Webinaires

Surrogate models for nano-optics and photonics

Annonce

Résumé

Proxy models are becoming increasingly important for data-driven modelling in nano-optics and photonics. Dependent on the complexity of a system, simulations of nano-photonic devices can be very expensive. Data-based surrogate models are therefore very interesting for acceleration of slow simulations in time-critical applications. In particular, the rapid solution of ill-posed inverse problems can be tackled with the help of proxy models. Another strength of proxy models is the possibility of gradient calculations via automatic differentiation. In this context, I will discuss the potential of proxy models for optimization problems as well as the use of physics informed deep learning methods for improving nano-photonics proxy models.