Mikkel Kirkegaard | Searcharxiv

arXiv2025

Optical microcavity with a pair of suspended resonant mirrors

We report on the realization of an optical microcavity consisting in the plane-plane arrangement of two suspended resonant mirrors possessing spectrally overlapping high-quality factor internal resonances. We first investigate its generic transmission spectra as the cavity length is varied on the basis of a simple linear Fabry-Perot model, compare them with those of broadband mirror cavities or Fano cavities possessing a single resoannt mirror, and then present an experimental realization using a pair of highly pretensioned, ultrathin silicon nitride films patterned with one-dimensional photonic crystal structures.

physics.optics↗

arXiv2025

EdgeMark: An Automation and Benchmarking System for Embedded Artificial Intelligence Tools

The integration of artificial intelligence (AI) into embedded devices, a paradigm known as embedded artificial intelligence (eAI) or tiny machine learning (TinyML), is transforming industries by enabling intelligent data processing at the edge. However, the many tools available in this domain leave researchers and developers wondering which one is best suited to their needs. This paper provides a review of existing eAI tools, highlighting their features, trade-offs, and limitations. Additionally, we introduce EdgeMark, an open-source automation system designed to streamline the workflow for deploying and benchmarking machine learning (ML) models on embedded platforms. EdgeMark simplifies model generation, optimization, conversion, and deployment while promoting modularity, reproducibility, and scalability. Experimental benchmarking results showcase the performance of widely used eAI tools, including TensorFlow Lite Micro (TFLM), Edge Impulse, Ekkono, and Renesas eAI Translator, across a wide range of models, revealing insights into their relative strengths and weaknesses. The findings provide guidance for researchers and developers in selecting the most suitable tools for specific application requirements, while EdgeMark lowers the barriers to adoption of eAI technologies.

cs.LG↗