Projections and Planes
Chapter 4 • Section 4-2
"Shadows and Surfaces... where geometry meets algebra! 📐"
⚫ The Dot Product
Definition
For $\vec{u} = (u_1, \dots, u_n)$ and $\vec{v} = (v_1, \dots, v_n)$:
Properties
- $\vec{u} \cdot \vec{v} = \vec{v} \cdot \vec{u}$ (Commutative)
- $\vec{u} \cdot (\vec{v} + \vec{w}) = \vec{u} \cdot \vec{v} + \vec{u} \cdot \vec{w}$ (Distributive)
- $(k\vec{u}) \cdot \vec{v} = k(\vec{u} \cdot \vec{v})$ (Associative)
- $\vec{u} \cdot \vec{u} = \norm{\vec{u}}^2 \geq 0$
Geometric Meaning
The dot product relates to the angle $\theta$ between vectors:
If $\vec{u} \cdot \vec{v} = 0$, the vectors are orthogonal (perpendicular).
Example: Orthogonality
Are $\vec{u}=(1, -2, 3)$ and $\vec{v}=(4, 5, 2)$ orthogonal?
Yes, they are orthogonal!
Angle Calculator
Projections
The projection of $\vec{u}$ onto $\vec{d}$ is the "shadow" of $\vec{u}$ on the line along $\vec{d}$.
Example: Shortest Distance to a Line
Find the shortest distance from point $P(3, 2, -1)$ to the line $L$ passing through $P_0(2, 1, 3)$ with direction $\vec{d}=(3, -1, -2)$.
- Vector $\vec{v} = \overrightarrow{P_0P} = (3-2, 2-1, -1-3) = (1, 1, -4)$.
- Projection $\vec{w} = \proj_{\vec{d}} \vec{v} = \frac{\vec{v} \cdot \vec{d}}{\norm{\vec{d}}^2}
\vec{d}$.
$\vec{v} \cdot \vec{d} = 1(3) + 1(-1) + (-4)(-2) = 10$.
$\norm{\vec{d}}^2 = 9 + 1 + 4 = 14$.
$\vec{w} = \frac{10}{14}(3, -1, -2) = \frac{5}{7}(3, -1, -2)$. - Distance is $\norm{\vec{v} - \vec{w}}$. (Calculation omitted for brevity, but it's the length of the orthogonal component).
Planes in $\mathbb{R}^3$
Scalar Equation
A plane with normal vector $\vec{n} = (a, b, c)$ passing through point $P_0(x_0, y_0, z_0)$ has the equation:
or $ax + by + cz = d$
Example: Shortest Distance to a Plane
Find the distance from $P(2, 3, 0)$ to the plane $5x + y + z = -1$.
Formula: $D = \frac{|ax_0 + by_0 + cz_0 - d|}{\sqrt{a^2 + b^2 + c^2}}$
🧠 Knowledge Check Win $15
Find the equation of the plane passing through $(1, 0, 0)$ with normal vector $\vec{n} = (2, 3, -1)$.