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Applications of Vector Algebra - Study Notes

Applications of Vector Algebra — Study Notes

This chapter pushes the dot and cross products one step further: it combines three vectors at a time, then uses those combinations to describe lines and planes in three‑dimensional space. The notes below summarise every idea you need for the book‑back exercise.

1. Scalar Triple Product (the box product)

For vectors \(\vec{a},\vec{b},\vec{c}\), the scalar \((\vec{a}\times\vec{b})\cdot\vec{c}\) is called the scalar triple product and is written \([\vec{a},\vec{b},\vec{c}]\). In components it is a determinant:

\[[\vec{a},\vec{b},\vec{c}]=\begin{vmatrix}a_{1}&a_{2}&a_{3}\\b_{1}&b_{2}&b_{3}\\c_{1}&c_{2}&c_{3}\end{vmatrix}.\]

2. Vector Triple Product

The product \(\vec{a}\times(\vec{b}\times\vec{c})\) is a vector, expanded by the BAC–CAB rule:

\[\vec{a}\times(\vec{b}\times\vec{c})=(\vec{a}\cdot\vec{c})\,\vec{b}-(\vec{a}\cdot\vec{b})\,\vec{c}.\]

The result always lies in the plane of the two bracketed vectors \(\vec{b}\) and \(\vec{c}\). The operation is not associative: in general \(\vec{a}\times(\vec{b}\times\vec{c})\neq(\vec{a}\times\vec{b})\times\vec{c}\). A handy mirror form is \((\vec{a}\times\vec{b})\times\vec{c}=(\vec{a}\cdot\vec{c})\,\vec{b}-(\vec{b}\cdot\vec{c})\,\vec{a}\).

3. Jacobi’s and Lagrange’s Identities

4. Equations of a Straight Line

A line is fixed either by a point and a direction, or by two points.

5. Relations Between Two Lines

6. Equations of a Plane

7. Angles, Containment and Intersections

8. Distances and Images

9. Common Exam Traps

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