Lectures related to Character of Dirac and Projectors

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

Covers the theory and examples of diagonalizing matrices, focusing on eigenvalues, eigenvectors, and linear independence.

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

Explores diagonalization through projectors and matrices of projection in relation to eigenvalues and eigenvectors.

Explains the diagonalization of matrices, criteria, and significance of distinct eigenvalues.

Explores eigenvalues and eigenvectors in matrices through examples and calculations.

Covers the concept of diagonalization of matrices through the study of eigenvectors and eigenvalues.

Explores symmetries in linear algebra, focusing on matrices and their properties.

Covers the basics of programming in Matlab, focusing on interactive usage, mathematical operations, vectors, matrices, strings, and 3D matrices.

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

Covers the decomposition of a matrix into its eigenvalues and eigenvectors, the orthogonality of eigenvectors, and the normalization of vectors.

Explains the diagonalization of linear transformations using eigenvectors and eigenvalues to form a diagonal matrix.

Explores the Eigen library for linear algebra, covering vectors, matrices, arrays, memory management, reshaping, and per-component operations.

Explores the diagonalization of matrices through eigenvalues and eigenvectors, emphasizing the importance of bases and subspaces.

Explores canonical basis, linear mapping, and eigenvalues in linear algebra.

Covers the solution of linear equations and operations with matrices and vectors.

Explores symmetric matrices, quadratic forms, diagonalization, and definiteness with examples and calculations.

Covers the calculation of eigenvalues and eigenvectors, emphasizing their significance and applications.

Covers the linearization of flow around a point, eigenvalues, eigenvectors, and critical points.

Explains eigenvalues and eigenvectors, focusing on real solutions and their properties.