Vectors

Vectors#


Table of Contents#


\(p = (2, 3)\) is a point but \(\mathbf{p} = \begin{bmatrix}2\\3\\\end{bmatrix}\) (a \(2 \times 1\) matrix) is a vector in \(\mathbb{R}^2\) (two-dimensional space)

\(p = (3, 7, 5)\) is a point but \(\mathbf{p} = \begin{bmatrix}3\\7\\5\\\end{bmatrix}\) (a \(3 \times 1\) matrix) is a vector in \(\mathbb{R}^3\) (three dimensional space)

[ Definition ] Vector Equality

Two vectors are equal iff their corresponding entries are equal.

\(\begin{bmatrix}2\\3\\\end{bmatrix} \ne \begin{bmatrix}3\\2\\\end{bmatrix}\)

[ Definition ] Vector Addition

\(\begin{bmatrix}v_1\\v_2\\\end{bmatrix} + \begin{bmatrix}w_1\\w_2\\\end{bmatrix} = \begin{bmatrix}v_1+w_1\\v_2+w_2\\\end{bmatrix}\)

Geometrically: parallelogram rule

\( \begin{bmatrix}a\\b\\c\\\end{bmatrix} + \begin{bmatrix}\alpha\\\beta\\\gamma\\\end{bmatrix} = \begin{bmatrix}a + \alpha\\b + \beta\\c + \gamma\\\end{bmatrix} \)

[ Definition ] Multiplication of a scalar with a vector

\(r\begin{bmatrix}v_1\\v_2\\\end{bmatrix} = \begin{bmatrix}rv_1\\rv_2\\\end{bmatrix}\)

\(r\begin{bmatrix}a\\b\\c\\\end{bmatrix} = \begin{bmatrix}ra\\rb\\rc\\\end{bmatrix}\)

EXAMPLE

Let \(\mathbf{u} = \begin{bmatrix}0\\1\\\end{bmatrix}, \mathbf{v} = \begin{bmatrix}3\\2\\\end{bmatrix}, \mathbf{w} = \begin{bmatrix*}[r]2\\-1\\\end{bmatrix*}\). Then the following is true.

\(5\mathbf{u} = 5\begin{bmatrix}0\\1\\\end{bmatrix} = \begin{bmatrix}0\\5\\\end{bmatrix}\)

\(2\mathbf{v} = 2\begin{bmatrix}3\\2\\\end{bmatrix} = \begin{bmatrix}6\\4\\\end{bmatrix}\)

\(-3\mathbf{w} = -3\begin{bmatrix*}[r]2\\-1\\\end{bmatrix*} = \begin{bmatrix*}[r]-6\\3\\\end{bmatrix*}\)

\( 5\mathbf{u} + 2\mathbf{v} - 3\mathbf{w} = \begin{bmatrix}0\\5\\\end{bmatrix} + \begin{bmatrix}6\\4\\\end{bmatrix} + \begin{bmatrix*}[r]-6\\3\\\end{bmatrix*} = \begin{bmatrix*}[r] 0 & + & 6 & + & (-6) \\ 5 & + & 4 & + & 3 \\ \end {bmatrix*} = \begin{bmatrix*}[r] 0 \\ 12 \\ \end {bmatrix*} \)

Zero Vector

The following vector is called the zero vector.

\(\mathbf{0} = \begin{bmatrix}0\\0\\\vdots\\0\\\end{bmatrix}\)

It is the only vector of length \(0\). It is unique among vectors in the fact that it does not specify a particular direction (i.e., it does not specify a particular family of parallel lines since it is contained in every line).

Properties of Vectors

Let \(\mathbf{u, v, w}\) be vectors and let \(s, t\) be scalars.

Additive Associativity

\(\mathbf{(u + v) + w = u + (v + w)}\)

Additive Commutativity

\(\mathbf{v + w = w + v}\)

Additive Identity Element

\(\mathbf{0 + v = v}\)

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\((-1)\mathbf{v + v = 0}\)

Scalar-Multiplicative Associativity

\(s(t\mathbf{v}) = (st)\mathbf{v}\)

Scalar-Multiplivative Identity Element

\(1\mathbf{v = v}\)

\(s(\mathbf{v + w}) = s\mathbf{v} + s\mathbf{w}\)

\((s + t)\mathbf{v} = s\mathbf{v} + t\mathbf{v}\)