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402-0810-70L 6 Credits MSC D-ITET , D-PHYS

Advanced Quantum Algorithms (University of Zurich)

Lecturers & Examiners: Dr. Guglielmo Mazzola
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH as an incoming student. UZH Module Code: PHY582 Mind the enrolment deadlines at UZH:
VVZ CR n/a

Last Updated: 2026-02-05 16:29:43

Abstract

The course treats selected families of quantum algorithms, currently the best candidates to achieve a practical quantum advantage over classical computation in physics, chemistry, optimization, sampling and machine learning.Starting from the basics, quantum algorithms are introduced and their feasibility to solve real-world problems in science and industry is critically discussed.

Objective

The course aims to provide a balanced outlook of this transformative technology, discussing strengths and possible limitations of all discussed algorithms, especially in the context of concrete today and future hardware implementation. After the course, students will have a clear understanding of the state- of-the-art of this field (i.e., the applications and algorithms amenable to quantum speedup, types of hardware, and quantum software). The course content is devised to provide first-hand experience with quantum algorithms and stimulate critical thinking. The course will be instrumental for the student's career development in quantum technology and computational science, in academia or industry.

Content

Course content: -) Quantum gates and circuits basics -) Quantum annealing -) Hamiltonian simulations (Trotter, LCU, circuit decompositions) -) Mapping fermionic, bosonic operators to qubits -) Quantum phase estimation and applications -) Variational quantum algorithms (VQE, QAOA) -) Algorithms for sampling and search (Amplitude amplification, estimation, quantum walks, quantum enhanced Markov chains) -) Selected Quantum Machine learning algorithms -) Prospects for quantum advantage

Resources

Lecture Notes

Lecture notes covering in detail all the course content will be provided.

Literature

-) My lecture notes and references therein which are open-access will be more than enough to follow. -) For an introduction to quantum computing and information it could be useful to read specific chapters of Nielsen and Chuang book.

General Information

Language
English
Levels
MSC
Frequency
Yearly recurring

Examination

Type
graded semester performance
Registration modalities, date and venue of this performance assessment are specified solely by the UZH.

Course Components

Type Title Time & Place Hours
lecture Advanced Quantum Algorithms (University of Zurich)
**Course at University of Zurich**
  • Wed 13:00-14:45
  • Wed None-None
2 h weekly
exercise Advanced Quantum Algorithms (University of Zurich)
**Course at University of Zurich**
  • Wed 15:00-15:45
  • Wed None-None
1 h weekly

Offered In