Nitrogen-vacancy centres: a model system for learning and sensing experiments

25 October, 2018 @ 3:00 pm

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Efficient modelling and validation of a quantum system’s Hamiltonian – like trapped ions and atoms, quantum dots, 2D-materials or colour centres – is intractable to classical computers [1], in particular when these physical systems are scaled-up or reach higher complexities [2]. The electron spin of a negatively charged nitrogen-vacancy center (NV-) in diamond is a perfect model system of such a Hamiltonian. It allows optical initialisation and readout of its ground state electronic spin, which may subsequently be manipulated using microwave fields. Its long spin coherence times, even at room-temperature, allow its use for quantum information processing [3].
In this talk, I’ll give a short introduction into colour centres and then highlight two recent experiments. First, I’ll show how the electron spin dynamics of an NV- centre in bulk diamond can be used to experimentally demonstrate Quantum Hamiltonian Learning (QHL) on a programmable silicon-photonics quantum simulator [5]. Here, QHL is able to efficiently validate predictions for quantum systems given by model Hamiltonians [3]. Second, I’ll show machine learning algorithms can be applied to the single spin NV- centre to achieve a magnetic sensitivity that scales with the Heisenberg limit [6]. In this so-called Magnetic-Field Learning (MFL) protocol we demonstrate how dephasing times can be simultaneously estimated, and that time-dependent fields can be dynamically tracked at room temperature. Our results dramatically increase the practicality of single spin sensors, which used to be limited to cryogenic temperatures.


  1. R. P. Feynman. Simulating physics with computers. International J. of theoretical physics, 21, 467-488,1982.
  2. Y. C. Chen et al. Laser writing of coherent colour centres in diamond. Nat. Photon. 236, 2016.
  3. F. Jelezko et al. Observation of coherent oscillations in a single electron spin. Phys. Rev. Lett. 92, 1-4, 2004.
  4. N. Wiebe et al. Hamiltonian learning and certification using quantum resources. Phys. Rev. Lett. 112, 190501, 2014.
  5. J. Wang et al. Experimental quantum Hamiltonian learning. Nat. Physics., DOI: 10.1038/NPHYS4074, 2017.
  6. R. Santagati*, A. A. Gentile*, S. Knauer* et al. Magnetic-field-learning using a single electronic spin in diamond with one-photon-readout at room temperature. arXiv1807.09753, 2018.


25 October, 2018
3:00 pm


Old Main Building, UNSW
Room G59, Old Main Building, UNSW Kensington Campus NSW Australia


University of New South Wales