Orthogonal operator and reflection

In summary, the conversation discusses the use of a linear operator ##F_n##, called the reflection on ##V## along the direction of ##n##, in solving two questions. In the first question, a unit vector ##n## is found such that ##F_n(S(w))=w##, where ##S## is an orthogonal linear operator on ##V## and ##W = \left\{u \in V | S(u) = u\right\}##. In the second question, it is proven that ##W \subsetneq E_1(F_n \circ S)##, where ##n## is the unit vector obtained in the first question and ##E_1(F_n \circ S)
  • #1
drawar
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Homework Statement


Let ##n## be a unit vector in ##V## . Define a linear operator ##F_n## on ##V## such that
$$F_n(u) = u-2\langle u, n \rangle n \; \mathrm{for} \; u \in V.$$
##F_n## is called the reflection on ##V## along the direction of ##n##. Let ##S## be an orthogonal linear operator on ##V## and let ##W = \left\{u \in V | S(u) = u\right\}##. Suppose ##W^\perp## is not empty and ##w## is a nonzero vector in ##W^\perp##.

(a) Find a unit vector ##n## such that ##F_n(S(w))=w##.

(b) Prove that ##W \subsetneq E_1(F_n \circ S)##, where ##n## is the unit vector obtain in (a) and ##E_1(F_n \circ S)## denotes the eigenspace of ##F_n \circ S## associated with 1.

Homework Equations


##S## is orthogonal iff ##||S(u)||=||u||## for all ##u \in V##

The Attempt at a Solution


Okay I admit I have no idea how to do either of the questions but I would really appreciate some help to do (a) because without getting it done first, I wouldn't be able to proceed to (b). So right now all I can do for (a) is writing down the equation I'm supposed to solve, hoping something useful would pop up and lead me straight to the answer but it doesn't seem that easy:
$$S(w)-2 \langle S(w),n \rangle n = w.$$
Honestly I'm stuck at here, is there any way I can do about it?
 
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  • #2
Perhaps not the best way but: what is ##F_n^2##, how can (a) be restated? And is there a way to recover n knowing v and ##F_n(v)##?
 
  • #3
bloby said:
Perhaps not the best way but: what is ##F_n^2##, how can (a) be restated? And is there a way to recover n knowing v and ##F_n(v)##?

##F_n^2=I##, so the equation in (a) reduces to ##S(w)=F_n(w)## (- I guess this requires ##F_n## to be bijective or at least injective but I don't know how to prove it). From here ##n## can be found by subtracting ##F_n(w)## (or equivalently ##S(w)##) from ##w## followed by a normalization. Does that sound ok?
 
  • #4
drawar said:
(- I guess this requires ##F_n## to be bijective or at least injective but I don't know how to prove it).

Yes. Either verify the solution found or simply use the definition of injective.

drawar said:
From here ##n## can be found by subtracting ##F_n(w)## (or equivalently ##S(w)##) from ##w## followed by a normalization. Does that sound ok?

Yes.

Is the part (b) ok?
 
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  • #5
bloby said:
Is the part (b) ok?

No, unfortunately. Would appreciate further hints if possible!
 
  • #6
I gave perhaps too much hints for (a): it's not magical trick, I just figured out what ##F_n## does on a vector in ##\mathbb R^3##, (do a sketch) hence the name and the intuitions.

For (b) there are two things to prove: ##W \subset E_1(F_n \circ S)## and there is a vector ##\not\in W## that belongs to ##E_1(F_n \circ S)##.

What does it means for a vector v to be in ##E_1(F_n \circ S)##?
 
  • #7
bloby said:
I gave perhaps too much hints for (a): it's not magical trick, I just figured out what ##F_n## does on a vector in ##\mathbb R^3##, (do a sketch) hence the name and the intuitions.

For (b) there are two things to prove: ##W \subset E_1(F_n \circ S)## and there is a vector ##\not\in W## that belongs to ##E_1(F_n \circ S)##.

What does it means for a vector v to be in ##E_1(F_n \circ S)##?

##E_1(F_n \circ S)=\left\{w \in V|F_n(S(w))=w\right\}##. ##W \subset E_1(F_n \circ S)## is because of the fact that ##S## is orthogonal. It remains to find a vector that ##\not\in W## but belongs to ##E_1(F_n \circ S)##, which is nothing but ##w##.
 
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  • #8
drawar said:
##E_1(F_n \circ S)=\left\{w \in V|F_n(S(w))=w\right\}##. ##W \subset E_1(F_n \circ S)## is because of the fact that ##S## is orthogonal. It remains to find a vector that ##\not\in W## but belongs to ##E_1(F_n \circ S)##, which is nothing but ##w##.

Yes, yes, and the definition of W and the fact that ##w## of (a) belongs to ##W^\perp##
 
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  • #9
Yeah, that also. Thanks for being so patient with me. I really appreciate your instructive help and guidance.
 
  • #10
You're welcome :smile:
 

Related to Orthogonal operator and reflection

1. What is an orthogonal operator?

An orthogonal operator is a linear transformation that preserves the length and angle between vectors. It can also be defined as a matrix with orthogonal columns and rows.

2. How is an orthogonal operator different from a non-orthogonal operator?

An orthogonal operator preserves the length and angle between vectors, while a non-orthogonal operator does not. This means that an orthogonal operator maintains the shape and orientation of a vector, while a non-orthogonal operator can change it.

3. What is the purpose of using orthogonal operators?

Orthogonal operators are useful in many mathematical and scientific fields, such as computer graphics, physics, and engineering. They allow for efficient and accurate transformations of vectors without distorting their properties.

4. What is the relationship between orthogonal operators and reflections?

Orthogonal operators can be used to perform reflections, as they preserve the length and angle between vectors. In fact, a reflection can be seen as a special case of an orthogonal transformation where the determinant of the transformation matrix is -1.

5. How are orthogonal operators and reflections used in real-life applications?

Orthogonal operators and reflections are used in various applications, such as image processing, robotics, and data compression. They can also be seen in everyday objects, such as mirrors, which reflect light using the principles of reflection and orthogonal transformations.

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