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Postgraduate course

Quantum Information, Quantum Computing, and Quantum Cryptography

  • ECTS credits10
  • Teaching semesterSpring
  • Course codeINF241
  • Number of semesters1
  • LanguageEnglish
  • Resources

ECTS Credits

10

Level of Study

Bachelor/Master/PhD

Full-time/Part-time

Full-time

Teaching semester

Spring

Objectives and Content

Objectives:

The course will teach the subject of quantum information theory, with its application to quantum computation and quantum cryptography ( in the context of both quantum-secure primitives and quantum attack scenarios). Depending on time, there may also be a very brief discussion of the potential application of quantum computing in the context of machine learning. The course will cover the following basics (probability theory, vector spaces, and linear algebra will also be taught if necessary)

Content:

  • Postulates of quantum mechanics (Hilbert, unitary and stochastic dynamics, density operators
  • Quantum Entanglement and classifications, Nonlocality, Bell Inequalities, Tsirelson's bound
  • Quantum Measurement Theory (POVMs ... etc)
  • No-Cloning Theorem, Dense Coding, Teleportation
  • Classical and quantum entropy and channel capacities, distance measures, fidelity
  • Quantum Algorithms: Shor, Grover, MBQC .... etc
  • Quantum Cryptography - Quantum Key Distribution (QKD), quantum protocols, min-entropy, privacy amplification, device-independent quantum cryptography, secure quantum channels, lattice-based cryptosystems
  • Quantum Graph States, Topological Quantum Computation
  • Various current Quantum Computer physical implementations
  • Quantum machine learning

Learning Outcomes

Knowledge

  • Understand quantum information theory, quantum computation, quantum cryptography and related topics.
  • Understand density operators, quantum superposition, entanglement, nonlocality, teleportation
  • Understand quantum channels, quantum algorithms, measurement theory, Bell inequalities, no-cloning theorems
  • Familiarity with quantum graph states, topological quantum computation
  • Aware of some state-of-the-art physical implementations
  • Understand developing concepts wrt quantum machine learning.

Skills

  • Able to apply his/her knowledge of quantum information theory, computation, and cryptography to up-and-coming problems
  • Expertise in quantum mechanics with reference, in particular, to quantum computation and quantum cryptography.
  • Ability to assess post-quantum crypto schemes from a quantum viewpoint.
  • Ability to assess and understand new developments in quantum computing.

General Competence

  • the potential for further independent research into the areas of quantum information, computing, and cryptography.
  • ability to convey the basic fundamentals of the course to others.
  • no ethical issues

Required Previous Knowledge

None

Recommended Previous Knowledge

Any prior knowledge of discrete mathematics, statistics, theoretical physics , quantum mechanics, will, of course, be useful, but is not essential as the topics will be taught taking into account the prior knowledge of the students.

Access to the Course

Access to the course requires admission to a programme of study at The Faculty of Mathematics and Natural Sciences

Teaching and learning methods

Weekly lectures, class web page with many links to extra-curricular topics of relevance and interest. Assignments. Group sessions will usually be lectures. All lectures will involve question and answer sessions and interaction will be encouraged.

Compulsory Assignments and Attendance

There will be assignments, both compulsory and voluntary, as well as suggested extra-curricular studies for the students. The compulsory exercises are valid for two semesters, including the semester in which they are approved.

Forms of Assessment

Written exam 3 hours. Compulsory exercises may count towards the final grade. Both the exam and the compulsory exercises must be passed.

Examination Support Material

Non-programmable calculator, according to the faculty regulations

Grading Scale

The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.

Assessment Semester

Examination both spring semester and autumn semester. In semesters without teaching the examination will be arranged at the beginning of the semester.

Reading List

The reading list will be available within June 1st for the autumn semester and December 1st for the spring semester

Course Evaluation

The course will be evaluated by the students in accordance with the quality assurance system at UiB and the department.

Programme Committee

The Programme Committee is responsible for the content, structure and quality of the study programme and courses.

Course Coordinator

Course coordinator and administrative contact person can be found on Mitt UiB, or contact Student adviser

Course Administrator

The Faculty of Mathematics and Natural Sciences represented by the Department of Informatics is the course administrator for the course and study programme.

Contact

Contact Information

Student adviser:

Student adviser

T: 55 58 42 00

Exam information

  • For written exams, please note that the start time may change from 09:00 to 15:00 or vice versa until 14 days prior to the exam. The exam location will be published 14 days prior to the exam. Candidates must check their room allocation on Studentweb 3 days prior to the exam.

  • Type of assessment: Written examinat

    Date
    19.05.2020, 15:00
    Duration
    3 hours
    Withdrawal deadline
    05.05.2020