Row of a matrix is a vector along the same degree of freedom

Click For Summary

Discussion Overview

The discussion revolves around the interpretation of matrices, particularly focusing on the relationship between rows and columns, and how matrices can be viewed geometrically. Participants explore the implications of viewing matrices as arrays of vectors and the mathematical operations involving them, including matrix-vector multiplication.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification

Main Points Raised

  • One participant suggests that viewing matrices as arrays of column vectors leads to confusion regarding the interpretation of rows as vectors along the same degree of freedom.
  • Another participant clarifies that row vectors can be considered as transposed vectors, which affects the interpretation of scalar products in matrix form.
  • A different viewpoint presents matrices as operators that can transform functions, using the example of Fourier series to illustrate how functions can be represented by column vectors and manipulated through matrix multiplication.
  • One participant expresses uncertainty about the geometric interpretation of matrices, suggesting that a discrete 2-D plot might be a fundamental representation.
  • Another participant references a resource that relates ordinary and matrix representations of equations, specifically in the context of angular momentum and kinetic energy.
  • A follow-up question is posed regarding the labeling of rows and columns in an m x p matrix, indicating a desire for clarification on dimensionality and indexing.

Areas of Agreement / Disagreement

Participants express various interpretations and conceptualizations of matrices, with no clear consensus on a singular geometric interpretation or the implications of viewing rows and columns in specific ways. The discussion remains open-ended with multiple competing views.

Contextual Notes

Participants acknowledge the complexity of interpreting matrices and the potential for confusion regarding the relationships between rows and columns. There are also references to specific mathematical contexts that may not be universally applicable.

Gear300
Messages
1,209
Reaction score
9
A particular introduction to matrices involved viewing them as an array/list of vectors (column vectors) in Rn. The problem I see in this is that it is sort of like saying that a row of a matrix is a vector along the same degree of freedom (elements of the same row are elements of different vectors all in the same dimension). So from this, technically, the scalar product of a column vector v and row1 of a matrix A should only exist as a product between the elements of row1 of the matrix A and row1 of the column vector v...which doesn't seem right (since matrix-vector multiplication Av is defined as a column vector of dot products between the vector v and rows of A). How would one geometrically interpret a matrix?
 
Last edited:
Physics news on Phys.org
Gear300 said:
… So from this, technically, the scalar product of a column vector v and row1 of a matrix A should only exist as a product between the elements of row1 of the matrix A and row1 of the column vector v...

which doesn't seem right (since matrix-vector multiplication Av is defined as a column vector of dot products between the vector v and rows of A).

Hi Gear300! :smile:

Technically, row vectors are transpose vectors,

so the first row of A is is not the vector a1 (say), but the transpose vector a1T.

Then your scalar product in matrix form is (a1T)v,

but in ordinary form is a.v :wink:
How would one geometrically interpret a matrix?

Dunno :redface:, except that I always think of a matrix as being a rule that converts one vector into another vector. :smile:
 


I understand matrices as operators, like you may have basis vectors (x,y,z all normal), you can have basis functions (such as sin(nx) for n=1,2,3...) which any periodic function can be decomposed into using Fourier series. Then the function can be represented completely by a column vector containing the amplitude of each frequency, and the matrix multiplication will output a new function. So in that sense you might represent a matrix geometrically by a series of "before and after" functions!

Then again this is just fun speculation... the most fundamental way of expressing a matrix geometrically is probably by a discrete 2-D plot, f(m,n) = the (m,n)th element of the matrix.
 


I see...good stuff so far...Thanks for all the replies.
 
Hi Gear300! :smile:

I've found http://farside.ph.utexas.edu/teaching/336k/lectures/node78.html#mom" on john baez's excellent website which shows the relation between the ordinary and the matrix representation of the same equation, and where the transpose fits in …

if ω is the (instantaneous) angular velocity, then the rotational kinetic energy is both:

1/2 ω.L
and (without the "dot")
1/2 ωTL = 1/2 ωTÎω

where L is the (instantaneous) angular momentum, and Î is the moment of inertia tensor, both measured relative to the centre of mass.
 
Last edited by a moderator:


Thanks a lot for the link tiny-tim.

So, its sort of like saying that for an m x p matrix with n being a dimensional space, you could label the rows (going down) from n = 1 to n = m and you could also label the columns (going across) from n = 1 to n = p, right?
 
Last edited:

Similar threads

  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 4 ·
Replies
4
Views
4K
  • · Replies 27 ·
Replies
27
Views
3K
  • · Replies 14 ·
Replies
14
Views
4K
  • · Replies 1 ·
Replies
1
Views
4K
  • · Replies 4 ·
Replies
4
Views
9K
  • · Replies 7 ·
Replies
7
Views
1K
  • · Replies 6 ·
Replies
6
Views
3K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 3 ·
Replies
3
Views
2K