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Using the definition of a dot-product as the sum of the products of the various components, how do you prove that the dot product will remain the same when the coordinate system rotates?

Preferably an intuitive proof please, explainable to a high-school student. Thanks in advance.

Kevin
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2 Answers2

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If $v$ and $u$ are vectors then the dot product is $vu^t$ or equivalently $v^tu$, $uv^t$ or $u^tv$ where $x^t$ is the transpose of $x$, i.e. switch the rows and columns, so that

$$(x_1, x_2, x_3, ...)^t = \begin{pmatrix} x_1\\ x_2\\ x_3\\ .\\ .\\ \end{pmatrix}$$ and the dot product of $u$ and $v$ is then seen to be

$$(u_1, u_2, u_3, ...)\begin{pmatrix} v_1\\ v_2\\ v_3\\ .\\ .\\ \end{pmatrix} = u_1v_1 + u_2v_2+ u_3v_3 + \ldots$$

If you now rotate the coordinate system with a rotation matrix $R$ then the components of a vector $u$ become $uR$, and he components of the transposed vector $v^t$ become $R^tv^t$ (where $R^t$ is the transpose of $R$ given by $R^t_{i, j} = R_{j, i}$), so that the dot product in the new coordinates is $uRR^tv^t$.

A property or rotations is that their matrices are orthogonal and their transpose is equal to their inverse so that $R^t = R^{-1}$, so the scalar product is = $uRR^{-1}v^t$ and $RR^{-1} = I$ (the identity matrix), so that $uRR^tv^t = uRR^{-1}v^t = uIv^t = uv^t$, i.e. the dot product is invariant under rotation.

That may be a bit much at high school level, so perhaps a demonstration in 2-D would help.

A rotation matrix has the form

$$\begin{pmatrix} \cos\theta& -\sin\theta\\ \sin\theta & \cos\theta \end{pmatrix}$$ where $\theta$ is the angle of rotation.

$u$ rotated is $$(u_x, u_y)\begin{pmatrix} \cos\theta& -\sin\theta\\ \sin\theta & \cos\theta \end{pmatrix} = ([u_x]\cos\theta + u_y \sin\theta], [-u_x\sin\theta + u_y\cos\theta])$$ and similarly for $v$, so that $$uv^t = ([u_x\cos\theta +u_y\sin\theta]\cdot[v_x \cos\theta + v_y \sin\theta] + [-u_x\sin\theta + u_y\cos\theta]\cdot[-v_x\sin\theta + v_y\cos\theta])$$

and when you multiply it out and gather the terms you end up with $(u_xv_x + u_yv_y)(\cos^2\theta + \sin^2\theta)$, i.e. the same $(u_xv_x + u_yv_y)$ as you have without the rotation.

Tom Collinge
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  • thanks for your answer! could you explain how the 2d rotation matrix works, as in the reasoning behind it? I know how the points [1,0] and [0,1] get transformed into [cos0,sin0] and [-sin0,cos0], but don't understand why that works for general poitns I've been trying to figure it out for a few hours now, but haven't been able to. – Kevin Sep 27 '14 at 10:02
  • @Kevin Here's a link that should help https://engineering.purdue.edu/~bethel/rot2.pdf (note that in this example the vectors are shown as columns rather than rows). – Tom Collinge Sep 27 '14 at 11:51
  • Isn't transformation of $u$ is $Ru$ instead of $uR$? – AvidSeeker Mar 30 '22 at 16:48
  • @AvidSeeker It depends if you write your vectors as rows or columns. In the Wiki entry https://en.wikipedia.org/wiki/Rotation_matrix they are using columns and the $Ru$ is correct. Here though I'm using rows and $uR$ is correct. – Tom Collinge Mar 31 '22 at 07:44
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First you should show that for any two vectors $v$ and $w$ in $\mathbb{R}^n$ (taking $n=3$ if necessary) $v\cdot w = |v||w|\operatorname{cos}\theta $, where $\theta$ is the (smaller) angle between both vectors.

This is a very geometric fact and you can probably prove it to them if they know the cosines law. First observe that:

$$||v-w||^2 = ||v||^2+||w||^2-2||v||w||\operatorname{cos}\theta.$$

This comes from the the fact that the vectors $v$, $w$ and $(v-w)$ form a triangle (draw it). On the other hand,

$$||v-w||^2 = (v-w)\cdot(v-w)=v\cdot v -2v\cdot w + w\cdot w .$$

The result follows immediately. After this you only need to observe that rotations don't affect lenghts or angles, then by the formula above the dot product is invariant under rotations.

hjhjhj57
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  • Thanks, what about using the definition of dot-product as the product of various components? – Kevin Sep 27 '14 at 07:51
  • You're actually using it in the last equality as you use it to show the dot product is commutative and distributive. Also to define the length of a vector with it. – hjhjhj57 Sep 27 '14 at 07:54