+On modern computer architectures, there are two basic number formats supported:
+fixed-width integers and \emph{floating-point} numbers. Typically, computers
+natively support integers of up to 64 bits, capable of representing all integers
+between $0$ and $2^{64} - 1$\footnote{Most machines also support \emph{signed} integers,
+which have the same cardinality as their \emph{unsigned} counterparts, but which
+represent integers between $-(2^{63})$ and $2^{63} - 1$}.
+
+By introducing a fractional component (analogous to a decimal point), we can convert
+integers to \emph{fixed-point} numbers, which have a more limited range, but a fixed, greater
+precision. For example, a number in 4.4 fixed-point format would have four bits representing the integer
+component, and four bits representing the fractional component:
+\begin{equation}
+ \underbrace{0101}_\text{integer component}.\underbrace{1100}_\text{fractional component} = 5.75
+\end{equation}
+
+
+Floating-point numbers\cite{goldberg1992thedesign} are the binary equivalent of scientific notation:
+each number consisting of an exponent ($e$) and a mantissa ($m$) such that a number is given by
+\begin{equation}
+ n = 2^{e} \times m
+\end{equation}
+
+The IEEE 754 standard\cite{ieee754std1985} defines several floating-point data types
+which are used\footnote{Many systems' implement the IEEE 754 standard's storage formats,
+but do not implement arithmetic operations in accordance with this standard.} by most
+computer systems. The standard defines 32-bit (8-bit exponent, 23-bit mantissa, 1 sign bit) and
+64-bit (11-bit exponent, 53-bit mantissa, 1 sign bit) formats\footnote{The 2008
+revision to this standard\cite{ieee754std2008} adds some additional formats, but is
+less widely supported in hardware.}, which can store approximately 7 and 15 decimal digits
+of precision respectively.
+
+Floating-point numbers behave quite differently to integers or fixed-point numbers, as
+the representable numbers are not evenly distributed. Large numbers are stored to a lesser
+precision than numbers close to zero. This can present problems in documents when zooming in
+on objects far from the origin.
+
+IEEE floating-point has some interesting features as well, including values for negative zero,
+positive and negative infinity and the ``Not a Number'' (NaN) value. Indeed, with these values,
+IEEE 754 floating-point equality does not form an equivalence relation, which can cause issues
+when not considered carefully.\cite{goldberg1991whatevery}