Course Identification

1. Classical complexity theory: the boolean circuit model, probabilistic computation, analysis of algorithms, oracle machines and related concepts.

2. Linear algebra: vectors, matrices, eigenvalues, Unitary and Hermitian operators, inner products, norms and related concepts.

3. Probability theory: events, random variables, conditional probability, expectation, variance and related concepts.

4. Algebra: group theory.

No background in physics or quantum mechanics is needed.

This is a basic class in quantum computing, covering basic definitions and algorithms.

1. The quantum model: superposition, measurement, density matrices.

2. Quantum circuits and quantum gates.

3. Effects of quantum entanglement: teleportation, superdense coding, the CHSH game.

4. Quantum Fourier Transform and basic quantum algorithms.

5. Other topics as time permits.

Upon successful completion of the course the students will be able to:

* Understand of the quantum computational model.

* Demonstrate familiarity with quantum algorithms.

We will not follow a particular textbook, but for a very good reference on quantum computing and quantum information, it is always good to refer to "Quantum Computation and Quantum information" by Nielsen and Chuang.