Angle between vector and its transpose


by newphysist
Tags: angle
newphysist
newphysist is offline
#1
Nov21-12, 12:53 PM
P: 12
Hi

What is the angle between a vector (e.g. a row vector A) and it's transpose (a column vector) ? I know what transpose means mathematically but what is the intuition?

Thanks guys
Phys.Org News Partner Mathematics news on Phys.org
Researchers help Boston Marathon organizers plan for 2014 race
'Math detective' analyzes odds for suspicious lottery wins
Pseudo-mathematics and financial charlatanism
Dead Boss
Dead Boss is offline
#2
Nov21-12, 01:29 PM
P: 150
Quote Quote by newphysist View Post
Hi

What is the angle between a vector (e.g. a row vector A) and it's transpose (a column vector) ? I know what transpose means mathematically but what is the intuition?

Thanks guys
If you're talking about simple real vectors (e.g. arrows in euclidian space) than the transposed vector is the same as the original. It's merely a matter of notation,whether you write the components in row or column.
In general case there is a distinction between row vectors and column vectors however in such cases it's hard to give concise meaning to the word "angle".
Robert1986
Robert1986 is offline
#3
Nov21-12, 01:49 PM
P: 828
I don't understand the question. Usually in vector spaces like this (well Euclidean Vector Spaces), we define "angle" to be the cosine of the inner product of two vectors. However,
a vector and its transpose are not in the same space. (In the sense that one is a 1xn matrix and one is a nx1 matrix.)

arildno
arildno is offline
#4
Nov21-12, 01:51 PM
Sci Advisor
HW Helper
PF Gold
P: 12,016

Angle between vector and its transpose


I agree with Robert.
The question is meaningless.
Mark44
Mark44 is offline
#5
Nov21-12, 01:55 PM
Mentor
P: 20,962
Consider
##u = (1, 2, 3)##
and
$$u^T = \begin{pmatrix} 1 \\ 2 \\ 3\end{pmatrix}$$

Clearly the angle between the two vectors is 90
Dead Boss
Dead Boss is offline
#6
Nov21-12, 01:55 PM
P: 150
I don't think it's meaningless. In introductory classes (where vectors aren't even defined properly) rows and columns are often just different notations for components of vectors.
arildno
arildno is offline
#7
Nov21-12, 02:13 PM
Sci Advisor
HW Helper
PF Gold
P: 12,016
Quote Quote by Mark44 View Post
Consider
##u = (1, 2, 3)##
and
$$u^T = \begin{pmatrix} 1 \\ 2 \\ 3\end{pmatrix}$$

Clearly the angle between the two vectors is 90
arildno
arildno is offline
#8
Nov21-12, 02:14 PM
Sci Advisor
HW Helper
PF Gold
P: 12,016
Quote Quote by Dead Boss View Post
I don't think it's meaningless. In introductory classes (where vectors aren't even defined properly) rows and columns are often just different notations for components of vectors.
In such classes, the word "transpose" ought to be banned. THAT word should be introduced AFTER proper definition of a vector.
newphysist
newphysist is offline
#9
Nov21-12, 02:32 PM
P: 12
Assuming that question is meaningless, what is the intuition behind taking transpose?
arildno
arildno is offline
#10
Nov21-12, 02:46 PM
Sci Advisor
HW Helper
PF Gold
P: 12,016
Quote Quote by newphysist View Post
Assuming that question is meaningless, what is the intuition behind taking transpose?
You transpose, in order to make the transpose.
It is a well-defined matrix operation.
Robert1986
Robert1986 is offline
#11
Nov21-12, 03:25 PM
P: 828
Quote Quote by newphysist View Post
Assuming that question is meaningless, what is the intuition behind taking transpose?
Are you familiar with the dot product? Well, this can be written like [itex]v^\top w[/itex]. If you have some vector [itex]v[/itex] then the matrix that projects onto that vector is given by [itex]vv^\top[/itex] (if you don't understand what projection means, that's OK, but this example probably doesn't make sense.)

Additionally, there are important classes of matricies that are defined using transpose (or complex conjugate transpose which is where you do the transpose and take the complex conjugates of the entries of your matrix, if your matrix has real entries then obviously the complex conjugate transpose is just the transpose.)

For example, if [itex]Q^\top=Q^{-1}[/itex] the matrix is called orthogonal. These matrices preserve angles and lengths of vectors. These are good for numerical applications for that reason, but also it is MUCH easier to compute the transpose than it is to compute the inverse (in a sense, you don't need to "compute" the transpose, your code just needs to "iterate backward" - if you don't understand that part, its OK.)

Another special class is Symmetric Matrices where [itex]M[/itex] is symmetric if [itex]M=M^\top[/itex]. These are really nice for several reasons. First, they are diagonalisable by an orthogonal matrix. Since they are diagonalisable, there is an eigenbasis and so you can do a "spectral resolution." Also, the eigenvalues are all real, even if the entries are complex.

This is just *very light* scratching the surface, but there are MANY important topics that involve transposes of matrices and vectors.
newphysist
newphysist is offline
#12
Dec5-12, 05:49 PM
P: 12
Quote Quote by Robert1986 View Post
Are you familiar with the dot product? Well, this can be written like [itex]v^\top w[/itex]. If you have some vector [itex]v[/itex] then the matrix that projects onto that vector is given by [itex]vv^\top[/itex].
Can you please explain what you mean by above projection example or did you switch [itex]v[/itex] and [itex]w[/itex]? I don't see any use of [itex]w[/itex] in your logic.

Thanks
MarneMath
MarneMath is offline
#13
Dec5-12, 08:50 PM
P: 422
It's two different examples. The first is an alternative definition for the dot product (that I believe only applies to column vectors, someone correct me if I'm wrong), the second is an orthogonal projection onto a line. To verify this, take two unit vectors and perform the operation described and draw them!
Robert1986
Robert1986 is offline
#14
Dec6-12, 04:36 AM
P: 828
The projection of [itex]w[/itex] onto [itex]v[/itex] is given by [itex](v\circ w)v[/itex] which is equal to [itex](v^\top w)v[/itex] which is equal to [itex](vv^\top)w[/itex]. That is, [itex]vv^\top[/itex] is the projection matrix. Note that I have assumed that [itex]v[/itex] has unit length.
HallsofIvy
HallsofIvy is offline
#15
Dec6-12, 09:10 AM
Math
Emeritus
Sci Advisor
Thanks
PF Gold
P: 38,879
Quote Quote by Dead Boss View Post
I don't think it's meaningless. In introductory classes (where vectors aren't even defined properly) rows and columns are often just different notations for components of vectors.
What kind of "introductory class" are you talking about? Every introductory linear algebra class I heard of defines vectors quite clearly. And if you mean physics classes where they just give vectors as "rows and columns", it still is meaningless to talk about "angles" between them. More rigorously the "transpose" of a vector, v, is its "dual" which is not even in the same vector space as v.
Vargo
Vargo is offline
#16
Dec6-12, 11:18 AM
P: 350
Meaningless is a strong word that probably does not help the OP much. To most non-mathematicians who use vectors, the the dual space is implicitly identified with the original space via the dot product. "Vectors" are written either as rows or columns depending on convenience. Why do so many people want to "ban" people from using reasonable notation just because they aren't versed with abstract mathematics? It's like being against differentials, or implicit functions, or Leibniz notation.
HallsofIvy
HallsofIvy is offline
#17
Dec6-12, 12:46 PM
Math
Emeritus
Sci Advisor
Thanks
PF Gold
P: 38,879
Using that interpretation, you are saying that a "vector" and its "transpose" are just different ways of writing the same vector so the "angle between them" is necessarily 0.

(Of course "identifying the dual space with the original space via the dot product" depends on the choice of basis so still doesn't have any meaning as a property of the vector space itself.

Oh, and "differentials", "implicit functions", and "Leibniz notation" all have very specific, rigorous, mathematical definitions.)
micromass
micromass is offline
#18
Dec6-12, 12:53 PM
Mentor
micromass's Avatar
P: 16,545
Quote Quote by Vargo View Post
Meaningless is a strong word that probably does not help the OP much. To most non-mathematicians who use vectors, the the dual space is implicitly identified with the original space via the dot product. "Vectors" are written either as rows or columns depending on convenience. Why do so many people want to "ban" people from using reasonable notation just because they aren't versed with abstract mathematics? It's like being against differentials, or implicit functions, or Leibniz notation.
If you are solving a problem and if you eventually have to find the angle between a column and a row vector, then this is a strong indication that you have done something wrong. Using rigorous notation is useful because it prevents people from making mistakes.

Also, notation that is "reasonable" for one person might not be understandable for another person. We should teach standard notation that can be understood by everybody and not just by the person who invented it.


Register to reply

Related Discussions
Calculate a vector wich forma an angle alpha with another vector Precalculus Mathematics Homework 2
Calculate the angle between the displacement vector and the force vector Introductory Physics Homework 3
Matrix Vector Transpose Calculus & Beyond Homework 0
Curl of the transpose of a gradient of a vector: demonstration of an identity Differential Geometry 15
Conjugate Transpose for a vector Advanced Physics Homework 14