1 Preliminaries
This blueprint follows Fan Chung: Spectral Graph Theory (first published: AMS, 1992).
Unless otherwise specified, all matrices are \(n \times n\) where \(n\) is the number of vertices in \(G\). We omit natural language proofs for theorems that only involve matrix multiplication and basic operations, although we formally prove them in Lean.
1.1 Weighted Graph
We extend the definition of a general graph to that of a weighted graph by defining a weight function over its edges.
with the condition that
We also add an arbitray orientation for undirected edges.
In a graph G, let \(d_v\) denote the degree (number of incident edges) of vertex \(v\).
For \(k \in \mathbb {N}\), a graph is said to be \(k\)-regular if every vertex \(v\) has degree \(d_v = k\).
The volume of a graph is defined as the sum of the degrees of its vertices.
A vertex v is said to be isolated if \(d_v = 0\).
A graph is said to be nontrivial if it contains at least one edge.
1.2 Matrices and Operators
The adjacency matrix of a graph \(G\), denoted \(A\) is defined as follows,
Consider the matrix L, defined as follows
Consider the matrix \(\mathcal{L}\), defined as follows
Let \(T\) denote the diagonal matrix with the \((u,v)\)-th entry having value \(d_v\).
We also define \(T^{-1/2}\) with the convention that \(T^{-1/2} = 0\) when \(d_v = 0\).
The Laplacian of a graph can be viewed as an operator on the space of functions \(g : V(G) \rightarrow \mathbb {R}\).
The Laplacian Operator satisfies
When \(G\) is \(k\)-regular,
where \(k {\gt} 0\), \(A\) is the adjacency matrix of \(G\), and \(I\) is the identity matrix.
For a general graph without isolated vertices, we have
Let \(S\) denote the matrix whose rows are indexed by the vertices and whose columns are indexed by the edges of G. Each column corresponding to an edge \(e = \{ u, v\} \) has an entry \(1/\sqrt{d_u}\) in the row corresponding to \(u\), an entry \(−1/\sqrt{d_v}\) in the row corresponding to \(v\), and has zero entries elsewhere.
We note that \(\mathcal{L}\) can be written as
The Matrix \(\mathcal{L}\) is hermitian.
By spectral theorem.
The Dirichlet sum of a graph \(G\) for a function \(f : \alpha \to \mathbb {R}\) is defined as
Let \(\tau \) denote the constant function which assigns the value \(1\) on each vertex.
\(T^{1/2} * \tau \) is an eigenfunction of \(\mathcal{L}\) with eigenvalue \(0\).
1.3 Basic facts about the spectrum of a graph
The sum of the eigenvalues of the graph is at most its number of vertices, that is
Follows from considering the trace of \(\mathcal{L}\).
In the previous lemma, the equality holds if and only if \(G\) has no isolated vertices.
When \(n{\gt}1\), we obtain the following upper bound on the second eigenvalue: