Turbulence Phenomenology

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

Covers the diagonalization of linear transformations in R^3, exploring properties and examples.

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

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

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

Explores diagonalization of matrices, similarity relations, and eigenvectors in linear algebra.

Explores eigenvalues and eigenvectors in matrix transformations, essential for understanding mathematical and real-world systems.

Explores the diagonalization of linear maps by finding a basis formed by eigenvectors.

Covers the Bloch sphere representation and Larmor precession in spin 1/2 systems.

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