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Connecting quantum systems through optimized photonics (Prof. J. Vuckovic)

  • Datum: 20.03.2018
  • Uhrzeit: 14:30 - 15:30
  • Vortragende(r): Prof. Dr. Jelena Vuckovic
  • Nanoscale and Quantum Photonics (NQP) Lab, Stanford University
  • Raum: New Lecture Hall, Room B 0.32
  • Gastgeber: MPQ
Semiconductor quantum dot in cavity has been the workhorse of solid-state quantum optics, enabling many exciting demonstrations such as photon blockade, and some of the best quantum light sources and spin-photon interfaces.

However, scaling and integration of multiple systems is a challenge because of quantum dot inhomogeneous broadening. On the other hand, color centers embedded in wide bandgap materials, such as silicon vacancy (SiV) in diamond, exhibit far less inhomogeneous broadening. With this platform, we have recently demonstrated single photon source with cooperativity C=1.5 and Purcell enhancement > 10 (approaching the strong coupling regime of cavity quantum electrodynamics), as well as cavity enhanced Raman scattering from a single SiV for detuning of up to 70GHz. These results are encouraging for implementation of scalable, solid-state quantum networks based on optically interconnected quantum nodes.

However, in addition to high quality quantum devices, successful implementation of such networks requires classical photonic circuits that are scalable, robust to errors, and exhibit minimal losses. In particular, losses in in/out coupling to chips and increased circuit complexities resulting from post-fabrication tuners are particularly detrimental to quantum circuits. Our recent work on inverse design in photonics (which combines methods of optimization / artificial intelligence with photonics) offers a powerful tool to design and implement photonic circuits with superior properties, including robustness to errors in fabrication and temperature, compact footprints, novel functionalities, and greater than 97% coupling efficiencies for very simple designs. This approach is also directly applicable to design of quantum hardware.

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