How to find orthogonal vectors?

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    Orthogonal Vectors
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Homework Help Overview

The discussion revolves around finding orthogonal vectors in R^6, specifically how to determine a vector whose dot product with a given vector vanishes. The original poster expresses uncertainty about extending their understanding from two-dimensional vectors to six-dimensional vectors.

Discussion Character

  • Exploratory, Assumption checking, Problem interpretation

Approaches and Questions Raised

  • Participants explore various methods to find orthogonal vectors, including the use of dot products and generalizations from lower dimensions. Some suggest using specific component choices to satisfy the orthogonality condition.

Discussion Status

The discussion includes multiple perspectives on how to approach the problem, with some participants providing alternative methods and examples. There is no explicit consensus, but several productive directions have been suggested, including generalizations and specific component selections.

Contextual Notes

Participants note the dimensionality of the problem and the freedom in choosing components for the orthogonal vector, highlighting the complexity of extending concepts from lower dimensions to higher dimensions.

meteorologist1
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Hi, this might be very easy, but I forgot how to do the following: I have a vector in R^6: (x1, x2, x3, x4, x5, x6). How do I find a vector such that their dot product vanishes? I know how to do it for the two dimensional case: (x1, x2), so the vector that is perpendicular to it is c(-x2, x1) where c is a scalar. Could someone show me how to do it for the vector in R^6 case?
 
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Take the cross product of your vector and any other vector that has the same origin (any unit vector usually fits the bill and is easiest since only one axis is non-zero).
 
Ok I see. I'm not sure how to do a cross product for a six-component vector though. Could you please show me?
 
The only condition on the vector is that its dot product with x vanishes?

Just solve

[tex]\vec{x}\cdot\vec{y} = 0[/tex]

--J
 
Given a vector in n-dimensions, there is a whole (n-1)-dimensional hyperplane of vectors that are orthogonal to that vector.

Let me do the 4D-case. The 6D-case is easily obtained by generalizing.
Given V=(x1,x2,x3,x4), choose W=(w1,w2,w3,w4) such that
0=(V dot W)=x1w1+x2w2+x3w3+x4w4.

One choice is w1=-x2, w2=x1, w3=0, w4=0. (This is a generalization of your 2D example).

Basically, you can choose values for three components of W. The fourth is determined by the requirement that 0=(V dot W).
 
since someone has already posted the answer... I will show you another alternative method for this problem

let's say you have vector x in R^n, and want to find a vector y orthogonal to it
we know the dot product of these two vector must be zero

[tex]\vec{x} \cdot \vec{y} = 0[/tex]

[tex]\Rightarrow x_{1} y_{1} + x_{2} y_{2} + x_{3} y_{3} + ...+ x_{n-1} y_{n-1} + x_{n} y_{n} = 0[/tex]

[tex]\Rightarrow x_{1} y_{1}+ x_{2} y_{2} + x_{3} y_{3} + ...+ x_{n-1} y_{n-1} = - x_{n} y_{n}[/tex]

[tex]\Rightarrow y_{n} = -(x_{1} y_{1} + x_{2} y_{2} + x_{3} y_{3} +...+ x_{n-1} y_{n-1}) / x_{n}[/tex]

now, you have more freedom to vary [itex]y_{1}.y_{2}...y_{n-1}[/itex] , as long as you the [itex]y_{n}[/itex] follows the formulas above :biggrin:
 
If you know how to do it with 2 dim vectors, just take a vector with all except two components 0 and fix the other 2 to give a 0 dot product!

For example, to find a vector orthogonal to <1, -3, 4, 1 , -1, 2>, take all except the first two components 0, take the first two 3 and 1 respectively: <3, 1, 0, 0, 0, 0>.

Of course, there are many independent vectors orthogonal to a given six dimensional vector (not true in 2 dimensions). You could also choose to make all except the first and last components 0: <2, 0, 0, 0, 0, -1>.

OR <0, 4, 3, 0, 0, 0>

OR ...
 
All right thanks all.
 

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