Lectures related to Advanced Physics I: Kinetic Energy and Examples

Introduces eigenspaces in linear algebra through definitions and practical examples of determining eigenspaces for matrices.

Explores the concept of rank in 3x3 matrix representations and how it determines the structure of matrices.

Explores the diagonalization of matrices through similarity transformations and the significance of this process in linear algebra.

Explains the inertia tensor, main axes, principal moments, and balancing of rotating solids.

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

Explores examples of diagonalization in linear algebra, focusing on eigenvalues and eigenvectors.

Explains square matrices, including invertible, triangular, and diagonal matrices, and their properties.