handouts/Advanced/Linear Maps/parts/1 spaces.tex

\section{Spaces}

\definition{Vector Spaces}
A \textit{space} over a field $\mathbb{F}$ consists of the following elements:
\begin{itemize}[itemsep = 2mm]
	\item A set $V$, the elements of which are called \textit{vectors}
	\item An operation called \textit{vector addition}, denoted $+$ \\
		Vector addition operates on two elements of $V$. \\

	\item An operation called \textit{scalar multiplication}, denoted $\times$ \\
		Scalar multiplication multiplies an element of $V$ by an element of $\mathbb{F}$. \\
		Any element of $\mathbb{F}$ is called a \textit{scalar}.
\end{itemize}

\vspace{2mm}

\textbf{Note:}
The same symbols are used for additions and multiplications in both $\mathbb{F}$ and $V$. \\
\textit{These are different operations}, so be aware of the context of each $+$ and $\times$.

\vspace{5mm}

Vector addition and multiplication must have the following properties. \\
In both tables, $x, y, z \in V$ and $a, b\in \mathbb{F}$.

\vspace{2mm}

% [t] and \vspace{0pt} ensure alignment at top
\begin{minipage}[t]{0.48\textwidth}\vspace{0pt}
	\begin{center}
	\begin{tabular}{l | r@{=}l }
		\hline
		\multicolumn{3}{|c|}{Properties of vector addition} \\
		\hline
		Closure			& \multicolumn{2}{c}{$x+y \in V$} \\
		Associativity	& $(x+y)+z~$&$~x+y+z$	\\
		Commutativity	& $x+y~$&$~y+x$ 		\\
		Distributivity	& $x(y+z)~$&$~xy + xz$	\\
		Identity		& $x+0~$&$~x$			\\
		Inverse			& $x + (-x)~$&$~0$
	\end{tabular}
	\end{center}
\end{minipage}%
\hfill%
\begin{minipage}[t]{0.48\textwidth}\vspace{0pt}
	\begin{center}
	\begin{tabular}{l | r@{=}l }
		\hline
		\multicolumn{3}{|c|}{Properties of vector multiplication} \\
		\hline
		Closure			& \multicolumn{2}{c}{$ax \in V$} \\
		Distributivity	& $a(x+y)~$&$~ax+ay$	\\
						& $(a+b)x~$&$~ax+bx$	\\
		Compatibility$^*$	& $(ab)x~$&$~a(bx)$		\\
		Identity		& $a+0~$&$~a$
	\end{tabular}
\end{center}
\end{minipage}

\vspace{2mm}

$^*$ Remember that $a, b \in \mathbb{F}$ and $x \in V$. Thus, $(ab)$ is scalar multiplication and $(bx)$ is vector multiplication. \\
Compatibility is \textit{not} associativity, it is \say{compatibility of vector and scalar multiplication.}

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\pagebreak

\definition{}
There is a good chance you are familiar with basic vector arithmetic. \\
Here's a quick review:
\begin{itemize}
	\item Scalar multiplication is done elementwise: $3 \times [a, b, c] = [3a, 3b, 3c]$.
	\item Vector addition is similar: $[a, b, c] + [1, 2, 3] = [a+1,~b+2,~c+3]$.
	\item Vector addition is not valid for vectors of different sizes.
\end{itemize}


\definition{}
We usually use the \textit{dot product} as our vector product. It is defined as follows. \\
Given two vectors $a, b \in \mathbb{R}^n$, the dot product $a \cdot b$ is $\sum_1^n a_ib_i$.

\vspace{2mm}

In other words, if $a = [1, 2, 3]$ and $b = [4, 5, 6]$,
$$
	a \cdot b = (1 \times 4) + (2 \times 5) + (3 \times 6) = 32
$$
As you may expect, the dot product $ab$ is valid iff $a$ and $b$ are the same size.



\problem{}
Show that the dot product satisfies the properties of a vector product listed above. \\
Conclude that $\mathbb{R}^n$ is a vector space over $\mathbb{R}$.

\vfill
\pagebreak