Lectures related to Hidden Sub-group Problem and Simon Algorithm

Covers the basics of quantum computing, focusing on superconducting qubits, scaling challenges, and potential applications.

Explores quantum random number generation, discussing the challenges and implementations of generating good randomness using quantum devices.

Explores matrix operations, linear systems, solutions, and the span of vectors in linear algebra.

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

Covers orthogonality, scalar products, orthogonal bases, and vector projection in detail.

Explores matrix similarity, diagonalization, characteristic polynomials, eigenvalues, and eigenvectors in linear algebra.