Construct & Normalize Orthogonal Vector to \underline{a}, \underline{b}

In summary, to construct a third vector orthogonal to the given pair and normalize all three vectors, use the equations c.a=0 and c.b=0, where c=(x y z). When dealing with complex vectors, use the complex conjugate of the first vector before multiplying the components. Another method would be to use a cross product, but it should be noted that the cross product is specifically defined for three real dimensional vectors, and may not work with complex vectors. Solving the linear equations is another option.
  • #1
Grand
76
0

Homework Statement


Construct a third vector which is orthogonal to the following pair and normalize all three vectors:
[tex]\underline{a}=(1-i,1,3i), \underline{b}=(1+2i,2,1)[/tex]


Homework Equations


[tex]\underline{c}.\underline{a}=0[/tex] and [tex]\underline{c}.\underline{b}=0[/tex] where c=(x y z)


The Attempt at a Solution

 
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  • #2
Your relevant equations are a good start, so use them.
 
  • #3
The question is, how do we make a dot product when the vectors are complex? Is it the same way as real vectors or not?
 
  • #5
Mark44 said:
Do it the same way.

Not exactly. You take the complex conjugate of the first vector before you multiply the components. Otherwise <x,x>>=0 doesn't work.
 
  • #6
Dick said:
Not exactly. You take the complex conjugate of the first vector before you multiply the components. Otherwise <x,x>>=0 doesn't work.

I'm not familiar with complex vectors, but since you want a vector that is orthogonal to both, rather than trying two dot products, wouldn't it be prudent to use a cross product?
 
  • #7
That would be the method I would choose, but as Dick says, the only difference in dot product with complex components is that you use the complex conjugates of the components of one vector.
 
  • #8
HallsofIvy said:
That would be the method I would choose, but as Dick says, the only difference in dot product with complex components is that you use the complex conjugates of the components of one vector.

I think that difference is important. I think if you take the usual definition of 'cross-product' with the complex notion of dot product, it isn't true that the cross product is orthogonal to the vectors in the product. The cross product is pretty specifically three real dimensional. C^3 isn't really three dimensional in that sense. I think you should just solve the linear equations.
 

FAQ: Construct & Normalize Orthogonal Vector to \underline{a}, \underline{b}

What does it mean to construct and normalize an orthogonal vector?

Constructing and normalizing an orthogonal vector means finding a vector that is perpendicular to two given vectors, and then scaling it to have a magnitude of 1. This process is used in linear algebra and geometry to find the direction of a vector that is perpendicular to two other vectors.

Why is it important to construct and normalize an orthogonal vector?

Constructing and normalizing an orthogonal vector is important because it allows us to find a direction that is perpendicular to two given vectors. This can be useful in many applications, such as calculating the normal vector of a plane or finding the direction of maximum change in a multivariable function.

How do you construct and normalize an orthogonal vector?

To construct and normalize an orthogonal vector, you will need to find the cross product of the two given vectors. This will give you a vector that is perpendicular to both of the given vectors. Then, you can divide this vector by its magnitude to normalize it to have a magnitude of 1.

What are some applications of constructing and normalizing orthogonal vectors?

As mentioned before, constructing and normalizing orthogonal vectors can be used in various applications such as calculating the normal vector of a plane, finding the direction of maximum change in a multivariable function, and in computer graphics for lighting and shading calculations.

Can you construct and normalize an orthogonal vector for more than two given vectors?

Yes, it is possible to construct and normalize an orthogonal vector for more than two given vectors. In this case, you will need to find the cross product of all the given vectors and then normalize the resulting vector. This will give you a vector that is perpendicular to all of the given vectors.

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