Computational Quantum Physics

Related lectures (30)

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

Covers the goals and motivations of representation theory, focusing on associative algebras and homomorphisms.

Covers electronic structure calculations using quantum mechanics and introduces fundamental concepts in computational quantum chemistry.

Covers eigenvalues, eigenfunctions, Hermitian operators, and the measurement of observables in quantum chemistry.

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

Explains the diagonalization of linear transformations using eigenvectors and eigenvalues to form a diagonal matrix.

Covers computational methods focusing on paths and strings, including examples of concatenation, regex elements, and string operations.

Covers projectors on invariant subspaces in quantum physics and their applications.

Explores the diagonalization of matrices through eigenvalues and eigenvectors, emphasizing the importance of bases and subspaces.

Covers the concept of asymptotic states and S-matrix in quantum field theory, focusing on the evolution of wave packets and the scattering states.