Lectures related to Uncertainty Principle

Covers linear transformations using matrices, focusing on linearity, image, and kernel.

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

Covers Hermitian and Unitary operators, real number equivalents, and eigenvalues.

Covers angular momentum in quantum physics, creation operators, spin, and matrix elements.

Explores eigenvalue problems, iterative methods, and their applications in quantum physics and network analysis.

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

Covers the reduction of a linear transformation in a 2-dimensional space to find a simpler matrix representation.

Covers the algorithm for matrix decomposition and base change in linear algebra.