Course manual 2018/2019
Course content
The goal of this course is to introduce students to the quantum model of computation and some of the most important quantum algorithms and quantum information processing protocols.
 Bits and qubits. Deterministic and probabilistic bits. Complex numbers, quantum bits, and the Bloch sphere. Quantum measurements, global and relative phases.
 Linear algebra. Review of linear algebra: vectors and matrices, inner product and matrix multiplication, Dirac braket notation, eigenvalues and eigenvectors, unitary matrices, tensor product.
 Quantum mechanics. Postulates of quantum mechanics: quantum states, their evolution and measurement, product and entangled states.
 Quantum computation. The model of quantum computation. Quantum gates and circuits. Deutsch’s algorithm.
 Elementary quantum algorithms. Quantum oracles, phase kickback. Deutsch's algorithm. Quantum programming with Cirq.
 Algorithms based on the Hadamard transform. DeutschJozsa, BernsteinVazirani, Simon's algorithms.
 Quantum information. Basic protocols: quantum key distribution, superdense coding, quantum teleportation, entanglement swapping.
 Quantum search. Grover’s search algorithm: reflections, Grover rotation, geometric analysis of the algorithm.
 Quantum Fourier transform and phase estimation. Fourier transform, its implementation, application to phase estimation.
 Order finding and factoring. Shor’s algorithm for factoring: order finding and factoring.
 Mixed states, quantum operations, graphical notation. Mixed states, superoperators, tensor networks.
 Quantum nonlocality and entanglement. Bell's inequality, nonlocal games.
 Quantum error correction. Stabilizer formalism, basic quantum error correcting codes.
 Classical and quantum complexity. Turing machine, basic classical and quantum complexity classes and their relationships.
Study materials
Literature
Kaye P., Laflamme R., Mosca M. (2007). An Introduction to Quantum Computing. Oxford University Press.
Mermin N.D. (2007). Quantum Computer Science: An Introduction. Cambridge University Press.
Lipton R.J., Regan K.W. (2014). Quantum Algorithms via Linear Algebra: A Primer. MIT Press.
Nielsen M.A., Chuang I.L. (2010). Quantum Computation and Quantum Information. Cambridge University Press.
Syllabus
Software
Objectives
At the end of the course students should understand:
 basic principles of quantum mechanics, the formalism and computational model used in quantum computing,
 main quantum algorithms and their analysis,
 main quantum protocols such as teleportation and superdense coding,
 entanglement and its role in quantum computing,
 basics of quantum error correction,
 how the quantum model relates to classical models of deterministic and probabilistic computation,
 Cirq language and be able to implement a given quantum algorithm in Cirq.
Teaching methods
 Lecture
 Computer lab session/practical training
 Selfstudy
Learning activities
Activiteit  Uren 
Hoorcollege  28 
Tentamen  3 
Werkcollege  28 
Zelfstudie  109 
Totaal  168  (6 EC x 28 uur) 
Attendance
Programme's requirements concerning attendance (OERB):

Each student is expected to actively participate in the course for which he/she is registered.

If a student can not be present due to personal circumstances with a compulsory part of the programme, he / she must report this as quickly as possible in writing to the relevant lecturer and study advisor.

It is not allowed to miss obligatory parts of the programme's component if there is no case of circumstances beyond one's control.

In case of participating qualitatively or quantitatively insufficiently, the examiner can expel a student from further participation in the programme's component or a part of that component. Conditions for sufficient participation are stated in advance in the course manual and on Canvas.

In the first and second year, a student should be present in at least 80% of the seminars and tutor groups. Moreover, participation to midterm tests and obligatory homework is required. If the student does not comply with these obligations, the student is expelled from the resit of this course. In case of personal circumstances, as described in OERA Article 6.4, an other arrangement will be proposed in consultation with the study advisor.
Assessment
Inspection of assessed work
Via Canvas.
Assignments
There will be 3 assignments (one every two weeks) that are graded and contribute towards the final grade.
Exercises done during the exercise classes will not be graded.
Fraud and plagiarism
The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl
Course structure
Week 
Topic 
Study material 
1 
Probabilistic bits, qubits, review of linear algebra 
lecture notes 
2 
Quantum mechanics and the quantum computational model 
lecture notes 
3 
Basic quantum algorithms 
lecture notes 
4 
Quantum information, quantum search 
lecture notes 
5 
Fourier transform, phase estimation, factoring 
lecture notes 
6 
Mixed states, superoperators, nonlocality and entanglement 
lecture notes 
7 
Quantum error correction, classical and quantum complexity 
lecture notes 
8 
Exam 

The schedule for this course is published on DataNose.
Coordinator