Dot Product
Table of Contents
For two vectors \(\small \vec{a}\) and \(\small \vec{b}\) in \(\small \mathbb{R}^n\) (real coordinate spaces, the dot product is defined as
$$ \vec{a} \cdot \vec{b} = \sum_{i=1}^n a_i b_i $$
Where
- \(\small a_i\) and \(\small b_i\) are the \(\small i\)-th components of \(\small \vec{a}\) and \(\small \vec{b}\), respectively, and
- \(\small n\) is the dimension of \(\small \vec{a}\) and \(\small \vec{b}\).
Alternative definition #
Given that \(\small \vec{a}\) and \(\small \vec{b}\) are vectors with lengths \(\small |a|\) and \(\small |b|\), respectively, the dot product is also equal to
$$ \vec{a} \cdot \vec{b} = |a| |b| \cos \theta $$
Where \(\small \theta\) is the angle between \(\small \vec{a}\) and \(\small \vec{b}\).
Note that the dot product is a less general version of the inner product.
Properties #
- \(\small \vec{a} \cdot \vec{b} = \vec{b} \cdot \vec{a}\)
- \(\small (\vec{a} + \vec{b}) \cdot \vec{c} = \vec{a} \cdot \vec{c} + \vec{b} \cdot \vec{c}\)
- \(\small \vec{a} \cdot \vec{a} = |a|^2\)
- \(\small \vec{a} \cdot \vec{b} = 0\) if and only if \(\small \vec{a}\) and \(\small \vec{b}\) are orthogonal
- For a scalar s, \((\small s \vec{a}) \cdot \vec{b} = s \cdot (\vec{a} \cdot \vec{b})\)