Admission requirements
Not applicable.
Description
Quantum computing is an upcoming technology which is expected to have game-changing applications in all computationally-intensive branches of the natural sciences; material sciences, chemistry and physics. Resource-efficient algorithm design is an essential step towards making quantum computers viable for these applications. This is an advanced course for students with understanding of the basics of quantum computing (e.g. for students which have taken Quantum Algorithms at LIACS or Quantum Information at LION), that emphasises practical quantum computing for potential near-term applications. In this course, you will learn about modern quantum algorithmic techniques, and how they are applied in quantum chemistry, quantum many-body physics and machine learning. Furthermore, you will learn about the fundamentals of quantum error correction and error mitigation techniques required to make noisy quantum computers functional.
Course objectives
The students will:
be able to interpret, evaluate, design and optimize quantum circuits;
be able to explain how variational quantum eigensolver and quantum phase estimation works;
know how to apply these quantum algorithms to problems in quantum chemistry and many-body physics;
know how to apply these algorithms to problems in machine learning;
be able to describe noise, quantum error correction and error mitigation.
The algorithms will also be implemented in a python-based language for quantum computing.
Timetable
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
See Brightspace.
Course load
Total hours of study: 168 hrs. (= 6 EC)
Lectures: 28:00 hrs.
Tutorials: 20:00 hrs.
Projects and assignments: 120:00 hrs.
Assessment method
Students will be evaluated by means of two take-home assignments. The average score of the two-take home assignments carry 50% of the final grade, and a final individual 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 the smallest passing passing.
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 the course.
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
Lecturers: dr. V. Dunjko, dr. J. Tura Brugués
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.