing is finding a transformation such that in the 'transformed space' the vector is a unit vector.

If the inverse matrix (A^{-1})is plotted in the original space, then does it have any relation to the original matrix(A)?

What I mean by that is, if you have a function y=f(x) in 2 D space, and you find the inverse function x=f^{-1}(y) the inverse function is a reflection of the function y=f(x) about the line y=x. Does the inverse matrix (A^{-1}) have any such relation to the original matrix(A)?
What do you mean by "plotted in the original space"? An n by n matrix operates on n dimensional vectors and itself exist in an n2 vector space. In order to "graph" A and A-1 you would need an n4 dimensional graph.
 


HallsofIvy said:
True, but I don't believe that was the question he was asking.


What do you mean by "plotted in the original space"? An n by n matrix operates on n dimensional vectors and itself exist in an n2 vector space. In order to "graph" A and A-1 you would need an n4 dimensional graph.

Why would you need an n4 dimensional graph? Say for a 3x3 matrix, you would need a 9 D space then. Its kind of hard for me to imagine that, but say if we took each row or column to be a plane in 3D (where I suppose each plane corresponds to a projection of 9D space on 3D), would there be a relation between the planes of A and A^{-1} ?
 


A plane? Wouldn't each row or column of a three by three matrix simply be a vector in F^3?
 


Yeah, each row or column of a 3x3 matrix would be a vector, but if you assume that vector to be the normal vector passing through a given point then you get three planes depending on whatever matrix equation you use. I don't think a standalone 3x3 matrix could represent planes by itself.

Even so, I'm guessing here, the projection would give you three vectors instead of three planes. So you would have a set of three vectors corresponding to A and three vectors corresponding to A^{-1}, would the vectors of A and A-1 be co-related in any way?
 


Anyone? Please :p ?
 


chaoseverlasting said:
What I mean by that is, if you have a function y=f(x) in 2 D space, and you find the inverse function x=f^{-1}(y) the inverse function is a reflection of the function y=f(x) about the line y=x. Does the inverse matrix (A^{-1}) have any such relation to the original matrix(A)?

In general, any function (including e.g. matrices) f:R^n\rightarrow R^n has a graph in R^{2n} which is the set \{(\textbf{x},f(\textbf{x})):\textbf{x}\in R^n\}. If f is invertible then the graph of f^{-1} is \{(f(\textbf{x}),\textbf{x}):\textbf{x}\in R^n\}. You get one from the other by reflection through a hyperplane and you can easily write out the matrix for this.

For a function on R this is very usefull as a visual aid. In general, not so. I think what you want to know is if we can read off the value that A^{-1} assigns to x using the graph of A? Because we can't visualise the graph we can't.
 
Last edited:


olliemath said:
In general, any function (including e.g. matrices) f:R^n\rightarrow R^n has a graph in R^{2n} which is the set \{(\textbf{x},f(\textbf{x})):\textbf{x}\in R^n\}. If f is invertible then the graph of f^{-1} is \{(f(\textbf{x}),\textbf{x}):\textbf{x}\in R^n\}. You get one from the other by reflection through a hyperplane and you can easily write out the matrix for this.

For a function on R this is very usefull as a visual aid. In general, not so. I think what you want to know is if we can read off the value that A^{-1} assigns to x using the graph of A? Because we can't visualise the graph we can't.

Thats exactly it. How would you go about writing a matrix for this? Perhaps we can't use it as a visual aid, but it would simplify a lot of other calculations.
 
  • #10


Use

B:=\left[ \begin{array}{cc} 0 &amp; I \\<br /> I &amp; 0 \end{array} \right]

where I is the identity on R^n. The coordinates of a general point on the graph are (Ix,Ax), so the coords of a general point on the graph of the inverse are B(Ix,Ax)=(Ax,Ix). One usually writes out the matrix (A,I):R^n\rightarrow R^{2n} and uses gaussian elimination to convert it to (I,A^{-1}), which again gives points on the graph of the inverse, but in a more useful fashion.
 

Similar threads

Back
Top