Postgraduate Science

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Vectors & Coordinate Systems

Vectors, bases, dot/cross products — the algebraic backbone of physics.

A vector is a geometric object with magnitude and direction; algebraically it is a tuple of components in a chosen basis. In an orthonormal basis $\{\hat e_i\}$ of Euclidean space,

$$\mathbf v = \sum_i v_i \hat e_i, \qquad \mathbf v \cdot \mathbf w = \sum_i v_i w_i = |\mathbf v||\mathbf w|\cos\theta.$$

The cross product in $\mathbb R^3$ produces a vector perpendicular to both inputs: $\mathbf v \times \mathbf w$ has magnitude $|\mathbf v||\mathbf w|\sin\theta$ and direction by the right-hand rule.

Under a rotation $R \in SO(3)$, components transform as $v'_i = R_{ij} v_j$. This transformation law is what distinguishes a true vector from an arbitrary triple of numbers — it's the entry point to tensor analysis.

Interactive: vector addition

Drag the sliders to change the two black/tan arrows. The red arrow is their sum.

Quiz

1. Under a rotation $R \in SO(3)$, the components of a vector transform as:
2. The magnitude of $\mathbf v \times \mathbf w$ is:
3. If $\mathbf v \cdot \mathbf w = 0$ for nonzero vectors, they are:
4. For orthonormal basis vectors, $\hat e_i \cdot \hat e_j$ equals:
5. Under a parity (mirror) transformation, an axial vector like $\mathbf L = \mathbf r \times \mathbf p$: