Proving Vector Orthogonality in R^3

In summary: \vec{v}\times\left(\vec{v}\times\vec{u}\right)= \left|\begin{array}{ccc} \vec{i} & \vec{j} & \vec{k} \\ 0 & b & 0 \\ 0 & 0 & a\end{array}\right|and\vec{u}\times\left(\vec{v}\times\left(\vec{v}\times\left(\vec{v}\times\vec{u}\right)\right)\right)= \left|\begin{array}{ccc} \vec{i} & \vec{j} & \vec{k} \\ a & 0 & 0 \\ 0 & b &
  • #1
mjstyle
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Homework Statement


a) Let v be a unit vector in R^3 and u be a vector which is orthogonal to v. Show v x (v x u) = -u
b) Let v and u be orthogonal unit vectors in R^3. Show u x (v x (v x (v x u))) = -v


Homework Equations





The Attempt at a Solution



I am very lost in this question, I know a unit vector is = 1 therefore the summuation of the vector v is 1 for example, v = (1,0,0). square root(1^2 + 0 + 0) = 1 and i know u dot v is 0 but how do i start the prove?

thank you
 
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  • #2
Apply the http://en.wikipedia.org/wiki/Triple_product" for the first one then simplify. Do it repeatedly for the second.
 
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  • #3
That's one way to do it - the other is to think about the geometry. You know that u and v are orthogonal, so that u,v, vxu are all orthogonal, hence you know that vx(vxu) is parallel to u (since it is orthogonal to both v and vxu). What about its length? Again, just think about the geometric meaning. You should be able to show that vx(vxu) has length 1. Now you just need to consider if that means it is u or -u.
 
  • #4
Since those equations are independent of choice of axes, it would be perfectly valid to choose you coordinate system so that u is pointing along the x-axis and v along the y-axis.

That is, assume that u= <a, 0, 0> and v= <0, b, 0> in the first problem and u= <1, 0, 0>, v= <0, 1, 0> in the other. Now use
[tex]\vec{u}\times\vec{v}= \left|\begin{array}{ccc}\vec{i} & \vec{j} & \vec{k} \\ a & 0 & 0 \\0 & b & 0\end{array}\right|[/tex]
 

What is the definition of vector orthogonality in R^3?

Vector orthogonality in R^3 refers to two vectors that are perpendicular to each other in three-dimensional space. This means that the dot product of the two vectors is equal to zero.

How do you prove vector orthogonality in R^3?

To prove vector orthogonality in R^3, you can use the dot product formula: A · B = |A||B|cosθ, where A and B are the two vectors and θ is the angle between them. If the dot product is equal to zero, then the vectors are orthogonal.

What is the significance of vector orthogonality in R^3?

Vector orthogonality in R^3 is important in many areas of mathematics and physics. It allows us to easily calculate angles and distances between vectors, and it is also used in applications such as computer graphics and engineering.

Can two vectors be orthogonal in R^3 but not in R^2?

Yes, two vectors can be orthogonal in R^3 but not in R^2. This is because in R^2, the vectors lie on a two-dimensional plane and can only be perpendicular to each other in one direction. In R^3, the vectors can have different directions and still be perpendicular to each other.

Are all vectors in R^3 orthogonal to each other?

No, not all vectors in R^3 are orthogonal to each other. In fact, most vectors in R^3 are not orthogonal. Two vectors are only orthogonal if their dot product is equal to zero, which is a special case.

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