Course syllabus

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Course-PM

MCC155 / FCC155 Quantum computing, sp2 HT24 (7.5 hp)

The course is offered by the department of Microtechnology and Nanoscience

Contact details

Administrative support for the Aachen-Chalmers international course exchange:

Student representatives:

Course purpose

The aim of this overview course is to familiarise the students with both important quantum algorithms (such as Grover's algorithm, the quantum Fourier transform, phase estimation, and Shor's algorithm), variational quantum algorithms that utilise an interplay between classical and quantum computers [such as the quantum approximate optimisation algorithm (QAOA) and the variational quantum eigensolver (VQE), among others], and the intersection of quantum computing and machine learning. The course will also give the students practical experience of programming a quantum computer.

Quantum computers are rapidly improving, and recently ”quantum computational primacy” was achieved, i.e., a quantum computer was able to perform a computational task much faster than a classical computer. Quantum computing is expected to have applications in many areas of society. The course prepares the students for applying quantum computation to a variety of important problems.

Schedule

TimeEdit
Time: Mondays 13:15, Thursdays 8:00, Fridays 15:15
Place: Some lectures in SB3-L110, some in SB3-L111; Zoom links are provided for the lectures for the Aachen students (the password is always QC2024)

Course literature

  • Nielsen and Chuang, Quantum Information and Quantum Computation (available at Chalmers STORE, including as an e-book)
  • Course notes (most up-to-date version available on this course homepage; an earlier version is available as a preprint on the arXiv)

Course design

The course consists of 15 lectures, interspersed with four tutorials, one computer exercise, and one Q&A session (see the course program). There are two hand-ins during the course and a written exam at the end (see "Examination form" below). The lectures are blackboard lectures, which mainly provide overviews of how quantum algorithms work. In the tutorials, more examples and calculations are shown. In the computer exercise, you get to try out running quantum algorithms on a real quantum computer. The Q&A session on December 6 gives you an opportunity to ask more questions about exercises and hand-ins.

For each lecture, there is material to read in the lecture notes. There are also suggested exercises connected to each lecture. In general, it is good to get an overview of the course early on, by looking at the program and the lecture notes, and by looking at the examples of earlier exams available here in Canvas. Before each lecture, it is good to read the corresponding parts of the lecture notes. Before or after each lecture, it is good to try the exercises connected to it. The recording of each lecture is uploaded here on Canvas under Pages.

We use Yata to help with the readings and exercises connected to the lectures. These are gathered in Yata under Questions. If you struggle finding the right solution, you can ask for help in the Discussion forum, or you can attend the Q&A session on December 6. In Yata's Discussion forum, you can ask questions to your peers: regarding assignments, course content, or anything related to quantum computing. We encourage everyone to participate actively by posing and answering questions, as well as by upvoting answers. Eduardo and Ariadna will also be participating in the forum every couple of days, and will forward the questions to Anton and Giulia if necessary. For more information about how this works, see the "Welcome to Yata" post in the discussion forum.

Changes made since the last occasion

The lecture on the "variational quantum eigensolver" has been moved to reading; instead, we have a new Q&A session for exercises and hand-ins.

Learning objectives and syllabus

Learning objectives: After completion of the course, the student should be able to

  1. List modern relevant quantum algorithms and their purposes.
  2. Explain the key principles of the various models of quantum computation (circuit, measurement-based, adiabatic model).
  3. Explain the basic structure of the quantum algorithms addressed in the course that are based on the circuit model, and to compute the outcome of basic quantum circuits.
  4. Compare, in terms of time complexity, what quantum advantage is expected from the quantum algorithms addressed in the course with respect to their classical counterparts.
  5. Program simple quantum algorithms on a cloud quantum computer or a cloud simulator.
  6. Understand the basic principles of the continuous variable encoding for quantum information processing.
  7. Give examples of the motivation for applying quantum computing to machine learning and of what the obstacles are to achieving an advantage from doing so.

Content:

  • Elementary quantum gates and basic quantum computing formalism
  • Circuit model for quantum computation
  • Foundational theorems for quantum computation: Solovey-Kitaev theorem; Gottesman-Knill theorem
  • Grover's algorithm
  • Quantum error correction
  • Quantum Fourier transform and phase estimation algorithms
  • Shor’s algorithm
  • Quantum machine learning
  • Quantum cloud computing exercise
  • Other models for universal quantum computation beyond the circuit model: measurement-based quantum computation and adiabatic quantum computation
  • Introduction to complexity classes and relevant conjectures
  • Quantum algorithms for solving combinatorial optimization problems: quantum annealing and QAOA
  • Variational quantum eigensolver
  • Sampling models: boson sampling and instantaneous quantum polynomial
  • Continuous-variable (CV) quantum computation, measurement-based quantum computation in CV and GKP encoding

Link to the syllabus on Studieportalen: Chalmers, University of Gothenburg

Examination form

The assessment comprises two hand-ins and a a final written exam.

The credits distribution is as follows: each of the hand-ins counts for 15% towards the total grade, resulting in 30%, and 2 hp; the written exam counts for 70% towards the final grade, and 5.5 hp. The total points determine the grade (F, 3, 4, 5), according to the cut-offs 50% = 3, 70% = 4, 85% = 5. However, you need to score at least 40% both at the written exam and on the total of the two hand-ins in order to receive a passing grade for the whole course. To just pass the 2 hp for the hand-ins, you need to score 40% in total on the two hand-ins.

For the written exam, you will be allowed to use one A4 page (front and back) of notes that you can prepare beforehand. Computers, cell phones, books, or course notes are not allowed. A basic calculator (not a big scientific calculator) is allowed.

Hand-in 1 is due November 21, 2024.
Hand-in 2 is due December 16, 2024.
The exam takes place in the morning of January 18, 2025.
Re-exams are offered in the afternoon of April 14, 2025 and in the morning of August 29, 2025.

 

Course summary:

Date Details Due