Quantum Control

Our institute combines techniques from quantum optimal control with applications in few- and many-body systems for the development of quantum technologies.

Head: Prof. Dr. Tommaso Calarco

News and Events

Detailaufnahme des OpenSuperQ

Helmholtz Quantum Center Launched

Jülich, 28 January 2020 – Quantum computer research will be established at Forschungszentrum Jülich as a national priority. The Helmholtz Quantum Center (HQC) will be a central technology laboratory which will cover the entire range of quantum research – from investigating quantum materials to developing prototypes. The project, which is funded by the Helmholtz Association with almost € 50 million, is launching in January 2020.

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PGI Colloquium: Prof. Dr. Tobias Kampfrath, FU Berlin & Fritz Haber Institute, Berlin, Germany

To take advantage of the electron spin in future electronics, spin angular momentum needs to be transported and detected. Electric fields and temperature gradients have been shown to efficiently drive spin transport at megahertz and gigahertz frequencies. However, to probe the initial elementary steps that lead to the formation of spin currents, we need to launch and measure transport on much faster, that is, on femtosecond time scales.

Focus

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Optimal Control

Quantum optimal control is concerned with developing innovative and efficient approaches to manipulate quantum systems. This might be achieved by avoiding adverse effects, such as decoherence or the population of undesired states, and by exploiting numerical optimizations.

Few Body Systems

Few-Body Systems

A microscopic understanding of quantum systems is crucial for their engineering. Detailed knowledge about the interactions within a system as well as its coupling to external fields can provide opportunities for accurate quantum state manipulation and quantum sensing.

Few Body Systems

Many-Body Systems

The quest for a better theoretical understanding and experimental exploitation of many-body phenomena motivates us to develop and apply innovative control approaches as well as numerical simulation techniques such as tensor network algorithms.