(A)Sculptural study of a variable space

학위논문(석사)--서울대학교 대학원 :조소과 조소전공,2007.Maste

THz Photonic Device Design by Machine Learning

MasterTerahertz (THz) technology has attracted due to potentials on basic science and applied engineering. Also, Photonic Integrated Circuits (PICs) based on Silicon-on-insulator (SOI) platform have become a new paradigm for an on-chip subsystem due to a large bandwidth, resistance to interference and nonexistence of Joule effect. We designed the two basic THz PIC devices, Distributed Bragg Reflector (DBR) and 1×2 Optical Power Splitter (OPS), by machine learning. First, we used Additive Reinforcement Learning (ARL) algorithm, which is conceptually simple, fully parallelizable and not depend on initial solutions. Second, we used Artificial Neural Network (ANN) algorithm and inverse design method. ANN make that inverse design can calculate gradient analytically. Using these two methods, we can make the DBR, which is shorter than analytically designed DBR. Also, we can make low insertion loss and broadband OPS with ARL and increase accuracy of OPS prediction ANN by training data which has uniform distribution. Our results and approaches are expected to make a significant contribution to the developments of THz photonic devices