Parallel and perpendicular components

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Discussion Overview

The discussion revolves around the decomposition of a vector into its parallel and perpendicular components relative to a subspace spanned by two vectors, using methods such as Gram-Schmidt orthogonalization. Participants explore various approaches, mathematical formulations, and the implications of orthogonality in their calculations.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant presents a method using Gram-Schmidt orthogonalization to find the parallel and perpendicular components of a vector, but encounters unexpected non-zero scalar products indicating a failure in achieving orthogonality.
  • Another participant notes that the Gram-Schmidt method assumes previous vectors are orthogonal, which is not the case here, suggesting a need to reapply the algorithm from scratch.
  • A participant questions whether the correct procedure involves normalizing and subtracting components in a specific order, indicating uncertainty about the method's application.
  • Another participant emphasizes the geometric interpretation of the projection of the vector onto the plane spanned by the two vectors and suggests using an orthogonal basis derived from Gram-Schmidt for accurate results.
  • An alternative approach is proposed involving the cross product of the two vectors to find a vector perpendicular to the plane, which could help in determining the perpendicular component.
  • A later reply shares a successful outcome after applying the Gram-Schmidt method to create an orthogonal basis, indicating that the proposed strategies can lead to correct results.

Areas of Agreement / Disagreement

Participants express differing views on the correct application of the Gram-Schmidt method and the implications of orthogonality, with no consensus reached on a single approach. Some participants agree on the need for orthogonalization, while others explore alternative methods.

Contextual Notes

The discussion highlights limitations related to the assumptions of orthogonality in the initial vectors and the dependence on the correct application of the Gram-Schmidt process. Unresolved mathematical steps and the specific conditions under which the methods are applied are also noted.

Portuga
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TL;DR
Consider the following vectors of ##\mathbb{V}^{3}##: ##u=\left(2,2,2\right)##
and ##v=\left(3,3,1\right)##. If ##w=\left(-5,1,-1\right)##, decompose
the vector ##v## into a component in ##W=\left[u,w\right]## and a component
in ##W^{\perp}##.
I first tried to use a method based on Gram Schmidt orthogonalization
method:
$$
v_{\parallel}=\left(v\ldotp\frac{u}{\left\Vert u\right\Vert }\right)\frac{u}{\left\Vert u\right\Vert }+\left(v\ldotp\frac{w}{\left\Vert w\right\Vert }\right)\frac{w}{\left\Vert w\right\Vert },
$$
and
$$
v_{\perp}=v-v_{\parallel}.
$$
Results were
$$
v_{\parallel}=\left(\frac{128}{27},\frac{50}{27},\frac{76}{27}\right)
$$
and
$$
v_{\perp}=\left(-\frac{47}{27},\frac{31}{27},-\frac{49}{27}\right).
$$
At first sight, things looked ok, because ##v_{\parallel}+v_{\perp}=v##,
but when I performed the scalar product between ##v_{\perp}## and ##u##
and ##w##, both resulted non null:
$$
v_{\perp}\ldotp u=-\frac{130}{27}
$$
and
$$
v_{\perp}\ldotp w=\frac{35}{3}.
$$
This was totally unespected to me because ##v_{\perp}## was designed
to be perpendicular to the subspace spanned by ##u## and ##w##, and
as so, these scalar products should result 0.

Then I tried a slight deviation from the previous method:
$$
v_{\parallel}=\left[v\ldotp\frac{\left(u+w\right)}{\left\Vert u+w\right\Vert }\right]\frac{\left(u+w\right)}{\left\Vert u+w\right\Vert }=\left(-\frac{3}{19},\frac{3}{19},\frac{1}{19}\right)
$$
and
$$
v_{\perp}=v-v_{\parallel}=\left(\frac{60}{19},\frac{54}{19},\frac{18}{19}\right).
$$
Again,
$$
v_{\perp}\ldotp u=\frac{264}{19}
$$
and
$$
v_{\perp}\ldotp w=-\frac{264}{19}.
$$
But, there was an advance:
$$
v_{\perp}\ldotp\left(u+w\right)=0.
$$
So, what am I doing wrong on all this? Am I missing something?
 
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Gram Schmidt goes step by step constructing an orthogonal set of vectors, but it assumes you did the right thing on the previous vectors on each step. Here, u and w are not orthogonal, so you can't orthogonalize the third vector immediately. You could run the algorithm from scratch on the set of u,w,v and do two iterations.
 
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I should subtract first component, normalize and then subtract the other one, and normalize it?
 
Portuga said:
I should subtract first component, normalize and then subtract the other one, and normalize it?

This is a little too vague for me to know if you're proposing the right thing.
 
@Portuga, can I add a few thoughts to what @Office_Shredder has said…

Thinking geometrically, ##v_{\parallel}## is simply the projection of ##v## onto the plane (P) spanned by ##u## and ##w##. Not too hard to visualise.

Your equation
##v_{\parallel}=\left(v\ldotp\frac{u}{\left\Vert u\right\Vert }\right)\frac{u}{\left\Vert u\right\Vert }+\left(v\ldotp\frac{w}{\left\Vert w\right\Vert }\right)\frac{w}{\left\Vert w\right\Vert }##
would give you ##v_{\parallel}## if ##u## and ##w## were orthogonal - but they aren’t!

You can find an orthogonal basis for ##[u,w]## using the Gram Schmidt method. And then you can use the above equation but with the orthogonal basis vectors.

An alternative approach would be to start by finding the cross product ##u \times w##. This is a vector perpendicular to P so it allows you to find ##v_{\perp}##.
 
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ok, thank you all very much!
 
Portuga said:
ok, thank you all very much!
You're welcome.
What did you get for results, and what method did you use?

After giving help, we're often curious as to the outcome.
 
I followed the trick of Gram Schmidt ortogonalization method to build an ortogonal basis ##\left\{ u^{\prime},w^{\prime}\right\}## for ##W## and the strategy of decomposing ##v## as ##v_{\parallel}=v\ldotp u^{\prime}u^{\prime}+v\ldotp w^{\prime}w^{\prime}## and ##v_{\perp}=v-v_{\parallel}##. It worked like a charm! Thank you all very much.
 
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