Graphs have nodes, and edges that connect nodes
We are interested in graph isomorphisms specifically
Definition: Graph Isomorphism
Graphs and are isomorphic if we can construct a bijection between vertex sets s.t. are adjacent iff are adjacent
i.e. adjacent vertices are mapped to adjacent vertices
Turns out it's not easy to see whether graphs are isomorphic at first glance, esp with large number of nodes/vertices #-> this is mostly recap from Ted GT class
Definition: Lie Algebra
A Lie Algebra is a vector space with a bilinear operation called the Lie bracket with
1) for all
2) (implied by 1 and bilinearity)
3) for all
Example: We see that with cross product is a Lie algebra
according to right hand rule, and we can validate that the Jacobi identity works
Another example: If is an associative -algebra (i.e. an -vector space equipped with bilinear associative operation ).
For all , define the commutator .
An explicit example of this would be , the set of all matrices over with the Lie brackets defined as .
Lie Algebras are an approdimation of the notions of symmetry, which are easy to work in.
Definition: Just Some Notations/ideals
The lie algberas we look at are nilpotent and solvable.
Definition: Lie Algebra Isomorphisms
A **Lie Algebra Isomorphism is a Lie Algebra Homomorphism that is also a Vector Space Isomorphism.
Formally, s.t. for all
Vector space isomorphism: Linear, bijection, thus dim equal and implies
Examples:
- Identity map is a Lie Algebra to itself
- If the brackets are trivial ( and ), then they are isomorphic iff dim are the same
Theorem: Isomorphism On N X N Matrices
If we take as the Lie algebra given by all matrices over field with the commutator as the Lie Bracket, then the map
Definition: Lie Algebra Associated On a Graph
Let be a simple graph (no self loops). Let be a vector space.
We define the bracket by
All other brackets not defined by linearity are zero.
The vector space with this braket operation is the Lie algebra associated with .
Because it acts as a vector space, we can have linear combinations and it's more powerful than just an adjacency matrix
We can compare graphs via the Lie Algebras as well! cool beans.
Because the Lie Algebra structure is mapped to the graph structure, we can reduce graph isomorphisms to Lie Algebra isomorphisms.
Theorem: Mainkar's Theorem
Let be graphs. Then, iff .
Forward direction is intuitive, because Lie Algebra structure relies on graph structure
We see that we can embed graph theory into lie theory.
Applications:
- Embeds simple graphs into Lie Algebras
- Helps categorize a subgroup (2 step nilpotent, solvable) of Lie Algebras
- May allow us to take results from Graph Theory (like Hall's Marriage Problem) and restate them in terms from Lie Theory, or vice versa