arXiv subjects

Taigao Ma

Publications and source records attributed to Taigao Ma.

4 recordsLinked to original sources

arXiv2024

Optical Multilayer Thin Film Structure Inverse Design: From Optimization to Deep Learning

Optical multilayer thin film structures have been widely used in numerous photonic domains and applications. The key component to enable these applications is the inverse design. Different from other photonic structures such as metasurface or waveguide, multilayer thin film is a one-dimensional structure, which deserves its own treatment for the design process. Optimization has always been the standard design algorithm for decades. Recent years have witnessed a rapid development of integrating different deep learning algorithms to tackle the inverse design problems. A natural question to ask is: how do these algorithms differ from each other? Why do we need to develop so many algorithms and what type of challenges do they solve? What is the state-of-the-art algorithm in this domain? Here, we review recent progress and provide a guide-tour through this research area, starting from traditional optimization to recent deep learning approaches. Challenges and future perspectives are also discussed.

physics.optics↗

arXiv2024

OptoGPT: A Foundation Model for Inverse Design in Optical Multilayer Thin Film Structures

Optical multilayer thin film structures have been widely used in numerous photonic applications. However, existing inverse design methods have many drawbacks because they either fail to quickly adapt to different design targets, or are difficult to suit for different types of structures, e.g., designing for different materials at each layer. These methods also cannot accommodate versatile design situations under different angles and polarizations. In addition, how to benefit practical fabrications and manufacturing has not been extensively considered yet. In this work, we introduce OptoGPT (Opto Generative Pretrained Transformer), a decoder-only transformer, to solve all these drawbacks and issues simultaneously.

physics.optics↗

arXiv2023

OL-Transformer: A Fast and Universal Surrogate Simulator for Optical Multilayer Thin Film Structures

Deep learning-based methods have recently been established as fast and accurate surrogate simulators for optical multilayer thin film structures. However, existing methods only work for limited types of structures with different material arrangements, preventing their applications towards diverse and universal structures. Here, we propose the Opto-Layer (OL) Transformer to act as a universal surrogate simulator for enormous types of structures. Combined with the technique of structure serialization, our model can predict accurate reflection and transmission spectra for up to $10^{25}$ different multilayer structures, while still achieving a six-fold degradation in simulation time compared to physical solvers. Further investigation reveals that the general learning ability comes from the fact that our model first learns the physical embeddings and then uses the self-attention mechanism to capture the hidden relationship of light-matter interaction between each layer.

cs.LG↗

arXiv2020

Simple Single-Section Diode Frequency Combs

Frequency combs, broadband light sources whose spectra consist of coherent, discrete modes, have become essential in many fields. Miniaturizing frequency combs would be a significant advance in these fields, enabling the deployment of frequency-comb based devices for diverse measurement and spectroscopy applications. We demonstrate diode-laser based frequency comb generators. These laser diodes are simple, electrically pumped, inexpensive and readily manufactured. Each chip contains several dozen diode-laser combs. We measure the time-domain output of a diode frequency comb to reveal the underlying frequency dynamics responsible for the comb spectrum, conduct dual comb spectroscopy of a molecular gas with two devices on the same chip, and demonstrate that these combs can be battery powered.

physics.optics↗