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Section 5.3 Properties of Functions

Worksheet 5.3.1 Worksheet

Guiding Questions.

In this section, we’ll seek to answer the questions:
  • What does it mean for a function to be injective, surjetive, or bijective?
  • What does it mean for two graphs to be isomorphic?
  • What does it mean for a function to have an inverse?
We begin with some definitions.

Definition 5.3.1.

Let \(f: X\to Y\) be a function.
  • We say that \(f\) is injective, or one-to-one (or that \(f\) is an injection), if whenever \(f(a) = f(b)\) we have \(a = b\text{.}\)
  • We say that \(f\) is surjective, or onto (or that \(f\) is n surjection), if for all \(y\in Y\) there exists \(x\in X\) such that \(f(x) = y\text{.}\)
  • If \(f\) is injective and surjective we say it is bijective, or a bijection, or a one-to-one correspondence.

Activity 5.3.3.

Using your answers to ActivityΒ 5.3.2 as a model, explain in words what it means for a function to not be injective, or not be surjective.

Problem 5.3.4.

Give examples of each of the following as well as an informal proof of your claim.
  • A function \(f: \Z\to \Z\) that is injective but not surjective.
  • A function \(f: \Z\to \Z\) that is surjective but not injective.
  • A function \(f: \Z\to \Z\) that is neither injective nor surjective.
  • A function \(f: \Z\to\Z\) that is bijective.

Problem 5.3.5.

Let \(X = \set{1,2,3,4}\text{,}\) \(Y = \set{a,b,c,d,e}\text{,}\) \(f: X\to Y\text{,}\) and \(g: Y \to X\text{.}\) Determine whether or not it is possible for each of the following to be true. Be prepared to share your thinking via an informal proof or a counterexample.
Write a few sentences summarizing your observations.
Functions are helpful tools for characterizing and comparing mathematical objects. An important class of functions relating to graphs are isomorphisms.

Definition 5.3.6.

Let \(G_1 = (V_1, E_1)\) and \(G_2 = (V_2, E_2)\) be graphs. An isomorphism from \(G_1\) to \(G_2\) is a bijection \(f : V_1 \to V_2\) such that \(\set{u,v}\in E_1\) if and only if \(\set{f(u), f(v)}\in E_2\text{.}\) In this case, we say that \(G_1\) and \(G_2\) are isomorphic, and write \(G_1 \cong G_2\text{.}\)

LaTeX Code 5.3.7.

To typeset \(G_1 \cong G_2\) in \(\LaTeX\text{,}\) use G_1 \cong G_2 in math mode.
To explore graph isomorphisms in more detail, an additional definition will be helpful.

Definition 5.3.10.

A cycle on \(n\) vertices, denoted \(C_n\text{,}\) is a graph with vertex set \(V(C_n) = \set{v_1, v_2, \ldots, v_n}\) and edge set
\begin{equation*} E(C_n) = \set{v_1 v_2, v_2 v_3, v_3 v_4, \ldots, v_{n-1} v_n, v_n v_1}, \end{equation*}
where, for \(u,v\in V\text{,}\) we represent the edge \(\set{u,v}\) by \(vu\) or \(uv\text{.}\)

Activity 5.3.11.

For various small values of \(n\text{,}\) draw examples of \(C_n\text{.}\)
For ActivityΒ 5.3.12, recall DefinitionΒ 4.4.5. We note that a graph \(G\) such that \(G\cong G^c\) is called self-complementary.

Activity 5.3.12.

For the same small values of \(n\) as in ActivityΒ 5.3.11, draw \(C_n^c\text{.}\) For any values of \(n\text{,}\) do we have \(C_n \cong C_n^c\text{?}\) If so, justify by explicitly stating the isomorphism. If not, explain why not.
Another important function concept is that of a composition of functions.

Definition 5.3.13.

Let \(f: X\to Y\) and \(g : Y\to Z\text{.}\) We define the composite function (or composition of \(f\) with \(g\)) to be the function \(g\circ f : X \to Z\) by, for each \(x\in X\text{,}\) \((g\circ f)(x) = g(f(x))\text{.}\)

LaTeX Code 5.3.14.

To typeset \(g\circ f\) in \(\LaTeX\text{,}\) use g\circ f in math mode.

Problem 5.3.15.

Let \(X = \set{a,b,c,d,e}\text{,}\) \(Y = \set{1,2,3,4,5}\text{,}\) and \(Z = \set{\alpha,\beta,\gamma,\delta}\text{.}\) Define a function \(f: X\to Y\) by
\begin{equation*} f = \set{(a,3), (b,3), (c,1), (d,2), (e,5)} \end{equation*}
and \(g : Y\to Z\) by
\begin{equation*} g = \set{(1,\gamma), (2,\alpha), (3,\beta), (4,\delta), (5,\gamma)}. \end{equation*}
Fully describe the composite \(h = g\circ f\text{.}\)
Function composition preserves the properties in which we are interested.
This yields a couple of nice results about graphs.