Isogeny Graphs: Eigenvalues and Cryptography

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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.

Explores pseudorandomness theory, AI challenges, pseudo-random graphs, random walks, and matrix properties.

Explores eigenvalues and eigenvectors in 3D linear algebra, covering characteristic polynomials, stability under transformations, and real roots.

Explores eigenvalues and eigenvectors, demonstrating their importance in linear algebra and their application in solving systems of equations.

Covers diagonalization of matrices, eigenvectors, linear maps, and least squares method.

Introduces differential forms on manifolds, covering tangent bundles and intersection pairings.