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Training Schrödinger’s cat: quantum optimal control

Strategic report on current status, visions and goals for research in Europe

The European Physical Journal D volume 69, Article number: 279 (2015) Cite this article

Abstract

It is control that turns scientific knowledge into useful technology: in physics and engineering it provides a systematic way for driving a dynamical system from a given initial state into a desired target state with minimized expenditure of energy and resources. As one of the cornerstones for enabling quantum technologies, optimal quantum control keeps evolving and expanding into areas as diverse as quantum-enhanced sensing, manipulation of single spins, photons, or atoms, optical spectroscopy, photochemistry, magnetic resonance (spectroscopy as well as medical imaging), quantum information processing and quantum simulation. In this communication, state-of-the-art quantum control techniques are reviewed and put into perspective by a consortium of experts in optimal control theory and applications to spectroscopy, imaging, as well as quantum dynamics of closed and open systems. We address key challenges and sketch a roadmap for future developments.

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Authors and Affiliations

  1. Department Chemie, TU-München (TUM), Lichtenbergstrasse 4, 85747, Garching, Germany

    Steffen J. Glaser & Thomas Schulte-Herbrüggen

  2. CNRS, CMAP École Polytechnique, Palaiseau, France and Team GECO, INRIA Saclay, Ile-de-France

    Ugo Boscain

  3. Institute for Complex Quantum Systems and Center for Integrated Quantum Science and Technology, University of Ulm, Albert-Einstein-Allee 11, 89069, Ulm, Germany

    Tommaso Calarco

  4. Theoretische Physik, Universität Kassel, Heinrich-Plett-Str. 40, 24132, Kassel, Germany

    Christiane P. Koch

  5. Sir Peter Mansfield Magnetic Resonance Centre, University of Nottingham, University Park, NG7 2RD, UK

    Walter Köckenberger

  6. Institute of Chemistry, the Fritz Haber Research Center for Molecular Dynamics, The Hebrew University, 91904, Jerusalem, Israel

    Ronnie Kosloff

  7. School of Chemistry, University of Southampton, University Road, Southampton, SO17 1BJ, UK

    Ilya Kuprov

  8. Institut für Organische Chemie and Institut für Biologische Grenzflächen, Karlsruher Institut für Technologie (KIT), Fritz-Haber-Weg 6, 76131, Karlsruhe, Germany

    Burkhard Luy

  9. College of Science, Swansea University, Singleton Park, Swansea SA2 8PP, Wales, UK

    Sophie Schirmer

  10. Laboratoire Interdisciplinaire Carnot de Bourgogne (ICB), UMR 6303 CNRS-Université de Bourgogne-Franche Comté, 9 avenue A. Savary, BP 47 870, 21078, Dijon Cedex, France

    Dominique Sugny

  11. Institute for Advanced Study, Technische Universität München, Lichtenbergstrasse 2a, 85748, Garching, Germany

    Dominique Sugny

  12. Theoretische Physik, Saarland University, 66123, Saarbrücken, Germany

    Frank K. Wilhelm

Authors
  1. Steffen J. Glaser
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  2. Ugo Boscain
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  3. Tommaso Calarco
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  4. Christiane P. Koch
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  5. Walter Köckenberger
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  6. Ronnie Kosloff
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  7. Ilya Kuprov
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  8. Burkhard Luy
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  9. Sophie Schirmer
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  10. Thomas Schulte-Herbrüggen
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  11. Dominique Sugny
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  12. Frank K. Wilhelm
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Corresponding author

Correspondence to Frank K. Wilhelm.

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Glaser, S., Boscain, U., Calarco, T. et al. Training Schrödinger’s cat: quantum optimal control. Eur. Phys. J. D 69, 279 (2015). https://doi.org/10.1140/epjd/e2015-60464-1

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  • DOI: https://doi.org/10.1140/epjd/e2015-60464-1

Keywords

  • Quantum Information