Fabrication and characterization of integrable GaAs-based high-contrast grating reflector and Fabry-Pérot filter array with GaInP sacrificial layer

Integrable GaAs-based high-contrast gratings (HCGs) are fabricated and characterized, targeting applications in high-speed vertical-cavity surface-emitting lasers (VCSELs). A Ga 0.51 In 0.49 P sacrificial layer beneath the GaAs layer is employed to create a low index surrounding HCG strips by selective etching. Experimental results show that the finite-size HCG has a reflectivity of 93% from 1270 to 1330 nm for the transverse magnetic polarization, which is consistent with the calculated results. An HCG-based Fabry-Perot filter array formed by the different HCGs, air gap, and GaAs substrate is demonstrated. The measured resonance wavelengths of the filter arrays are consistent with the theoretical results, which implies that the resonance wavelength of such filters can be tuned by parameters of the HCG itself

GaAs-based subwavelength grating on an AlOx layer for a vertical-cavity surface-emitting laser

© 2020 Optical Society of America. Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserved.A GaAs-based subwavelength grating on a thick (∼3/4*λ at 1300 nm) AlOx layer is designed, fabricated, and characterized. The AlOx layer as a low-index medium is oxidized from a 640-nm Al0.9Ga0.1As layer. The layer contraction of the Al0.9Ga0.1As layer after wet oxidation to AlOx is 4.9%. We fabricated GaAs-based subwavelength gratings on the AlOx layer showing a high reflectivity of 90% in the 1300-nm wavelength range, consistent with the simulation results. Such GaAs-based subwavelength gratings can be used as high-contrast grating mirrors for narrow-linewidth VCSELs, improving the mechanical stability and simplifying the device fabrication

Concept drift adaptation for learning with streaming data

University of Technology Sydney. Faculty of Engineering and Information Technology.The term concept drift refers to the change of distribution underlying the data. It is an inherent property of evolving data streams. Concept drift detection and adaptation has been considered an important component of learning under evolving data streams and has attracted increasing attention in recent years. According to the existing literature, the most commonly used definition of concept drift is constrained to discrete feature space. The categorization of concept drift is complicated and has limited contribution to solving concept drift problems. As a result, there is a gap to uniformly describe concept drift for both discrete and continuous feature space, and to be a guideline to addressing the root causes of concept drift. The objective of existing concept drift handling methods mainly focuses on identifying when is the best time to intercept training samples from data streams to construct the cleanest concept. Most only consider concept drift as a time-related distribution change, and are disinterested in the spatial information related to the drift. As a result, if a drift detection or adaptation method does not have spatial information regarding the drift regions, it can only update learning models or their training dataset in terms of time-related information, which may result in an incomplete model update or unnecessary training data reduction. In particular, if a false alarm is raised, updating the entire training set is costly and may degrade the overall performance of the learners. For the same reason, any regional drifts, before becoming globally significant, will not trigger the adaptation process and will result in a delay in the drift detection process. These disadvantages limit the accuracy of machine learning under evolving data streams. To better address concept drift problems, this thesis proposes a novel Regional Drift Adaptation (RDA) framework that introduces spatial-related information into concept drift detection and adaptation. In other words, RDA-based algorithms consider both time-related and spatial information for concept drift handling (concept drift handling includes both drift detection and adaptation). In this thesis, a formal definition of regional drift is given which has theoretically proved that any types of concept drift can be represented as a set of regional drifts. According to these findings, a series of regional drift-oriented drift adaptation algorithms have been developed, including the Nearest Neighbor-based Density Variation Identification (NN-DVI) algorithm which focuses on improving concept drift detection accuracy, the Local Drift Degree-based Density Synchronization Drift Adaptation (LDD-DSDA) algorithm which focuses on boosting the performance of learners with concept drift adaptation, and the online Regional Drift Adaptation (online-RDA) algorithm which incrementally solves concept drift problems quickly and with limited storage requirements. Finally, an extensive evaluation on various benchmarks, consisting of both synthetic and real-world data streams, was conducted. The competitive results underline the effectiveness of RDA in relation to concept drift handling. To conclude, this thesis targets an urgent issue in modern machine learning research. The approach taken in the thesis of building regional concept drift detection and adaptation system is novel. There has previously been no systematic study on handling concept drift from spatial prespective. The findings of this thesis contribute to both scientific research and practical applications

VCSEL with finite-size high-contrast metastructure

© Copyright 2018 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.High-contrast metastructures like one-dimensional high-contrast gratings (HCGs) are promising to improve the performance of conventional VCSELs, also presenting a basis for new applications. Different from the previous studies where HCGs are always modelled being of infinite size, we studied here the finite-size HCGs, which match the real situation. We observe finite-size HCGs behaving very differently from infinite-size HCGs. The reflectivity of a finitesize HCG strongly depends on the HCG size and the source size. At the same time, the simulation results show, that finite-size HCGs can shape the output beam, and a Gaussian-like reflected wave is typically achieved. Most important the normally incident light is partly redirected to the in-plane direction, showing unidirectional transmission. Monolithically integrated HCG-based optical sensors can be based on this novel effect. An integrable HCG reflector was fabricated with GaInP as the sacrificial layer targeting the application of HCG-VCSEL at 980 nm range. The measured reflectivity agrees well with the calculated reflectivity