Position:  Research Associate

Current Institution:  University of Washington

Abstract:  Integrated Photonic Circuits for Single Quantum Emitters

An entangled graph state of qubits is a valuable resource for both universal quantum computation and quantum communication. To date, entanglement generation rates are too low to realize these multi-qubit networks due to photon emission into unwanted spatial and spectral modes. The integration of crystal, defect-based qubits with photonic circuits can significantly enhance photon collection efficiency, albeit at the cost of degrading the defect’s optical properties, such as an increase in inhomogeneous emission energies (linewidth broadening of GHz vs a few tens of MHz) and decreased spectral stability (spectral diffusion of tens of GHz vs a few hundred MHz). Compensating for this static and dynamic spread in emission energies is of critical importance for scalable on-chip graph state generation. We demonstrate the ability to tune the emission energy of photonic device-coupled near-surface NV centers over a large (200 GHz) tuning range with applied bias voltage. This is larger than the inhomogeneity of implanted NV centers, suggesting a viable route for indistinguishable photons from separate emitters. However, measurements on many single waveguide-coupled NV centers highlight the variability in response to an applied bias voltage. Despite this variability, we are able to apply real-time voltage feedback control to partially stabilize the emission energy of a device-coupled NV center.

Bio:
Emma R. Schmidgall is a research associate in Professor Kai-Mei Fu’s group at the University of Washington.  She received a PhD from Technion-Israel Institute of Technology in 2016, a master’s degree in Nanomaterials from Imperial College London, a master’s in physics from the University of Cambridge, and bachelor’s degrees in physics and history from the California Institute of Technology (Caltech).  Se was a Marshall Scholar in 2007-2009 and Intelligence Community Postdoctoral Fellow in 2016-2018.