Linear Operators: Basis Transformation and Eigenvalues

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Explores the matrix representation of operators and basis transformation in linear algebra.

Explores vector spaces, linear transformations, matrices, eigenvalues, inner products, and operators.

Explores the application of linear algebra in quantum mechanics, emphasizing vector spaces, Hilbert spaces, and the spectral theorem.

Explains the postulates of Quantum Mechanics, focusing on self-adjoint operators and mathematical notation.

Explores the role of linear operators in Quantum Mechanics and linear algebra, emphasizing eigenvalues and basis transformations.

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

Explores the application of linear algebra in Quantum Mechanics, emphasizing its importance in understanding materials properties.

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

Explores eigenvalue problems, eigenbasis, spectral theorem, and properties of normal operators.

Explains the postulates of quantum mechanics and the representation of observables by operators.