given two complex vectors, what is the geometric interpretation of their dot product?

$$ \mathbf{x}\mathbf{y} = \sum x_i y_i^* $$

is there any interpretation similar to the case with real vectors based on projection of one vector onto another or similar?

  • 3
    $\begingroup$ Exactly the same one; in fact, the projection formulas work for this dot product/inner product just as they do for real numbers. $\endgroup$ – Arturo Magidin Jul 22 '11 at 19:10

If ${\bf x}={\bf a}+{\bf b}i$, ${\bf y}={\bf c}+{\bf d}i$ in $C^n$, define vectors ${\bf u}=({\bf a},{\bf b})$, ${\bf v}=({\bf c},{\bf d})$, ${\bf w}=(-{\bf d},{\bf c})$ in $R^{2n}$. Then $$ {\bf x}\cdot {\bf y} = {\bf u}\cdot {\bf v}+i{\bf u}\cdot {\bf w} $$ so the real and imaginary parts of ${\bf x}\cdot {\bf y}$ have exactly the geometric interpretations you are familiar with, as applied to ${\bf u}$, ${\bf v}$ and ${\bf w}$, where ${\bf w}$ is a rotation of ${\bf v}$.

But I think it is best to separate some of the concepts a bit. If we take "geometry" to refer to concepts of distance and angle, then projection goes beyond geometry because it involves linear combinations; we don't really project a vector to a vector, instead we project it to a subspace. And, while it is true that the projection of ${\bf x}$ to the span of ${\bf y}$ in $C^n$ gives the point of the subspace closest to ${\bf x}$, the word to focus on is not so much "closest" (geometry), but "subspace" (algebra).

The simplest example of this is probably in $C^1$ versus $R^2$: The projection of $x=a+bi$ onto the span of $1$ is $x$ itself. But the projection of $(a,b)$ onto the span of $(1,0)$ is $(a,0)$. In both cases you have the closest point; what has changed is the subspace rather than the concept of distance.

  • $\begingroup$ Wow! +1 Bob, do you have somewhere where I could read more into this in depth? I'm still super lost with geometrically understanding complex inner products...and most sources don't even seem to try explaining them geometrically! $\endgroup$ – Joshua Ronis Jul 12 at 20:49

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