Isogeny Graphs: Eigenvalues and Cryptography

Explores characteristic polynomials, similarity of matrices, and eigenvalues in linear transformations.

Explores isogenic graphs, spectral properties, and mathematical applications in modular forms and cryptography.

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.

Covers the process of diagonalizing matrices, focusing on symmetric matrices and the spectral theorem.

Covers the method of diagonalization for determining if a non-square matrix A is diagonalizable.