Quantum Artificial Intelligence

Vorlesung an der Universitšt des Saarlandes, Fachrichtung Informatik, LSF 146584


Quantum Artificial Intelligence (QAI) refers to the use of quantum computing and quantum communication for solving computational problems in AI. Unlike classical computation, quantum computing does not follow binary information processing, but quantum mechanical principles of superposition, interference, and entanglement of quantum states of particles. Though there is no strictly common consensus on the interpretation of quantum mechanics for our conception of reality, there is one on the mathematical description and use of quantum mechanical principles for computation. This course on QAI takes the computer science perspective and is structured into two parts: The first part briefly introduces the basic concepts of quantum computation with quantum bits in the gate-based and adiabatic quantum computational models and illustrates these concepts with a few prominent basic quantum algorithms. In the second part, we look at the feasibility and potential benefit of leveraging quantum computational means for solving selected problems of AI, with focus on machine learning, and optimization illustrated by selected quantum AI algorithms with applications in the real world. 


This advanced course aims at advanced master students in Computer Science who preferably hold a B.Sc. degree in this or related field. Good knowledge of AI (introductory course on AI), machine learning, and mathematics  - in particular linear algebra - is required. Selected background references are given on the lectures page. For successful participation in this course (3 CPs), please check the requirements. Attendance of the course without registration to the course exam (no certificate, no CPs) by anyone who is interested in the topics is, of course, very much welcome. The course language is English.

Date and Location:

The course is held on Friday from 10:15 - 12:00, starting from October 27, 2023.

The lectures of this course will be given on-site in the lecturing hall HS02 in the SIC building E1.3 unless stated otherwise in the course schedule (ONLINE). Please frequently check the schedule for changes.