Salman Beigi

 


Linear Algebra

  1. • Lecture 2: Vector space, Dirac’s notation, inner product, change of basis

  2. • Lecture 3: Elementary row/column operations, rank, eigenvalues and eigenvectors

  3. • Lecture 4: Linear operators

  4. • Lecture 5: Matrix representation, functions of operators, adjoint, Schur decomposition

  5. • Lecture 6: Unitary, hermitian, normal, singular value decomposition

  6. • Lecture 7: Direct sum and tensor product of vector spaces: motivation and definition

  7. • Lecture 8: Linear operators on tensor spaces, Schmidt decomposition

Postulates of Quantum Mechanics

  1. • Lecture 9: Postulates of quantum mechanics: state space and measurement

  2. • Lecture 10: Postulates of quantum mechanics, Heisenberg’s uncertainty principle

  3. • Lecture 11: Superdense coding, teleportation, EPR’s hidden variable model

  4. • Lecture 12: Density matrices, ensembles

  5. • Lecture 13: Coding in a quantum state

  6. • Lecture14: Partial trace 1

  7. • Lecture 15: Partial trace 2

  8. • Lecture 16: Purification

  9. • Lecture 17: Quantum CPTP maps 1

  10. • Lecture 18: Quantum CPTP maps 2

  11. • Lecture 19: Trace distance and fidelity

Quantum Information Theory

  1. • Lecture 20: Classical concepts of typicality, KL-divergence, source coding and channel coding

  2. • Lecture 21: Definition of a quantum source and channel, entropic expressions and inequalities

  3. • Lecture 22: Tools from linear algebra, operator monotone and operator convex functions

  4. • Lecture 23: Properties of von Neumann entropy

  5. • Lecture 24: Entropy of measurement, majorization

  6. • Lecture 25: Quantum typicality, Schumacher compression and Fannes-Audenaert inequality

  7. • Lecture 26: Schumacher compression, quantum channel coding (Holevo information)

  8. • Lecture 27: Holevo information 2

  9. • Lecture 28: Entanglement distillation, entanglement of formation, LOCC maps

  1. • Quantum information theory (in Farsi)

   prepared jointly with Amin Gohari

  1. • Quantum computing (in Farsi)

  1. • Lecture 1: Review of the subject

  2. • Lecture 2: Review of linear algebra, Dirac’s notation

  3. • Lecture 3: Postulates of quantum mechanics 1

  4. • Lecture 4: Postulates of quantum mechanics 2

  5. • Lecture 5: Density matrices, partial trace

  6. • Lecture 6: Purification, EPR paradox

  7. • Lecture 7: Quantum circuits

  8. • Lecture 8: Quantum gates, Deutsch-Jozsa algorithm

  9. • Lecture 9: Grover’s algorithm, Shor’s algorithm

  10. • Lecture 10: Quantum CPTP maps

  11. • Lecture 11: Trace distance, fidelity

  12. • Lecture 12: Quantum error correcting codes 1

  13. • Lecture 13: Quantum error correcting codes 2

  14. • Lecture 14: Quantum error correcting codes 3