How Do Squared Vector Components Relate to the Dot Product?

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Oblio
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This technically a homework question, but needed for homework and understanding for homework to come. Just hope to get it cleared up, thanks again!

1. This formula is given:

r[tex]_{1}[/tex]s[tex]_{1}[/tex] + r[tex]_{2}[/tex]s[tex]_{s}[/tex]+ r[tex]_{e}[/tex]s[tex]^{3}[/tex] = [tex]\sum[/tex]r[tex]_{n}[/tex]s[tex]_{n}[/tex] (with the limits etc. not too important).

Then, in respect to scalar products, the magnitude of any vector is denoted by l r l or by Pythoagora's theorem: square root of[r(1)[tex]^{2}[/tex] + r(2)[tex]^{2}[/tex] + r(3)[tex]^{2}[/tex]]
(couldn't find square root in latex)

and that THAT is the same as square root of [r . r]
This last step I do not follow...
 
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I know that it's true, (in reading my text) but how does 3 squared terms boil down to r^2?
 
This is a vector operation.

One squares the corresponding vector components represented in each of three dimensions, which are orthogonal in the Cartesian system.

The magnitude r is given as the sqrt of the sum of the squares, i.e. r = sqrt (r12 + r22 + r32), so

r2 = r12 + r22 + r32
 
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Oblio said:
I know that it's true, (in reading my text) but how does 3 squared terms boil down to r^2?

See [tex]\vec{r}\cdot\vec{r}[/tex] is nothing but [tex]\sca{r}\sca{r}\cos\theta[/tex]. But [tex]\theta[/tex] = 0 and so [tex]\cos\theta[/tex] = 1.

Hence [tex]\vec{r}\cdot\vec{r}[/tex] = [tex]^{}r^2[/tex]

Now a projection of a vector on an axis is known as the component of the vector on that axis. So take a cartesian system and draw any arbritary vector and drop perpendiculars on the x y and z axis. Now try using pythagoras theorem for this and you will see that how

[tex]\sca{r^2}[/tex] = [tex]\sqrt{r^2_x + r^2_y + r^2_z}[/tex]