Quantum Artificial Intelligence

Vorlesung an der Universität des Saarlandes, Fachrichtung Informatik, LSF 159845

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Lecture

1

Welcome

  • Course organization
  • Introduction: Quantum Computing and AI in a Nutshell
  • Q/A

Part I: Quantum Computation

2

Basic Concepts (I)

  • Postulates of Quantum Mechanics
  • Qubits, quantum registers, operations and gates, entanglement, measurement
  • No-cloning theorem
     

3

Basic Concepts (II)

  • Quantum teleportation
  • Implementation in Qiskit

 

4

Quantum Algorithms (I)

  • Quantum parallelism and Deutsch Algorithm
  • Implementation in Qiskit
     

5

Quantum Algorithms (II)

  • Quantum parallelism and Deutsch-Josza Algorithm
     

6

Quantum Algorithms (III)

  • Quantum search and Grover’s Algorithm
  • Implementation in Qiskit
     

Part II: Quantum Computation for AI

7

Quantum Complexity and Quantum Machine Learning (I)

  • Quantum prime factorization and Shor’s Algorithm and HHL (in brief)
  • Quantum Complexity
  • Introduction to Quantum Machine Learning
     

8

Quantum Machine Learning (II)

  • Fault-Tolerant Quantum Algorithms for Supervised Learning
  • Variational Quantum Algorithms and Quantum Neural Networks
     

9

Quantum Machine Learning (III)

  • Implicit and Explicit Quantum Models: Implementation with Qiskit and Pennylane
  • Introduction to Quantum Reinforcement Learning
     

10

Quantum Machine Learning and Optimization (I)

  • Hybrid quantum reinforcement learning for safe navigation
  • Adiabatic quantum computation in brief
     

11

Quantum Machine Learning and Optimization (II)

  • From NP-hard AI problem to gate-based or adiabatic quantum solution
  • Quantum annealing-based unsupervised image segmentation

 

12

Selected QAI Algorithms for Applications (I)

 

13

Selected QAI Algorithms for Applications (II)
 

14

Selected QAI Algorithms for Applications (III)

 

Selected background references:

Quantum Artificial Intelligence

  1. Klusch, M., Lässig, J., Müssig, D., Macaluso, A., & Wilhelm, F.K. (2024): Quantum Artificial Intelligence: A Brief Survey. Künstliche Intelligenz, 38(4), Springer. Also: arxiv:2408.10726
  2. Acampora, G., Ambainis, A., Ares, N., Banchi, L., Bhardwaj, P., Binosi, D., ... & Wilhelm, F. K. (2025). Quantum computing and artificial intelligence: status and perspectives. arXiv preprint arXiv:2505.23860.
     

Quantum Computing

  1. De Wolf, R. (2023): Quantum Computing: Lecture Notes. arxive 1907.09415
  2. Nielsen, M. & Chuang I. (2002): Quantum Computation and Quantum Information.
  3. Biamonte, J. et al. (2017): Quantum Machine Learning. Nature, 549(7671):195-202.
  4. Rieffel, E. G., & Polak, W. H. (2011). Quantum computing: A gentle introduction. MIT Press.
  5. Kaye, P., Laflamme, R., & Mosca, M. (2007). An introduction to quantum computing. Rinton Press.
  6. Farhi, E., Goldstone, J., & Gutmann, S. (2014). A quantum approximate optimization algorithm. arXiv preprint arXiv:1411.4028.

Artificial Intelligence

  1. Russell, S. & Norvig, P. (2021). Artificial Intelligence: A modern approach. 4th Ed., Pearson Education
  2. Mitchell, T. (1997): Machine Learning. McGraw-Hill
  3. Goodfellow, I.J. et al. (2016): Deep Learning. MIT Press,
  4. Nielsen, M. (2017): Neural Networks and Deep Learning.
  5. http://deeplearning.net
     
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