Math 183: Toolkit 🧰 (no animations)

This toolkit contains all of the definitions, properties, facts and theorems you need to memorize all on one webpage. These are your tools on quizzes and exams.

Table of Contents

Chapter 12: Vectors and the Geometry of Space


12.1: Three-Dimensional Coordinate Systems

set

A set is a collection of objects, along with a condition of membership. We write \[A = \{\text{objects} : \text{membership condition}\}\]

If $a$ is an element of the set $S$, we write $a \in S$.

$\mathbb{R}^2$, $\mathbb{R}^3$

$\mathbb{R}$ denotes the set of all real numbers. The familiar $xy$-plane is \[\mathbb{R}^2 = \{(x, y) : x, y \in \mathbb{R}\}\]

The 3D rectangular coordinate system is \[\mathbb{R}^3 = \{(x, y, z) : x, y, z \in \mathbb{R}\}\]

Movement in each coordinate $a, b, c$ of the point $(a, b, c)$ is parallel to the $x$-, $y$-, and $z$-axis, respectively.

Right Hand Rule

There are two directions the positive $z$-axis could point. Mathematicians decided on the right hand rule: flatten your hand and point your four fingers along the $x$-axis. Curl your fingers in the shortest rotation from the $x$-axis to the $y$-axis. Then your thumb points in the direction of the positive $z$-axis.

Distance Formula in 3D

The distance between the points $P_1(x_1, y_1, z_1)$ and $P_2(x_2, y_2, z_2)$, denoted $|P_1P_2|$, is \[|P_1P_2| = \sqrt{(x_2 - x_1)^2 + (y_2 - y_1)^2 + (z_2 - z_1)^2}\]

equation of a sphere

A sphere is the set of all points $P(x, y, z)$ at distance $r$ away from the center $C(h, k, \ell)$. Its equation is \[(x - h)^2 + (y - k)^2 + (z - \ell)^2 = r^2\]

If the center is $O(0,0,0)$, then the equation is \[x^2 + y^2 + z^2 = r^2\]

12.2: Vectors


vector

A vector is a mathematical quantity with both direction and magnitude. Vectors carry no information about position.

displacement vector, equivalent vectors, zero vector

A displacement vector $\ray{AB}$ is a vector that takes you from a point $A$ to a point $B$.

Two vectors are equivalent (we write $\ray{AB} = \ray{CD}$) if they have the same direction and magnitude. Their initial points may be different, yet the vectors are equivalent.

The zero vector, denoted $\vec{0}$, is the vector with magnitude $0$. It is the one exception to the definition above: it has no assigned direction.

geometric addition of vectors

Given two vectors $\vec{u}$ and $\vec{v}$, position the tail of $\vec{v}$ on the tip of $\vec{u}$. Then $\vec{u} + \vec{v}$ is the vector from the tail of $\vec{u}$ to the tip of $\vec{v}$.

scalar multiplication

Let $c$ be a scalar and $\vec{v}$ a vector. The scalar multiple $c\vec{v}$ is the vector whose magnitude is $|c|$ times the magnitude of $\vec{v}$ and whose direction is the same as $\vec{v}$ if $c > 0$ and opposite to $\vec{v}$ if $c < 0$.

If $c = 0$ or $\vec{v} = \vec{0}$, then $c\vec{v} = \vec{0}$.

Scaling and Lines

Scaling changes magnitude and either preserves or reverses direction. Every scalar multiple of $\vec{v}$ lies along the same line. Collecting all of them at once, the set \[\left\{c\,\vec{v} : c \in \mathbb{R}\right\}\] is a line in the direction of $\vec{v}$.

subtraction of vectors

The difference of two vectors is defined as \[\vec{u} - \vec{v} = \vec{u} + (-\vec{v})\]

Think Reverse the direction of $\vec{v}$, then add normally.

If the initial points of both vectors are the same, $\vec{u} - \vec{v}$ is simply the vector from the tip of $\vec{v}$ to the tip of $\vec{u}$.

position vector

If we let the initial point of a vector $\vec{a}$ be the origin, then the terminal point has coordinates $(a_1, a_2)$ or $(a_1, a_2, a_3)$, and we write \[\vec{a} = \vc{a_1, a_2} \qquad \text{or} \qquad \vec{a} = \vc{a_1, a_2, a_3}\]

Angled brackets distinguish a vector from a coordinate $(a_1, a_2)$. These vectors are called position vectors.

finding a position vector from two points

Given points $A(a_1, a_2, a_3)$ and $B(b_1, b_2, b_3)$, the (position) vector $\vec{v}$ with representation $\ray{AB}$ is \[\vec{v} = \vc{b_1 - a_1,\ b_2 - a_2,\ b_3 - a_3}\] A vector is a difference of points (destination minus start). This is why a vector has no information about position: the difference forgets where the vector started.

vector algebra and magnitude

Let $\vec{a} = \vc{a_1, a_2, a_3}$, $\vec{b} = \vc{b_1, b_2, b_3}$ and $c \in \mathbb{R}$.

  1. The magnitude (or length) of $\vec{a}$, denoted $|\vec{a}|$, is $|\vec{a}| = \sqrt{a_1^2 + a_2^2 + a_3^2}$
  2. $\vec{a} + \vec{b} = \vc{a_1, a_2, a_3} + \vc{b_1, b_2, b_3} = \vc{a_1 + b_1,\ a_2 + b_2,\ a_3 + b_3}$
  3. $\vec{a} - \vec{b} = \vc{a_1, a_2, a_3} - \vc{b_1, b_2, b_3} = \vc{a_1 - b_1,\ a_2 - b_2,\ a_3 - b_3}$
  4. $c\vc{a_1, a_2, a_3} = \vc{ca_1,\ ca_2,\ ca_3}$
    Think To add/subtract vectors, add/subtract their corresponding components. To multiply a vector by a scalar, multiply each component by that scalar.
$V_n$, vector space

The set of all $n$-dimensional vectors is \[V_n = \left\{\vc{a_1, a_2, \dots, a_n} : a_i \in \mathbb{R}\right\}\]

$V_n$ is called a vector space: a set of vectors, together with addition and scalar multiplication, required to satisfy the 8 properties below (the vector space axioms, for those in Calculus IV).

Properties of Vectors

Let $\vec{a}, \vec{b}, \vec{c} \in V_n$ and $c, d \in \mathbb{R}$.

  1. $\vec{a} + \vec{b} = \vec{b} + \vec{a}$
  2. $\vec{a} + \vec{0} = \vec{a}$
  3. $c(\vec{a} + \vec{b}) = c\vec{a} + c\vec{b}$
  4. $(cd)\vec{a} = c(d\vec{a})$
  5. $\vec{a} + (\vec{b} + \vec{c}) = (\vec{a} + \vec{b}) + \vec{c}$
  6. $\vec{a} + (-\vec{a}) = \vec{0}$
  7. $(c + d)\vec{a} = c\vec{a} + d\vec{a}$
  8. $1\vec{a} = \vec{a}$
unit vector

A unit vector is a vector with magnitude 1. Given $\vec{a} \neq \vec{0}$, the corresponding unit vector is \[\vec{u} = \dfrac{\vec{a}}{|\vec{a}|}\]


Any vector $\vec{a} \neq \vec{0}$ can be decomposed into a product of its length and its unit direction: \[\vec{a} = \underbrace{\abs{\vec{a}}}_{\text{length}} \cdot \underbrace{\dfrac{\vec{a}}{|\vec{a}|}}_{\text{unit direction}}\]


An arbitrary vector $\vec{a} = \vc{a_1, a_2, a_3}$ can be broken up into vectors in each dimension: \begin{align} \vec{a} &= \vc{a_1, a_2, a_3} \\ &= \vc{a_1, 0, 0} + \vc{0, a_2, 0} + \vc{0, 0, a_3} \\ &= a_1\vc{1,0,0} + a_2\vc{0,1,0} + a_3\vc{0,0,1} \\ &= a_1\iv + a_2\jv + a_3\kv \end{align} where $\iv = \vc{1,0,0}$, $\jv = \vc{0,1,0}$, $\kv = \vc{0,0,1}$ are the standard basis vectors.

12.3: The Dot Product


dot product

Given two vectors $\vec{a} = \vc{a_1, a_2, a_3}$ and $\vec{b} = \vc{b_1, b_2, b_3}$, the dot product $\vec{a}\cdot\vec{b}$ is defined \[\vec{a}\cdot\vec{b} = a_1b_1 + a_2b_2 + a_3b_3\]

Dot Product Properties

Let $\vec{a}, \vec{b}, \vec{c} \in V_3$ and $c \in \mathbb{R}$. Then

  1. $\vec{a} \cdot \vec{a} = |\vec{a}|^2$
    Think Equivalently $|\vec{a}| = \sqrt{\vec{a}\cdot\vec{a}}$.
  2. $\vec{a} \cdot \vec{b} = \vec{b} \cdot \vec{a}$
  3. $\vec{a} \cdot \left(\vec{b} + \vec{c}\right) = \vec{a}\cdot \vec{b} + \vec{a} \cdot \vec{c}$
  4. $\left(c\vec{a}\right) \cdot \vec{b} = c\left(\vec{a}\cdot \vec{b}\right) = \vec{a} \cdot \left(c\vec{b}\right)$
  5. $\vec{0} \cdot \vec{a} = 0$
  6. If $\vec{a} \cdot \vec{a} = 0$, then $\vec{a} = \vec{0}$.
Theorem (Geometric Meaning of the Dot Product)

If $\theta$ is the angle between $\vec{a}$ and $\vec{b}$, then \[\vec{a} \cdot \vec{b} = |\vec{a}||\vec{b}|\cos\theta\]

Key Idea $\vec{a}\cdot\vec{b}$ is the Pythagorean defect: how far off $\vec{a}$ and $\vec{b}$ are from forming a right angle.

Corollary (Angle Between Two Vectors)

If $\vec{a}, \vec{b} \neq \vec{0}$, then the angle $\theta$ between $\vec{a}$ and $\vec{b}$ satisfies \[\cos\theta = \dfrac{\vec{a}\cdot\vec{b}}{|\vec{a}||\vec{b}|}\]

orthogonal

Two vectors are orthogonal (perpendicular) precisely when the angle between them is $\theta = 90^\circ$.

Fact $\vec{a}$ and $\vec{b}$ are orthogonal if and only if $\vec{a}\cdot\vec{b} = 0$.

Orientation from the Dot Product

The angle $\theta$, and in turn the dot product, tells us how two nonzero vectors are oriented:

Vectors are parallel when $\theta = 0^\circ$ or $180^\circ$, or equivalently when $\vec{b} = c\vec{a}$ for some scalar $c$.

Key Idea (Projections)

$\vec{a}\cdot\vec{b}$ really measures "how much" $\vec{b}$ is pointing in $\vec{a}$'s direction, relative to $|\vec{a}|$.

When $|\vec{a}| = 1$, $\vec{a}\cdot\vec{b}$ answers the question "How much of $\vec{b}$ points along $\vec{a}$, measured in $\vec{a}$-lengths?"

In general, $\vec{a}$ is not a unit vector, but \[\vec{a}\cdot\vec{b} = |\vec{a}||\vec{b}|\cos\theta \qquad \text{implies} \qquad |\vec{b}|\cos\theta = \dfrac{\vec{a}\cdot\vec{b}}{|\vec{a}|} = \dfrac{\vec{a}}{|\vec{a}|}\cdot \vec{b}\] which is exactly the dot product of $\vec{b}$ with the unit vector in the direction of $\vec{a}$.

scalar projection, vector projection

The scalar projection of $\vec{b}$ onto $\vec{a}$ (also called the component of $\vec{b}$ along $\vec{a}$) is the signed length of the shadow of $\vec{b}$ in the direction of $\vec{a}$: \[\text{comp}_{\vec{a}}\vec{b} = \dfrac{\vec{a}\cdot\vec{b}}{|\vec{a}|}\]

The vector projection of $\vec{b}$ onto $\vec{a}$ is that shadow as a vector (scalar projection times the unit vector in the direction of $\vec{a}$): \[\text{proj}_{\vec{a}}\vec{b} = \left(\dfrac{\vec{a}\cdot\vec{b}}{|\vec{a}|}\right)\dfrac{\vec{a}}{|\vec{a}|} = \left(\dfrac{\vec{a}\cdot\vec{b}}{|\vec{a}|^2}\right)\vec{a}\]

Thales's Theorem

If $A, B, C$ are distinct points on circle $O$ where $\overline{AB}$ is a diameter, then $\angle ACB$ is a right angle.

Alternate Equation of a Circle

If $A(x_1, y_1)$ and $B(x_2, y_2)$ are the endpoints of a diameter, then the circle is the set of points $C(x, y)$ with $\ray{CA}\cdot\ray{CB} = 0$, giving \[(x - x_1)(x - x_2) + (y - y_1)(y - y_2) = 0\]

12.4: The Cross Product


determinant of order 2

A determinant of order 2 is defined by \[\begin{vmatrix} a & b \\ c & d\end{vmatrix} = ad - bc\]

Determinants and Signed Area

Insert the coordinates of $\vec{a}$ and $\vec{b}$ into the determinant column-wise, $\vec{a}$ first. The result is the signed area of the parallelogram determined by $\vec{a}$ and $\vec{b}$.

The sign comes from the right hand rule, with the left column vector rotated onto the right column vector:

Swapping the order of the columns (rotating $\vec{b}$ onto $\vec{a}$ instead) flips the sign.

cross product

Let $\vec{a} = \vc{a_1, a_2, a_3}$ and $\vec{b} = \vc{b_1, b_2, b_3}$. The cross product of $\vec{a}$ and $\vec{b}$ is the vector \[\vec{a}\times\vec{b} = \vc{a_2b_3 - a_3b_2,\ a_3b_1 - a_1b_3,\ a_1b_2 - a_2b_1}\]

determinant of order 3

A determinant of order 3 is defined by expansion along the first row: \[\begin{vmatrix} a_1 & a_2 & a_3 \\ b_1 & b_2 & b_3 \\ c_1 & c_2 & c_3\end{vmatrix} = a_1\begin{vmatrix} b_2 & b_3 \\ c_2 & c_3\end{vmatrix} - a_2\begin{vmatrix} b_1 & b_3 \\ c_1 & c_3\end{vmatrix} + a_3\begin{vmatrix} b_1 & b_2 \\ c_1 & c_2\end{vmatrix}\]

Note the alternating signs $+, -, +$.
cross product (determinant form)

Let $\vec{a} = \vc{a_1, a_2, a_3}$ and $\vec{b} = \vc{b_1, b_2, b_3}$. The cross product $\vec{a}\times\vec{b}$ is \[\vec{a}\times\vec{b} = \begin{vmatrix} \iv & \jv & \kv \\ a_1 & a_2 & a_3 \\ b_1 & b_2 & b_3\end{vmatrix} = \begin{vmatrix} a_2 & a_3 \\ b_2 & b_3\end{vmatrix}\iv - \begin{vmatrix} a_1 & a_3 \\ b_1 & b_3\end{vmatrix}\jv + \begin{vmatrix} a_1 & a_2 \\ b_1 & b_2\end{vmatrix}\kv\]

Theorem (Direction of the Cross Product)

The vector $\vec{a}\times\vec{b}$ is orthogonal to both $\vec{a}$ and $\vec{b}$: \[(\vec{a}\times\vec{b})\cdot\vec{a} = 0 \qquad \text{and} \qquad (\vec{a}\times\vec{b})\cdot\vec{b} = 0\]

Among the two directions orthogonal to both, the direction of $\vec{a}\times\vec{b}$ is given by the right hand rule.

Careful Always curl your fingers from the vector left of $\times$ towards the vector on the right.

normal vector to a plane

A vector $\vec{a}$ that is orthogonal to every vector in the plane.

Theorem (Length of the Cross Product)

If $\theta$ is the angle between $\vec{a}$ and $\vec{b}$ with $\theta \in [0, \pi]$, then \[|\vec{a}\times\vec{b}| = |\vec{a}||\vec{b}|\sin\theta\]

Cross Product as Area

The length of the cross product $\vec{a}\times\vec{b}$ is equal to the area of the parallelogram determined by $\vec{a}$ and $\vec{b}$.

Components are Shadow Areas

Let $\vec{a}, \vec{b} \in V_3$ be nonzero. Then \[\vec{a}\times\vec{b} = \vc{A_{yz},\ A_{zx},\ A_{xy}}\] where $A_{yz}$ is the signed area of the parallelogram determined by $\vec{a}, \vec{b}$ after projecting onto the $yz$-plane, and likewise for $A_{zx}$ and $A_{xy}$.

Signed Shadow Areas

Given $\vec{a}\times\vec{b}$, after you apply the right hand rule, look down the positive axis normal to that plane (toward the origin).

Projecting a surface onto a coordinate plane: set the coordinate along the plane's normal to 0.

Cross Product Properties

Let $\vec{a}, \vec{b}, \vec{c} \in V_3$ and $c \in \mathbb{R}$. Then

  1. $\vec{a}\times\vec{b} = -\left(\vec{b}\times\vec{a}\right)$
    Think The cross product is anticommutative: swapping the order reverses the direction.
  2. $(c\vec{a})\times\vec{b} = c\left(\vec{a}\times\vec{b}\right) = \vec{a}\times(c\vec{b})$
  3. $\vec{a}\times(\vec{b} + \vec{c}) = \vec{a}\times\vec{b} + \vec{a}\times\vec{c}$
  4. $(\vec{a} + \vec{b})\times\vec{c} = \vec{a}\times\vec{c} + \vec{b}\times\vec{c}$
  5. $\vec{a}\cdot(\vec{b}\times\vec{c}) = (\vec{a}\times\vec{b})\cdot\vec{c}$
  6. $\vec{a}\times(\vec{b}\times\vec{c}) = (\vec{a}\cdot\vec{c})\vec{b} - (\vec{a}\cdot\vec{b})\vec{c}$

In particular, $\vec{a}\times\vec{a} = \vec{0}$ for every $\vec{a} \in V_3$.

scalar triple product

The product $\vec{a}\cdot(\vec{b}\times\vec{c})$ is called the scalar triple product.\[\vec{a}\cdot(\vec{b}\times\vec{c}) = \begin{vmatrix} a_1 & a_2 & a_3 \\ b_1 & b_2 & b_3 \\ c_1 & c_2 & c_3\end{vmatrix}\]

Volume of a Parallelepiped

The volume of the parallelepiped determined by the vectors $\vec{a}, \vec{b}$ and $\vec{c}$ is the absolute value of their scalar triple product: \[V = \left|\vec{a}\cdot(\vec{b}\times\vec{c})\right|\]

In particular, $\vec{a}, \vec{b}, \vec{c}$ lie in the same plane (are coplanar) if and only if $\vec{a}\cdot(\vec{b}\times\vec{c}) = 0$.

12.5: Equations of Lines and Planes


What Determines a Line

A line $L$ in $\mathbb{R}^3$ is completely determined if we know two things: a point on the line and a direction vector for $L$, which is a vector $\vec{v}$ parallel to the line.

vector equation of a line

The vector equation of a line through a point $P_0(x_0, y_0, z_0)$ with position vector $\vec{r}_0$ and parallel to the vector $\vec{v}$ is \[\vec{r} = \vec{r}_0 + t\vec{v}, \qquad t \in \mathbb{R}\]

Letting $\vec{v} = \vc{a, b, c}$, $\vec{r} = \vc{x, y, z}$ and $\vec{r}_0 = \vc{x_0, y_0, z_0}$, this becomes \[\vc{x, y, z} = \vc{x_0 + ta,\ y_0 + tb,\ z_0 + tc}\]

parametric equations of a line

Parametric equations for a line through the point $(x_0, y_0, z_0)$ and parallel to the vector $\vec{v} = \vc{a, b, c}$ are \[x = x_0 + at, \qquad y = y_0 + bt, \qquad z = z_0 + ct\]

linear interpolation

The line segment from $\vec{r}_0$ to $\vec{r}_1$ is given by the vector equation \[\vec{r}(t) = (1 - t)\vec{r}_0 + t\vec{r}_1, \qquad 0 \leq t \leq 1\]

What Determines a Plane

A plane in $\mathbb{R}^3$ is completely determined if we know two things:

  1. A point on the plane, and
  2. a normal vector to the plane.
vector equation of a plane

The vector equation of a plane through a point $P_0(x_0, y_0, z_0)$ with position vector $\vec{r}_0$, normal vector $\vec{n}$, and arbitrary point $P(x, y, z)$ with position vector $\vec{r}$ is \[\vec{n}\cdot\left(\vec{r} - \vec{r}_0\right) = 0\] $\vec{r} - \vec{r}_0$ sweeps out every point in the plane.

scalar equation of a plane

A scalar equation of the plane through the point $P_0(x_0, y_0, z_0)$ with normal vector $\vec{n} = \vc{a, b, c}$ is \[a(x - x_0) + b(y - y_0) + c(z - z_0) = 0\]

Chapter 13: Vector Functions


13.0: Preliminaries


Main Idea Behind Parametrics

Think of parameter $t$ as time, and $(x(t), y(t))$ as the location of a moving point. This allows us to trace curves which do not pass the vertical line test.

Vector $\vc{x(t), y(t)}$ is a position vector with tip tracing out the curve.

conic section

A conic section is an intersection of a double cone and a plane in $\mathbb{R}^3$.

Conic Parametrizations
Conic Rectangular Equation Parametric Equations
Circle \( (x-h)^2 + (y-k)^2 = r^2 \) \( \begin{aligned} x &= h + r\cos t \\ y &= k + r\sin t \end{aligned} \) \( t \in [0, 2\pi) \)
Ellipse \( \dfrac{(x-h)^2}{a^2} + \dfrac{(y-k)^2}{b^2} = 1 \) \( \begin{aligned} x &= h + a\cos t \\ y &= k + b\sin t \end{aligned} \) \( t \in [0, 2\pi) \)
Hyperbola \( \dfrac{(x-h)^2}{a^2} - \dfrac{(y-k)^2}{b^2} = 1 \) \( \begin{aligned} x &= h + a\sec t \\ y &= k + b\tan t \end{aligned} \) \( t \in \left(-\tfrac{\pi}{2}, \tfrac{\pi}{2}\right) \cup \left(\tfrac{\pi}{2}, \tfrac{3\pi}{2}\right) \)
Three Ways to Parametrize a Curve from Its Rectangular Equation
  1. Look for the form \(Ax^2 + Cy^2 + Dx + Ey + F = 0\). This is a conic section. Complete the square to reach standard form, then use above table.
  2. Isolate one variable and set the other equal to $t$. Then $t$ ranges over the domain of the resulting expression, usually $\mathbb{R}$.
    • If isolating produces a $\pm$, you will need two parametrics. Try to avoid, unless you are in case 3.
  3. If the curve is a closed loop, try periodic motion: \(x = a\cos t,\ y = b\sin t,\ t\in[0,2\pi)\).

13.1: Vector Functions and Space Curves


vector-valued function, space curve

A vector-valued function is a function $\vec{r} : \mathbb{R} \to \mathbb{R}^3$. It eats real numbers and spits out vectors: \[\vec{r}(t) = \vc{x(t), y(t), z(t)} = x(t)\iv + y(t)\jv + z(t)\kv\]

The component functions $x(t), y(t), z(t)$ are parametrics in disguise. The space curve traced by $\vec{r}$ is the path swept out by the tip of the position vector $\vec{r}(t)$.

Think Input a time $t$, output a position.

Domain of a Vector Function

The domain of $\vec{r}(t)$ is the set of all $t$ you can plug in and get a vector out. That is, it is the intersection of the domains of the component functions.

Curves of Intersection

To parametrize the curve where two surfaces meet:

  1. Substitute one equation into the other to eliminate a variable. This leaves a curve in the two remaining variables.
  2. Parametrize that curve using the three techniques from 13.0.
  3. Recover the eliminated variable using the equation you substituted with.
limit of a vector function

If $\vec{r}(t) = \vc{f(t), g(t), h(t)}$, then \[\lim_{t\to a}\vec{r}(t) = \vc{\lim_{t\to a} f(t),\ \lim_{t\to a} g(t),\ \lim_{t\to a} h(t)}\] provided the limits of the component functions exist.

13.2 + 13.4: Derivatives and Integrals of Vector Functions


derivative, tangent vector, tangent line

Let $C$ be the curve traced by $\vec{r}(t)$. The derivative $\vec{r}\,'(t)$ is defined \[\vec{r}\,'(t) = \dfrac{d\vec{r}}{dt} = \lim_{h\to 0}\dfrac{\vec{r}(t + h) - \vec{r}(t)}{h}\] if this limit exists. $\vec{r}\,'(t)$ is called the tangent vector to $C$.

The tangent line to $C$ at $\vec{r}(t_0)$ is the line parallel to $\vec{r}\,'(t_0)$ at the point of tangency.

Think If $\vec{r}(t)$ is the track of a rollercoaster and you are sitting at the tip of $\vec{r}(t)$, then the direction of $\vec{r}\,'(t)$ is your line of sight.

Theorem (Differentiate Componentwise)

If $\vec{r}(t) = \vc{f(t), g(t), h(t)} = f(t)\iv + g(t)\jv + h(t)\kv$ where $f, g$ and $h$ are differentiable functions, then \[\vec{r}\,'(t) = \vc{f'(t), g'(t), h'(t)} = f'(t)\iv + g'(t)\jv + h'(t)\kv\]

unit tangent vector

A unit vector that has the same direction as $\vec{r}\,'(t)$ is \[\vec{T}(t) = \dfrac{\vec{r}\,'(t)}{|\vec{r}\,'(t)|}\]

velocity vector, speed, acceleration

If $\vec{r}(t)$ describes the position vector of an object, then \[\vec{v}(t) = \vec{r}\,'(t)\] describes the rate of change of position of the object with respect to time.

The speed of the object is the magnitude $|\vec{v}(t)| = |\vec{r}\,'(t)|$. Speed is a scalar function; velocity is a vector function.

The acceleration of the object is \[\vec{a}(t) = \vec{v}\,'(t) = \vec{r}\,''(t)\]

What $\vec{v}(t)$ Tells Us About $\vec{r}(t)$
  1. $\vec{v}(t) = \vec{r}\,'(t) = \vc{x'(t), y'(t)}$. Each component describes how fast that coordinate is changing.
  2. $\vec{v}(t)$ records how the tip of $\vec{r}(t)$ is changing.
    • Direction of $\vec{v}(t)$: which way the tip of $\vec{r}(t)$ is being dragged next.
    • Magnitude $|\vec{v}(t)|$: how fast or slow the tip of $\vec{r}(t)$ is changing.
  3. $\vec{v}(t)$ is always tangent to the curve.
What $\vec{a}(t)$ Tells Us About $\vec{v}(t)$

$\vec{a}(t)$ records how the tip of $\vec{v}(t)$ is changing: its direction says which way the tip of $\vec{v}(t)$ is being dragged next, and its magnitude says how fast the tip of $\vec{v}(t)$ is changing.

Acceleration changes velocity in two different ways:

Theorem (Differentiation Rules)

Suppose $\vec{u}$ and $\vec{v}$ are differentiable vector functions, $c \in \mathbb{R}$ and $f$ is a real-valued function.

  1. $\dfrac{d}{dt}\left[f(t)\vec{u}(t)\right] = f'(t)\vec{u}(t) + f(t)\vec{u}\,'(t)$
  2. $\dfrac{d}{dt}\left[\vec{u}(t)\cdot\vec{v}(t)\right] = \vec{u}\,'(t)\cdot\vec{v}(t) + \vec{u}(t)\cdot\vec{v}\,'(t)$
  3. $\dfrac{d}{dt}\left[\vec{u}(t)\times\vec{v}(t)\right] = \vec{u}\,'(t)\times\vec{v}(t) + \vec{u}(t)\times\vec{v}\,'(t)$
    Careful The cross product is anticommutative, so you must preserve the order of the factors.
definite integral of a vector valued function

Let $\vec{r}(t) = \vc{x(t), y(t), z(t)}$ be a continuous vector function. Then \[\int_a^b \vec{r}(t)\,dt = \vc{\int_a^b x(t)\,dt,\ \int_a^b y(t)\,dt,\ \int_a^b z(t)\,dt}\]

The indefinite integral is \[\int \vec{r}(t)\,dt = \vc{\int x(t)\,dt,\ \int y(t)\,dt,\ \int z(t)\,dt} + \vec{c}\] where $\vec{c} = \vc{c_1, c_2, c_3}$ is a constant vector.

Think Just like differentiation, integrate each component separately.

13.3: Arc Length and Curvature


arc length

If a curve $C$ has vector equation $\vec{r}(t) = \vc{x(t), y(t), z(t)}$ where $a \leq t \leq b$ and the curve is traversed exactly once as $t$ increases from $a$ to $b$, then the arc length of $C$ is \[L = \int_a^b \sqrt{\left[x'(t)\right]^2 + \left[y'(t)\right]^2 + \left[z'(t)\right]^2}\,dt = \int_a^b \sqrt{\left(\dfrac{dx}{dt}\right)^2 + \left(\dfrac{dy}{dt}\right)^2 + \left(\dfrac{dz}{dt}\right)^2}\,dt\]

Since $\vec{r}\,'(t) = \vc{x'(t), y'(t), z'(t)}$, we can simply write \[L = \int_a^b \left|\vec{r}\,'(t)\right|\,dt\]

Why Arc Length Uses the Tangent Vector

In the staircase paradox, a staircase approximation to the diagonal of the unit square has length 2 at every stage, yet the diagonal has length $\sqrt{2}$.

The issue is that tangency to the curve is not preserved: the staircase's corners are not on the line you are trying to estimate. In a proper arc length calculation, all estimating points are on the curve, so tangency is preserved under the limit.

arc length function

Suppose the curve $C$ is traversed exactly once by $\vec{r}(t) = \vc{x(t), y(t), z(t)}$ where $t \in [a,b]$ as $t$ increases from $a$ to $b$. The arc length function is \[s(t) = \int_a^t \left|\vec{r}\,'(u)\right|\,du\]

By the Fundamental Theorem of Calculus, \[\dfrac{ds}{dt} = \left|\vec{r}\,'(t)\right|\] which says "the rate of change of arc length with respect to $t$ is exactly the speed of $\vec{r}(t)$."