AOS5 Topic 4: Cross Product
Vector Product
Geometric Definition of the Vector Product
Definition of the vector product: The vector product of \( \mathbf{a} \) and \( \mathbf{b} \) is denoted by \( \mathbf{a} \times \mathbf{b} \).
The magnitude of \( \mathbf{a} \times \mathbf{b} \) is equal to \( |\mathbf{a}| |\mathbf{b}| \sin \theta \), where \( \theta \) is the angle between \( \mathbf{a} \) and \( \mathbf{b} \).
The direction of \( \mathbf{a} \times \mathbf{b} \) is perpendicular to the plane containing \( \mathbf{a} \) and \( \mathbf{b} \), in the sense of the right-hand rule.
Note: The vector product is often called the cross product.
Watch the video below to understand the notes about the cross product more deeply.
Created with GeoGebra®, by Dave Nero, Link
The Magnitude of \( \mathbf{a} \times \mathbf{b} \)
By definition, we have \( |\mathbf{a} \times \mathbf{b}| = |\mathbf{a}| |\mathbf{b}| \sin \theta \) where \( \theta \) is the angle between \( \mathbf{a} \) and \( \mathbf{b} \).
The direction of \( \mathbf{a} \times \mathbf{b} \) using the right-hand rule:
- Point your index finger along the vector \( \mathbf{a} \).
- Point your middle finger along the vector \( \mathbf{b} \).
- Keep your thumb at right angles to both \( \mathbf{a} \) and \( \mathbf{b} \). The direction of your thumb gives the direction of the vector \( \mathbf{a} \times \mathbf{b} \).
Calculating Cross Product
Created with GeoGebra®, by Lenore Horner, Link
The direction of \( \mathbf{a} \times \mathbf{b} \) using the right-hand rule
To find the direction of the vector \( \mathbf{a} \times \mathbf{b} \) using your right hand:
- Point your index finger along the vector \( \mathbf{a} \).
- Point your middle finger along the vector \( \mathbf{b} \).
- Keep your thumb at right angles to both \( \mathbf{a} \) and \( \mathbf{b} \), as in the picture. The direction of your thumb gives the direction of the vector \( \mathbf{a} \times \mathbf{b} \).
The following two diagrams show \( \mathbf{a} \times \mathbf{b} \) and \( \mathbf{b} \times \mathbf{a} \).
The vector \( \mathbf{b} \times \mathbf{a} \) has the same magnitude as \( \mathbf{a} \times \mathbf{b} \), but the opposite direction. We can see that:
\( \mathbf{b} \times \mathbf{a} = -(\mathbf{a} \times \mathbf{b}) \)
Thus, the vector product is not commutative.
Note: The vector product is also not associative. In general, we have \( (\mathbf{a} \times \mathbf{b}) \times \mathbf{c} \neq \mathbf{a} \times (\mathbf{b} \times \mathbf{c}) \).
Vector Product of Parallel Vectors
If \( \mathbf{a} \) and \( \mathbf{b} \) are parallel vectors, then \( \mathbf{a} \times \mathbf{b} = 0 \), since \( |\mathbf{a} \times \mathbf{b}| = |\mathbf{a}| |\mathbf{b}| \sin 0^\circ = 0 \).
Conversely, if \( \mathbf{a} \) and \( \mathbf{b} \) are non-zero vectors such that \( \mathbf{a} \times \mathbf{b} = 0 \), then \( \mathbf{a} \) and \( \mathbf{b} \) are parallel.
Vector Product of Perpendicular Vectors
If \( \mathbf{a} \) and \( \mathbf{b} \) are perpendicular vectors, then
\[ |\mathbf{a} \times \mathbf{b}| = |\mathbf{a}| |\mathbf{b}| \sin 90^\circ = |\mathbf{a}| |\mathbf{b}| \]
The three vectors \( \mathbf{a} \), \( \mathbf{b} \), and \( \mathbf{a} \times \mathbf{b} \) form a right-handed system of mutually perpendicular vectors,as shown in the diagram.
Vector Product in Component Form
Using the previous observations about the vector product of parallel and perpendicular vectors:
\[ \mathbf{i} \times \mathbf{i} = \mathbf{j} \times \mathbf{j} = \mathbf{k} \times \mathbf{k} = 0 \]
\[ \mathbf{i} \times \mathbf{j} = \mathbf{k}, \quad \mathbf{j} \times \mathbf{k} = \mathbf{i}, \quad \mathbf{k} \times \mathbf{i} = \mathbf{j} \]
\[ \mathbf{j} \times \mathbf{i} = -\mathbf{k}, \quad \mathbf{k} \times \mathbf{j} = -\mathbf{i}, \quad \mathbf{i} \times \mathbf{k} = -\mathbf{j} \]
The diagram on the right may help you to follow the pattern among these vector products.
The vector product distributes over addition. That is:
\[ \mathbf{a} \times (\mathbf{b} + \mathbf{c}) = \mathbf{a} \times \mathbf{b} + \mathbf{a} \times \mathbf{c} \]
These facts can be used to establish the following result.
If \( \mathbf{a} = a_1 \mathbf{i} + a_2 \mathbf{j} + a_3 \mathbf{k} \) and \( \mathbf{b} = b_1 \mathbf{i} + b_2 \mathbf{j} + b_3 \mathbf{k} \), then
\[ \mathbf{a} \times \mathbf{b} = (a_2 b_3 - a_3 b_2) \mathbf{i} - (a_1 b_3 - a_3 b_1) \mathbf{j} + (a_1 b_2 - a_2 b_1) \mathbf{k} \]
Example 1
\( \begin{vmatrix}
\mathbf{i} & \mathbf{j} & \mathbf{k} \\
3 & 3 & 8 \\
1 & -3 & 2
\end{vmatrix} \)
\(= \mathbf{i} \begin{vmatrix} 3 & 8 \\ -3 & 2 \end{vmatrix} - \mathbf{j} \begin{vmatrix} 3 & 8 \\ 1 & 2 \end{vmatrix} + \mathbf{k} \begin{vmatrix} 3 & 3 \\ 1 & -3 \end{vmatrix} \)
\(= \mathbf{i} \left(3 \times 2 - 8 \times (-3)\right) - \mathbf{j} \left(3 \times 2 - 8 \times 1\right) + \mathbf{k} \left(3 \times (-3) - 3 \times 1\right) \)
\(= 30\mathbf{i} + 2\mathbf{j} - 12\mathbf{k} \)
Example 2
Example 3
Example 4
Example 5
- Calculate the vector product \( \mathbf{c} = \mathbf{a} \times \mathbf{b} \).
- Normalize \( \mathbf{c} \) by dividing it by its magnitude.
- Scale \( \mathbf{c} \) to have a magnitude of 5.
Example 6
Example 7
\[ \overrightarrow{OA} = \langle 0 - 0, 1 - 0, 3 - 0 \rangle = \langle 0, 1, 3 \rangle \] \[ \overrightarrow{OB} = \langle 0 - 0, 2 - 0, 5 - 0 \rangle = \langle 0, 2, 5 \rangle \]
\[ \overrightarrow{OA} \times \overrightarrow{OB} = -\mathbf{i} \]