Prospectus

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Quantum Algorithms

Course
2024-2025

Admission requirements

Assumed prior knowledge

To be able to follow the course, the students should have basic knowledge of mathematics and computer science. More specifically the course will strongly rely on:

  • working knowledge of basic linear algebra, including matrix manipulations;

  • working with complex numbers;

  • basics of algorithms and computational complexity theory.

Understanding of basics of computability theory (or mathematical theories of computation, e.g. Turing machines, lambda calculus) is beneficial. No previous knowledge in physics, quantum mechanics or quantum information is required.

Description

Quantum computing is a relatively novel model of computation which has served as a hot buzz word in science writing for years. It is often singled out as one of the upcoming technologies which will revolutionize our world. Despite all the popularity and research efforts, the power quantum computing is still widely misunderstood and misrepresented. Moreover, very often it is claimed that for a genuine understanding of quantum computing one requires expertise in quantum physics; in this course you will see that this is not the case.
In this course you will learn:

  • what quantum computing is,

  • how quantum algorithms work, and

  • what quantum computers are actually useful for.

Throughout the course you will also have the possibility to write programs for a quantum computer and, conditions permitting, run your programs on a real quantum computer. The emphasis of the course is on quantum algorithm theory. This course will include formal analyses of quantum algorithms, proofs of correctness and separations, and is recommended for students with affinities towards mathematics and theoretical aspects of computer science.

Course objectives

The objective of this course is to provide the students with a clear overview of the basics of theoretical quantum computing , quantum algorithms and insights into the key applications of quantum computers.
At the end of the course, the successful student will:

  • be able to summarize what the basic elements of quantum computing are (register, gates, measurements) and how to use them (know their mathematical representation) [understanding]

  • be able to calculate the outcomes of small quantum computations on paper given quantum circuits [applying]

  • be able to prove basic identities between quantum computations and prove the basic properties (e.g. correlations of measurements between entangled qubits); [analyzing]

  • be able to construct and simplify quantum computations achieving simple objectives (e.g. evaluate classical functions) [creating]

  • be able to design simple quantum algorithms solving computational problems using computational primitives learned (e.g. algorithm for solving MAJSAT) [creating]

  • be able to describe the workings of selected quantum algorithms and their applications [analyzing]

  • be able to program quantum computing algorithms in a suitable programming language and analyze their performance or to theoretically analyze advanced quantum algorithms [evaluating]

Interested students will also have hands-on experience in programming of basic quantum programs.

Timetable

The most recent timetable can be found at the Computer Science (MSc) student website.

In MyTimetable, you can find all course and programme schedules, allowing you to create your personal timetable. Activities for which you have enrolled via MyStudyMap will automatically appear in your timetable.

Additionally, you can easily link MyTimetable to a calendar app on your phone, and schedule changes will be automatically updated in your calendar. You can also choose to receive email notifications about schedule changes. You can enable notifications in Settings after logging in.

Questions? Watch the video, read the instructions, or contact the ISSC helpdesk.

Note: Joint Degree students from Leiden/Delft need to combine information from both the Leiden and Delft MyTimetables to see a complete schedule. This video explains how to do it.

Mode of instruction

  • Lectures

  • Tutorials

Course load
Total hours of study: 168 hrs. (= 6 EC)
Lectures: 26:00 hrs.
Tutorials: 26:00 hrs.
Projects and assignments: 116:00 hrs.

Assessment method

Students will be evaluated by means of two take-home assignments and a final mini-project, and there will be options for individual and group projects. The average score of the two-take home assignments carry 50% of the final grade, and a final mini-project (carries 50% of the final grade). 50% is the smallest passing grade.
In formulas: THA1, THA2 and MP denote the score for the first, second take home assignment and for the miniproject, respectively. Each score is between 0 and 100.
The final score is FIN = (THA1+THA2)/4 + MP/2, and 50 is passing. Only the total score must be passing. The overall course will have an oral resit for the take-home assignments with a new miniproject if needed.

The teacher will inform the students how the inspection of and follow-up discussion of the exams will take place.

Reading list

  • Nielsen and Chuang, Quantum computation and quantum information.

  • Links to extensive on-line literature to be provided during lectures.

Registration

As a student, you are responsible for enrolling on time through MyStudyMap.

In this short video, you can see step-by-step how to enrol for courses in MyStudyMap.
Extensive information about the operation of MyStudyMap can be found here.

There are two enrolment periods per year:

  • Enrolment for the fall opens in July

  • Enrolment for the spring opens in December

See this page for more information about deadlines and enrolling for courses and exams.

Note:

  • It is mandatory to enrol for all activities of a course that you are going to follow.

  • Your enrolment is only complete when you submit your course planning in the ‘Ready for enrolment’ tab by clicking ‘Send’.

  • Not being enrolled for an exam/resit means that you are not allowed to participate in the exam/resit.

Contact

Lecturer: dr. V. Dunjko
Course announcements and additional materials will be provided on Brightspace.

Remarks

Software
Starting from the 2024/2025 academic year, the Faculty of Science will use the software distribution platform Academic Software. Through this platform, you can access the software needed for specific courses in your studies. For some software, your laptop must meet certain system requirements, which will be specified with the software. It is important to install the software before the start of the course. More information about the laptop requirements can be found on the student website.