Parameter reconstructions are indispensable in metrology. Here, the objective is to explain K experimental measurements by fitting to them a parameterized model of the measurement process. The model parameters are regularly determined by least-square methods, that is, by minimizing the sum of the squared residuals between the K model predictions and the K experimental observations, 𝝌 2 . The model functions often involve computationally demanding numerical simulations. Bayesian optimization methods are specifically suited for minimizing expensive model functions. However, in contrast to least-square methods such as the Levenberg-Marquardt algorithm, they only take the value of 𝝌 2 into account, and neglect the K individual model outputs. A Bayesian target-vector optimization scheme with improved performance over previous developments, that considers all K contributions of the model function and that is specifically suited for parameter reconstruction problems which are often based on hundreds of observations is presented. Its performance is compared to established methods for an optical metrology reconstruction problem and two synthetic least-squares problems. The proposed method outperforms established optimization methods. It also enables to determine accurate uncertainty estimates with very few observations of the actual model function by using Markov chain Monte Carlo sampling on a trained surrogate model.

We present a numerical investigation of directly fiber-coupled hybrid circular Bragg gratings (CBGs) featuring electrical control for operation in the application relevant wavelength regimes around 930 nm as well as the telecom O- and C-band. We use a surrogate model combined with a Bayesian optimization approach to perform numerical optimization of the device performance which takes into account robustness with respect to fabrication tolerances. The proposed high-performance designs combine hybrid CBGs with a dielectric planarization and a transparent contact material, enabling > 86% direct fiber coupling efficiency (> 93% efficiency into NA 0.8) while exhibiting Purcell factors > 20. Especially the proposed designs for the telecom range prove robust and can sustain expected fiber efficiencies of more than (82.2±4.1)−5.5+2.2% and expected average Purcell factors of up to (23.2±2.3)−3.0+3.2 assuming conservative fabrication accuracies. The wavelength of maximum Purcell enhancement proves to be the most affected performance parameter by the deviations. Finally, we show that electrical field strengths suitable for Stark-tuning of an embedded quantum dot can be reached in the identified designs. Our work provides blueprints for high-performance quantum light sources based on fiber-pigtailed and electrically-controlled quantum dot CBG devices for quantum information applications.

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Interfacing spin-active solid-state quantum emitters or memories with photons remains a challenging task due to photon losses. We propose and demonstrate the ‘Sawfish’ photonic crystal cavity to eliminate photon losses at spin-photon interfaces.