Introduction to Quantum Computing
This course will provide an introduction to the field of quantum computing and information, covering a variety of topics ranging from computation and cryptography to foundations of quantum physics. Once familiar with the fundamentals, we will explore current research topics and discuss how quantum phenomena give rise to new algorithms for machine learning, quantum computational supremacy, cryptographic schemes with unprecedented security guarantees, and device-independent protocols.
As part of the exercises, you will run simple quantum programs on an actual, albeit noisy, quantum computer available through the cloud.
Topics covered include
- Fundamentals of quantum computing (quantum states, superposition, measurement, unitaries)
- The circuit model (qubits, unitary gates)
- Basic protocols (e.g. teleportation, superdense coding, state discrimination)
- Basic quantum algorithms (e.g. Deutch-Josza, Grover, HHL) and the concept of quantum computational supremacy
- Bell inequalities, non-local games and the concept of device-independence
- Basic quantum protocols for cryptography, e.g. quantum key-distribution
- Noisy intermediate scale quantum devices and quantum error-correction
MSc Programme in Mathematics
MSc Programme in Quantum Information Science
MSc Programme in Mathematics with a minor subject
Knowledge: the students will have an understanding of the basic principles of quantum information and computing, including knowledge of basic protocols, applications, and algorithms.
Skills: Carry-out computations corresponding to valid transformations of quantum states as a result of measurement or application of unitary gates.
Competencies: Ability to analyze simple quantum protocols and reason about basic information processing capabilities of quantum computers.
4 hours of lectures and 2 hours of exercise classes per week for 7 weeks.
1) Linear algebra: LinAlg or LinAlgDat course or equivalent
2) Basic probability: SS or DMA or StatFys course or equivalent
Students will receive written individual feedback on their assignement solutions. Collective oral feedback will be given during lectures and exercise classes regarding the problems/questions posed to the class.
- 7,5 ECTS
- Type of assessment
Continuous assessmentOral examination, 25 minutes
- Type of assessment details
- The students' performance will be evaluated via
- 2 individual, equally weighted assignments during the term
- Final oral exam (with 25 minutes preparation), where the student presents one randomly selected topic from a previously known list of topics
The assignments will account for 40% and the oral exam for 60% of the final grade.
- Only certain aids allowed
All aids allowed for the assignments.
Personally handwritten notes on paper allowed during the 25-minute preparation period before the examination.
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
Criteria for exam assessment
The student should convincingly and accurately demonstrate the knowledge, skills and competences described under Intended learning outcome.
Single subject courses (day)
- Theory exercises
- Course number
- 7,5 ECTS
- Programme level
- Full Degree Master
- Block 1
- No limit
The number of seats may be reduced in the late registration period
- Study Board of Mathematics and Computer Science
- Department of Mathematical Sciences
- Faculty of Science
- Albert H. Werner (6-5a6875716875437064776b316e7831676e)
- Laura Mancinska (9-736774696f747971674673677a6e34717b346a71)
- Morten Kjaergaard (11-747271686c796e6868796b4775697035727c356b72)
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