Near-term Quantum Computing

Course manual 2024/2025

Course content

This course will allow students to gain experience with the implementation of quantum computations or quantum simulations on emulators or quantum hardware. In the near term, such implementations are necessarily done on what are called NISQ devices: Noisy Intermediate Scale Quantum devices. The students will learn about the potential and limitations of concrete qubit platforms: what native gates are available, which noise models apply, how can error mitigation best be done? The students will implement concrete quantum algorithms, such as VQE and QAOA, and analyse their performance.

Study materials

Other

• Lecture notes are provided on a week-by-week basis.

  Quantum computing Labs, in the form of Jupyter notebooks.

  For reference: the Qiskit online textbook and learning labs, https://qiskit.org/learn/

  For reference: a list of textbooks and open-source course materials will be provided during the course.

Objectives

• Describe at a high level the current state of quantum computing and near-term quantum computing, on what are called Noisy Intermediate Scale Quantum devices
• Describe approaches to quantum simulation and their relation to quantum hardware.
• Reason about the potential and limitations of concrete near-term qubit platforms.
• Apply knowledge on qubit architectures by working with Qiskit, a software development kit for working with quantum computers at the level of pulses, circuits, and application modules.
• Apply knowledge by implementing concrete quantum algorithms, such as VQE and QAOA, on both simulation software and quantum hardware and analysing their performance.
• Compare various error mitigation strategies applicable to NISQ devices and evaluate their effectiveness in improving the performance of VQE and QAOA implementations

Teaching methods

• Lecture
• Computer lab session/practical training
• Self-study
• Supervision/feedback meeting
• Working independently on e.g. a project or thesis

Learning activities

Attendance

Additional requirements for this course:

We expect full in-person attendance. Please contact the teachers if you have to miss one or more course sessions.

Assessment

• Individual written test (Nov 12): 30%
• Exam going with on-line course (Nov 26): 20%
• Individual programming exercise (Nov 26): 10%
• Group project (end of course): 40%

Further details will be provided on Canvas and discussed with the students during the first session.

Assignments

After week 3, there will be a written test on background material offered in weeks 1-3.

At the end of week 5, students will be tested on their Qiskit skills. They are also required to individually complete a Jupyter notebook by implementing a quantum algorithm.

In weeks 6-8, students work in groups of two to four on a project to implement a NISQ algorithm of choice on quantum hardware. They report on the implementation and performance.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Contact information

Coordinator

• prof. dr. C.J.M. Schoutens

Staff

• dr. S. Hariharan PhD
• Daan Schoneveld MSc