Coherent control and sensitive detection of quantum states in condensed matter are among the most topical challenges of modern physics. They drive the development of novel materials, theoretical concepts, and experimental methods to advance our understanding of fundamental laws of quantum mechanics and to create transformative technologies for future applications. During the past decades carbon has emerged as a new material platform to address these challenges: graphene and carbon nanotubes have been created as paradigm systems with exceptional physical properties.
As atomically-thin cylinders carbon nanotubes combine ultra-low mass with extreme mechanical stiffness. This identifies them as perfect candidates for the realization of ultra-high quality mechanical resonators with applications in quantum metrology and sensing. Their crystalline lattice can be made free of nuclear spins by material engineering to ensure ultra-long electron spin coherence times for quantum information processing and coherent spintronics. In addition, semiconducting single-wall carbon nanotubes exhibit optical resonances with unprecedented tunability in color for quantum communication and cryptography. These outstanding material properties form the basis for our scientific research proposal.
Our vision is to realize up-conversion schemes interfacing light with spin, mechanical, and spin-mechanical degrees of freedom in carbon nanotube devices. In particular, we will study spin dynamics in carbon nanotubes with an isotopically engineered nuclear spin lattice and we will suspend individual carbon nanotubes in high-fidelity optical micro-cavities to detect and control mechanical motion down to the quantum ground state. Ultimately, our devices will realize entirely novel regimes of quantum states by hybridizing light with magnetic or mechanical excitations and explore the foundations of emerging technologies at the quantum limit.
Field of science
- /natural sciences/physical sciences/quantum physics
- /natural sciences/computer and information sciences/data science/data processing
Call for proposal
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