Integrating atomic quantum memories based on color centers in diamond with on-chip photonic devices could enable entanglement distribution over long distances. However, efforts towards integration have been challenging as color centers can be highly sensitive to their environment, and their properties degrade in nanofabricated structures. Here, we describe a heterogeneously integrated, on-chip, III-V on diamond platform for integrating color centers in diamond with nanophotonic devices including photonic crystal cavities and ring-resonators. A key challenge to realizing high quality factor (Q) hybrid photonic crystals is the reduced index contrast on the substrate compared to suspended devices in air. This challenge is particularly acute for color centers in diamond because of diamond's high refractive index, which leads to increased scattering loss into the substrate. Here we develop a design methodology for hybrid photonic crystals utilizing a detailed understanding of substrate-mediated loss, which incorporates sensitivity to fabrication errors as a critical parameter. Using this methodology we design robust, high-Q, GaAs-on-diamond photonic crystal cavities, and by optimizing our fabrication procedure we experimentally realize cavities with Q approaching 30,000 at a resonance wavelength of 955~nm. We then propose a nonlinear photonics based quantum frequency conversion scheme to effectively scatter the qubit emission into the telecom band using an integrated photonic device, thus minimizing transmission loss. By integrating color centres in diamond with hybrid photonic cavities and quantum frequency conversion units, the platform could be scaled to longer entanglement distances and faster entanglement generation rates. Owing to the generality of the design process, the model could be readily applied to arbitrary wavelengths and material stacks. By separating device fabrication from the substrate, the hybrid photonics platform could be utilized to significantly expand the space of candidate qubits for quantum network experiments.

Adviser:  Nathalie de Leon