Covers the basics of Numpy, including importing the library, creating arrays, and performing linear algebra operations.
Explores the Eigenstate Thermalization Hypothesis in quantum systems, emphasizing the random matrix theory and the behavior of observables in thermal equilibrium.
Covers fundamental concepts in linear algebra, including linear equations, matrix operations, determinants, and vector spaces.
Explores the definition and properties of the metric tensor, enabling control of geometric quantities and lengths.
Explores matrix inversion, conditions for invertibility, uniqueness of the inverse, and elementary matrices for inversion.
