Presentation Information

[10p-N221-4]Suppression of Q-factor variation in an asymmetric heterostructure nanocavity
with the designed Q-factor exceeding 300 million

〇(M1)Yuta Kanemaru1, Takashi Asano2, Rikuto Ichinose1, Yasushi Takahashi3 (1.Osaka Met. Univ., 2.Kyoto Univ., 3.Okayama Univ.)

Keywords:

silicon photonics,machine learning,high-Q nanocavity

We have been working on achieving high Q-factors in photonic crystal nanocavities and have experimentally obtained a Q-factor of 11 million. For practical applications, not only achieving a high Q-factor but also suppressing the variation in Q-values is important. The main cause of this variation is fluctuations in the positions and radii of air holes due to fabrication errors. To address this issue, we focus on asymmetric cavities, which are less affected by these air hole fluctuations. In this work, we designed an asymmetric heterostructure nanocavity with a design Q-factor exceeding 300 million using machine learning and evaluated its effectiveness in reducing Q-value variations.