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2. Inverse design of nano-photonic wavelength demultiplexer with a deep neural network approach

Author

Yuan, Mengwei, Yang, Gang, Song, Shijie, Zhou, Luping, Minasian, Robert, and Yi, Xiaoke

Subjects
Physics - Optics, Computer Science - Machine Learning
Abstract

In this paper, we propose a pre-trained-combined neural network (PTCN) as a comprehensive solution to the inverse design of an integrated photonic circuit. By utilizing both the initially pre-trained inverse and forward model with a joint training process, our PTCN model shows remarkable tolerance to the quantity and quality of the training data. As a proof of concept demonstration, the inverse design of a wavelength demultiplexer is used to verify the effectiveness of the PTCN model. The correlation coefficient of the prediction by the presented PTCN model remains greater than 0.974 even when the size of training data is decreased to 17%. The experimental results show a good agreement with predictions, and demonstrate a wavelength demultiplexer with an ultra-compact footprint, a high transmission efficiency with a transmission loss of -2dB, a low reflection of -10dB, and low crosstalk around -7dB simultaneously.

Published
2022
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7. Wide-Range Operation of Microwave Photonic Sensor Using Recurrent Neural Network

Author

Tian, Xiaoyi, Chen, Yeming, Yan, Yiming, Li, Liwei, Zhou, Luping, Nguyen, Linh, and Yi, Xiaoke

Abstract

In this paper, we present a microwave photonic (MWP) sensor whose operational range and sensing accuracy are enhanced through the utilization of a recurrent neural network (RNN). The MWP sensor utilizes an optical microresonator as the sensor probe and converts the optical resonance responses near the optical carrier frequency into variations in RF transmission with high interrogation resolution. To overcome bandwidth limitations and achieve wide-range operation, a tunable laser is employed to perform the high-resolution interrogation across multiple optical carrier frequencies during each measurement cycle. Subsequently, a RNN, leveraging long-range dependencies and shared parameters, is integrated to process the concatenated interrogation outputs after dimensionality reduction, compensating for output wavelength discrepancies of the tunable laser and enabling accurate wide-range sensing. The proposed approach is experimentally validated using a microring resonator to measure fructose solution concentrations while contending with laser frequency deviation and thermal interference. The operational range of the system is extended three times to 114 GHz, facilitating the measurement of solution concentrations ranging from 49.91% to 30.43% under a temperature variation of 0.61 °C and a laser frequency deviation of ±2 GHz. The established RNN model demonstrates a root-mean-square error of 0.11%, showcasing 1.60-fold, 2.77-fold, 1.10-fold, and 3.45-fold improvements in accuracy over models based on convolutional neural networks, multilayer perceptrons, sparse vision transformer, and linear fitting, respectively.

Published
2024
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12. Editorial

Author

Chen, Lawrence R., primary, Calabretta, Nicola, additional, Fok, Mable, additional, Li, Ming, additional, Torres-Company, Victor, additional, and Yi, Xiaoke, additional

Published
2023
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21. Inverse design of a nano-photonic wavelength demultiplexer with a deep neural network approach

Author

Yuan, Mengwei, Yang, Gang, Song, Shijie, Zhou, Luping, Minasian, Robert, and Yi, Xiaoke

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, FOS: Physical sciences, Atomic and Molecular Physics, and Optics, Physics - Optics, Optics (physics.optics), Machine Learning (cs.LG)
Abstract

In this paper, we propose a pre-trained-combined neural network (PTCN) as a comprehensive solution to the inverse design of an integrated photonic circuit. By utilizing both the initially pre-trained inverse and forward model with a joint training process, our PTCN model shows remarkable tolerance to the quantity and quality of the training data. As a proof of concept demonstration, the inverse design of a wavelength demultiplexer is used to verify the effectiveness of the PTCN model. The correlation coefficient of the prediction by the presented PTCN model remains greater than 0.974 even when the size of training data is decreased to 17%. The experimental results show a good agreement with predictions, and demonstrate a wavelength demultiplexer with an ultra-compact footprint of 2.6×2.6µm2, a high transmission efficiency with a transmission loss of -2dB, a low reflection of −10dB, and low crosstalk around −7dB simultaneously.

Published
2022

37. Marketing warfare: a case study from the 2008 Beijing Olympics

Author

Marber, Allen, Wellen, Paul M., Wurtz, Michael, and Yi, Xiaoke

Subjects
Coca-Cola Co. (Atlanta, Georgia) -- Marketing, Olympics -- 2008 AD, Soft drink industry -- Marketing, Marketing -- Case studies -- Analysis, Carbonated beverages -- Marketing -- 2008 AD, Company marketing practices, Business, international
Abstract

This study shows how contrasting marketing warfare strategies were utilized by two different companies for the same event, the 2008 Olympics in Beijing. Indeed, it appears that ancient warfare tactics can be used purposefully, and successfully, to either defend or increase market share. The Coca-Cola Company used a defensive marketing strategy while the Li Ning Sportswear Company used an ambush marketing strategy, with each company achieving it's marketing objectives. Keywords: Ambush marketing, defensive marketing, market share improvement, INTRODUCTION Much of this paper is based upon the ancient Eastern warfare strategies of Sun Tzu, a general from the Chinese province of Ch'i, who lived about 2400 years ago. [...]

Published
2012

38. High-Q suspended optical resonators in 3C-SiC obtained by thermal annealing

Author

Powell, Keith, Shams-Ansari, Amirhassan, Desai, Smit, Austin, Mitchell, Deng, Jiangdong, Sinclair, Neil, Lončar, Marko, Yi, Xiaoke, Powell, Keith, Shams-Ansari, Amirhassan, Desai, Smit, Austin, Mitchell, Deng, Jiangdong, Sinclair, Neil, Lončar, Marko, and Yi, Xiaoke

Abstract

We fabricate suspended single-mode optical waveguides and ring resonators in 3C-SiC that operate at telecommunication wavelength, leverage post-fabrication thermal annealing to minimize optical propagation losses and demonstrate Q of over 41,000.

Published
2020

39. Dispersion induced RF distortion of spectrum-sliced microwave-photonic filters

Author

Yi, Xiaoke and Minasian, Robert A.

Subjects
Photonics -- Research, Signal processing -- Analysis, Electric filters -- Design and construction, Digital signal processor, Business, Computers, Electronics, Electronics and electrical industries
Abstract

A general theoretical model for spectrum-sliced microwave-photonic filter design is presented. It is applicable to arbitrary variable time-delay characteristics, and to both double- and single-sideband modulation formats. Based on this model, dispersion-induced RF characteristics are investigated theoretically and experimentally. The results show that apart from the carrier suppression effect, the performance of spectrum-sliced microwave-photonic filters is limited by a dispersion-induced RF distortion that is related to the sliced spectrum character, and which is modulation format independent. The model provides data for designing the optimum grating optical slicing bandwidth and shape, and for determining the required spectral slice matching tolerance, to overcome nonideal RF characteristics and to enhance the filter frequency response. Index Terms--Fiber Bragg gratings (FBGs), microwave photonics, photonic signal processing, spectrum slicing.

Published
2006

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