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The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
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These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Algebraic and Spectral Graph Theory — Examples
1 · Prerequisites
- Algebraic and Spectral Graph Theory
- Algebraic Closure, Embeddings, and Separability
- Algebraic Extensions, Extension Degree, and Finite Fields
- Binary Operations, Monoids, Groups and Subgroups
- Composition Series, the Jordan–Hölder Theorem and Solvable Groups
- Congruences, the Integers Modulo n and the Chinese Remainder Theorem
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Continuity, IVT, EVT, and Uniform Continuity
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Cyclic Groups and Direct Products
- Determinants of Matrices over a Commutative Ring
- Diagonalisation and the Minimal Polynomial
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Divisibility, Greatest Common Divisors and Bézout's Identity
- Dual Spaces, Bilinear and Quadratic Forms, and Sylvester's Law of Inertia
- Eigenvalues, Eigenvectors and the Characteristic Polynomial
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Graphs, Walks and Connectivity
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Group Homomorphisms and the Isomorphism Theorems
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Inner Product Spaces, Gram-Schmidt, Projections and Adjoints
- Limits of Real Functions
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Monotone Sequences, Bolzano-Weierstrass, and Cauchy Completeness
- Normal Subgroups and Quotient Groups
- Order, Zorn's Lemma, and the Axiom of Choice
- Polynomial Rings, the Division Algorithm and Roots
- Primes, Euclid's Lemma and the Fundamental Theorem of Arithmetic
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Roots, Rational Powers, and Classical Inequalities
- Sequences and Limits
- Simple Field Extensions and the Construction of the Complex Numbers
- Splitting Fields
- Suprema and Infima
- Sylow's Theorems, p-Groups and Nilpotent Groups
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- The Determinant of a Linear Operator, Cofactors and Cramer's Rule
- The Fundamental Theorem of Algebra
- The Fundamental Theorem of Finite Abelian Groups
- The Galois Correspondence
- The Spectral Theorem, Positive Operators and Singular Value Decomposition
- The ZFC Axioms and the Basic Set Constructions
- Topology of ℝ
- Trees, Forests and Spanning Trees
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
These examples check the page's standard spectral computations on small named graphs and record two false converses that the main theorems do not justify: cospectrality does not force isomorphism, and positive algebraic connectivity detects connectedness rather than -connectedness.
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
The cycle has adjacency spectrum
Example
The cycle graph has adjacency spectrum .
Facts & Assumptions
Given: The cycle graph .
The cycle graph has adjacency eigenvalues for (The cycle graph has adjacency spectrum ).
Verification
Applying [L1] with gives the eigenvalues , , , and .
Reordering these values from largest to smallest yields .
A disconnected graph has a Laplacian kernel spanned by its component indicators
Example
Let have vertex set and edge set . Then
Facts & Assumptions
Given: The graph with components and .
The Laplacian kernel is spanned by the indicator vectors of the connected components (The multiplicity of the Laplacian eigenvalue equals the number of connected components).
Verification
The graph has exactly two connected components, namely and . Their indicator vectors are and .
By [L1], those two indicator vectors span the Laplacian kernel. They are linearly independent, so this displayed span is exactly .
Kirchhoff's formula gives
Example
The complete graph has exactly spanning trees.
Facts & Assumptions
Given: The complete graph .
For a regular graph, (The matrix-tree theorem becomes an eigenvalue product formula).
The adjacency eigenvalues of are (The complete graph has adjacency spectrum ).
Verification
The graph is -regular and has four vertices, so [L1] and [L2] give .
Therefore Kirchhoff's product formula recovers the count .
The graph has adjacency spectrum
Example
The complete bipartite graph has adjacency spectrum .
Facts & Assumptions
Given: The graph .
The graph has adjacency spectrum (The complete bipartite graph has adjacency spectrum ).
Verification
Applying [L1] with gives the eigenvalues , , and .
So the ordered spectrum is .
The two-subset model reproduces the Petersen spectrum
Example
The Petersen graph, realised on the two-element subsets of a five-element set, has adjacency spectrum .
Facts & Assumptions
Given: The Petersen graph on for a five-element set .
This graph is the Petersen graph exactly when adjacency means disjointness of the two-element subsets (The Petersen graph on the two-element subsets of a five-element set, adjacent when disjoint).
The Petersen graph has adjacency spectrum (The Petersen graph has adjacency spectrum ).
Verification
By [F1], the displayed two-subset construction is precisely the Petersen graph, not merely an isomorphic copy under a different naming convention.
Therefore [L1] applies directly and yields the spectrum .
Two cospectral graphs need not be isomorphic
Statement refuted
If two finite simple graphs are cospectral, then they are isomorphic.
Facts & Assumptions
Given: The star and the disjoint union .
The graph has spectrum (The complete bipartite graph has adjacency spectrum ).
The graph has spectrum (The cycle graph has adjacency spectrum ).
Isomorphic graphs have the same spectrum (The adjacency spectrum is an isomorphism invariant).
Cospectral graphs are those with the same adjacency spectrum (Adjacency spectrum, spectral radius, and cospectral graphs).
Counterexample
By [L1], the star has spectrum . By [L2], the cycle has spectrum , so adjoining an isolated vertex contributes one more zero eigenvalue and gives the same spectrum for . Hence the two graphs are cospectral by [F1].
The graphs are not isomorphic, because is connected while is not. Therefore the converse of [L3] fails.
So cospectral graphs need not be isomorphic.
FALSE: positive second Laplacian eigenvalue characterises 2-connectivity
Statement
False claim. A finite simple graph has positive second Laplacian eigenvalue if and only if it is -connected.
Facts & Assumptions
Given: The path graph on vertices .
A graph with positive algebraic connectivity is connected, and conversely (A finite simple graph is connected if and only if its algebraic connectivity is positive).
The algebraic connectivity is the second-smallest Laplacian eigenvalue (The algebraic connectivity of a finite simple graph).
A graph is -connected when deleting any one vertex leaves it connected (Vertex cuts, edge cuts, vertex connectivity and edge connectivity , with conventions for complete and one-vertex graphs).
Refutation
The path is connected, so [L1] and [F1] show that its second Laplacian eigenvalue is positive.
Deleting the middle vertex of leaves two isolated vertices, which is disconnected. Therefore [F2] shows that is not -connected.
So has positive second Laplacian eigenvalue but is not -connected, refuting the claim.
FALSE: the matrix-tree theorem works only for one distinguished cofactor
Statement
False claim. The matrix-tree theorem computes the spanning-tree count from only one special cofactor of the Laplacian; deleting a different row and column can change the answer.
Facts & Assumptions
Given: A finite simple graph .
Every principal cofactor of the Laplacian equals (Kirchhoff's matrix-tree theorem).
Refutation
By [L1], for every vertex index the principal cofactor obtained by deleting row and column has determinant . So the value does not depend on a distinguished choice of index.
This is exactly the negation of the false claim, so the claim is refuted.
Sources
- Steve Butler, Spectral Graph Theory course notes, lecture 3
- Richard P. Stanley, MIT 18.314 handout, The Matrix-Tree Theorem
- Richard P. Stanley, MIT 18.314 handout, Example 1.11
- Richard P. Stanley, MIT 18.314 handout, Problem 1
- Steve Butler, Spectral Graph Theory course notes, lecture 9
- Steve Butler, guest notes on cospectral graphs
- O. Pikhurko, Algebraic Methods in Combinatorics, Section 14.2
- Richard P. Stanley, MIT 18.314 handout, Theorem 1.8