Quantum Machine Learning – An analysis of expertise, research and applications

This study aims to provide a meaningful, reliable assessment of the state of development of current quantum computing technologies. All the essential concepts of quantum computing will be presented concisely and comprehensibly, and their importance for artificial intelligence (AI) and in particular for machine learning (ML) will be explained. We will review the developments of the last several decades and provide an overview of the availability, potential, relevance, and profitability of quantum computers. In addition to the functional principles of quantum computers, we will also present the concepts of hardware implementation, because not all quantum computers are created equal. There is a distinction between universal quantum computers and so-called “quantum annealers”, which are comparatively simple in their structure and are only suited for very specific tasks. One particular feature of the technical implementation of quantum computers is the extreme cooling down to temperatures near absolute zero, which makes building quantum computers technologically challenging and expensive. We will illustrate the practical capabilities of quantum computers using specially selected examples that show how quantum algorithms are used to search massive databases and solve complex systems of equations and combinatorial optimization problems. In particular, algorithms that predict the behavior of dynamic systems and simulation, optimization, and encryption algorithms can be improved by using quantum processes and have great potential for real-world applications.

  • Published in:
    Fraunhofer Big Data and Artificial Intelligence Alliance
  • Type:
    Article
  • Authors:
    C. Bauckhage, E. Brito, I. Daase, L. Franken, B. Georgiev, D. Hecker, A. Paschke, N. Piatkowski, T. Soddemann, D. Trabold
  • Year:
    2020

Citation information

C. Bauckhage, E. Brito, I. Daase, L. Franken, B. Georgiev, D. Hecker, A. Paschke, N. Piatkowski, T. Soddemann, D. Trabold: Quantum Machine Learning – An analysis of expertise, research and applications, Fraunhofer Big Data and Artificial Intelligence Alliance, 2020, https://www.researchgate.net/publication/357635403_QUANTUM_MACHINE_LEARNING_-_An_analysis_of_expertise_research_and_applications, Bauckhage.etal.2020,