We propose the combination of forward shape derivatives and the use of an iterative inversion scheme for Bayesian optimization to find optimal designs of nanophotonic devices. This approach widens the range of applicability of Bayesian optmization to situations where a larger number of iterations is required and where derivative information is available. This was previously impractical because the computational efforts required to identify the next evaluation point in the parameter space became much larger than the actual evaluation of the objective function. We demonstrate an implementation of the method by optimizing a waveguide edge coupler.

翻译：我们建议将前形衍生物与代位转换方案相结合,供贝叶斯优化利用,以找到纳米光学装置的最佳设计。这种方法扩大了贝叶斯选择方案的适用范围,使之适用于需要更多迭代和有衍生信息的情况。这以前是不切实际的,因为确定参数空间下一个评价点所需的计算努力比对目标功能的实际评价要大得多。我们通过优化波导边对齐器,展示了该方法的实施。