Deep-etched high-density fused-silica transmission gratings with high efficiency at a wavelength of 1550 nm

We describe the design, fabrication, and excellent performance of an optimized deep-etched high-density fused-silica transmission grating for use in dense wavelength division multiplexing (DWDM) systems. The fabricated optimized transmission grating exhibits an efficiency of 87.1% at a wavelength of 1550 nm. Inductively coupled plasma-etching technology was used to fabricate the grating. The deep-etched high-density fused-silica transmission grating is suitable for use in a DWDM system because of its high efficiency, low polarization-dependent loss, parallel demultiplexing, and stable optical performance. The fabricated deep-etched high-density fused-silica transmission gratings should play an important role in DWDM systems. (c) 2006 Optical Society of America.

Deep near-infrared spectroscopy of high-redshift galaxies: the physical growth of passive systems

The assembly history of massive galaxies is one of the most important aspects of galaxy formation and evolution. Although we have a broad idea of what physical processes govern the early phases of galaxy evolution, there are still many open questions. In this thesis I demonstrate the crucial role that spectroscopy can play in a physical understanding of galaxy evolution. I present deep near-infrared spectroscopy for a sample of high-redshift galaxies, from which I derive important physical properties and their evolution with cosmic time. I take advantage of the recent arrival of efficient near-infrared detectors to target the rest-frame optical spectra of z > 1 galaxies, from which many physical quantities can be derived. After illustrating the applications of near-infrared deep spectroscopy with a study of star-forming galaxies, I focus on the evolution of massive quiescent systems.

Most of this thesis is based on two samples collected at the W. M. Keck Observatory that represent a significant step forward in the spectroscopic study of z > 1 quiescent galaxies. All previous spectroscopic samples at this redshift were either limited to a few objects, or much shallower in terms of depth. Our first sample is composed of 56 quiescent galaxies at 1 < z < 1.6 collected using the upgraded red arm of the Low Resolution Imaging Spectrometer (LRIS). The second consists of 24 deep spectra of 1.5 < z < 2.5 quiescent objects observed with the Multi-Object Spectrometer For Infra-Red Exploration (MOSFIRE). Together, these spectra span the critical epoch 1 < z < 2.5, where most of the red sequence is formed, and where the sizes of quiescent systems are observed to increase significantly.

We measure stellar velocity dispersions and dynamical masses for the largest number of z > 1 quiescent galaxies to date. By assuming that the velocity dispersion of a massive galaxy does not change throughout its lifetime, as suggested by theoretical studies, we match galaxies in the local universe with their high-redshift progenitors. This allows us to derive the physical growth in mass and size experienced by individual systems, which represents a substantial advance over photometric inferences based on the overall galaxy population. We find a significant physical growth among quiescent galaxies over 0 < z < 2.5 and, by comparing the slope of growth in the mass-size plane dlogR_e/dlogM_∗ with the results of numerical simulations, we can constrain the physical process responsible for the evolution. Our results show that the slope of growth becomes steeper at higher redshifts, yet is broadly consistent with minor mergers being the main process by which individual objects evolve in mass and size.

By fitting stellar population models to the observed spectroscopy and photometry we derive reliable ages and other stellar population properties. We show that the addition of the spectroscopic data helps break the degeneracy between age and dust extinction, and yields significantly more robust results compared to fitting models to the photometry alone. We detect a clear relation between size and age, where larger galaxies are younger. Therefore, over time the average size of the quiescent population will increase because of the contribution of large galaxies recently arrived to the red sequence. This effect, called progenitor bias, is different from the physical size growth discussed above, but represents another contribution to the observed difference between the typical sizes of low- and high-redshift quiescent galaxies. By reconstructing the evolution of the red sequence starting at z ∼ 1.25 and using our stellar population histories to infer the past behavior to z ∼ 2, we demonstrate that progenitor bias accounts for only half of the observed growth of the population. The remaining size evolution must be due to physical growth of individual systems, in agreement with our dynamical study.

Finally, we use the stellar population properties to explore the earliest periods which led to the formation of massive quiescent galaxies. We find tentative evidence for two channels of star formation quenching, which suggests the existence of two independent physical mechanisms. We also detect a mass downsizing, where more massive galaxies form at higher redshift, and then evolve passively. By analyzing in depth the star formation history of the brightest object at z > 2 in our sample, we are able to put constraints on the quenching timescale and on the properties of its progenitor.

A consistent picture emerges from our analyses: massive galaxies form at very early epochs, are quenched on short timescales, and then evolve passively. The evolution is passive in the sense that no new stars are formed, but significant mass and size growth is achieved by accreting smaller, gas-poor systems. At the same time the population of quiescent galaxies grows in number due to the quenching of larger star-forming galaxies. This picture is in agreement with other observational studies, such as measurements of the merger rate and analyses of galaxy evolution at fixed number density.

Polarizing beam splitter of a deep-etched fused-silica grating

We described a highly efficient polarizing beam splitter (PBS) of a deep-etched binary-phase fused-silica grating, where TE- and TM-polarized waves are mainly diffracted in the -1st and 0th orders, respectively. Tb achieve a high extinction ratio and diffraction efficiency, the grating depth and period are optimized by using rigorous coupled-wave analysis, which can be well explained based on the modal method with effective indices of the modes for TE/TM polarization. Holographic recording technology and inductively coupled plasma etching are employed to fabricate the fused-silica PBS grating. Experimental results of diffraction efficiencies approaching 80% for a TE-polarized wave in the -1st order and more than 85% for a TM-polarized wave in the 0th order were obtained at a wavelength of 1550 nm. Because of its compact structure and simple fabrication process, which is suitable for mass reproduction, a deep-etched fused-silica grating as a PBS should be a useful device for practical applications. (C) 2007 Optical Society of America

The choice of a suitable sampler for benthic macroinvertebrates in deep rivers

Both chemical and biological methods are used to assess the water quality of rivers. Many standard physical and chemical methods are now established, but biological procedures of comparable accuracy and versatility are still lacking. This is unfortunate because the biological assessment of water quality has several advantages over physical and chemical analyses. Several groups of organisms have been used to assess water quality in rivers and these include Bacteria, Protozoa, Algae, macrophytes, macroinvertebrates and fish. Hellawell (1978) provides an excellent review of the advantages and disadvantages of these groups, and concludes that macroinvertebrates are the most useful for monitoring water quality. Although macroinvertebrates are relatively easy to sample in shallow water (depth < 1m), quantitative sampling poses more problems than qualitative sampling because a large number of replicate sampling units are usually required for accurate estimates of numbers or biomass per unit area. Both qualitative and quantitative sampling are difficult in deep water (depth > 1m). The present paper first considers different types of samplers with emphasis on immediate samplers, and then discusses some problems in choosing a suitable sampler for benthic macroinvertebrates in deep rivers.

Advanced Monte Carlo Simulation and Machine Learning for Frequency Domain Optical Coherence Tomography

Optical Coherence Tomography(OCT) is a popular, rapidly growing imaging technique with an increasing number of bio-medical applications due to its noninvasive nature. However, there are three major challenges in understanding and improving an OCT system: (1) Obtaining an OCT image is not easy. It either takes a real medical experiment or requires days of computer simulation. Without much data, it is difficult to study the physical processes underlying OCT imaging of different objects simply because there aren't many imaged objects. (2) Interpretation of an OCT image is also hard. This challenge is more profound than it appears. For instance, it would require a trained expert to tell from an OCT image of human skin whether there is a lesion or not. This is expensive in its own right, but even the expert cannot be sure about the exact size of the lesion or the width of the various skin layers. The take-away message is that analyzing an OCT image even from a high level would usually require a trained expert, and pixel-level interpretation is simply unrealistic. The reason is simple: we have OCT images but not their underlying ground-truth structure, so there is nothing to learn from. (3) The imaging depth of OCT is very limited (millimeter or sub-millimeter on human tissues). While OCT utilizes infrared light for illumination to stay noninvasive, the downside of this is that photons at such long wavelengths can only penetrate a limited depth into the tissue before getting back-scattered. To image a particular region of a tissue, photons first need to reach that region. As a result, OCT signals from deeper regions of the tissue are both weak (since few photons reached there) and distorted (due to multiple scatterings of the contributing photons). This fact alone makes OCT images very hard to interpret.

This thesis addresses the above challenges by successfully developing an advanced Monte Carlo simulation platform which is 10000 times faster than the state-of-the-art simulator in the literature, bringing down the simulation time from 360 hours to a single minute. This powerful simulation tool not only enables us to efficiently generate as many OCT images of objects with arbitrary structure and shape as we want on a common desktop computer, but it also provides us the underlying ground-truth of the simulated images at the same time because we dictate them at the beginning of the simulation. This is one of the key contributions of this thesis. What allows us to build such a powerful simulation tool includes a thorough understanding of the signal formation process, clever implementation of the importance sampling/photon splitting procedure, efficient use of a voxel-based mesh system in determining photon-mesh interception, and a parallel computation of different A-scans that consist a full OCT image, among other programming and mathematical tricks, which will be explained in detail later in the thesis.

Next we aim at the inverse problem: given an OCT image, predict/reconstruct its ground-truth structure on a pixel level. By solving this problem we would be able to interpret an OCT image completely and precisely without the help from a trained expert. It turns out that we can do much better. For simple structures we are able to reconstruct the ground-truth of an OCT image more than 98% correctly, and for more complicated structures (e.g., a multi-layered brain structure) we are looking at 93%. We achieved this through extensive uses of Machine Learning. The success of the Monte Carlo simulation already puts us in a great position by providing us with a great deal of data (effectively unlimited), in the form of (image, truth) pairs. Through a transformation of the high-dimensional response variable, we convert the learning task into a multi-output multi-class classification problem and a multi-output regression problem. We then build a hierarchy architecture of machine learning models (committee of experts) and train different parts of the architecture with specifically designed data sets. In prediction, an unseen OCT image first goes through a classification model to determine its structure (e.g., the number and the types of layers present in the image); then the image is handed to a regression model that is trained specifically for that particular structure to predict the length of the different layers and by doing so reconstruct the ground-truth of the image. We also demonstrate that ideas from Deep Learning can be useful to further improve the performance.

It is worth pointing out that solving the inverse problem automatically improves the imaging depth, since previously the lower half of an OCT image (i.e., greater depth) can be hardly seen but now becomes fully resolved. Interestingly, although OCT signals consisting the lower half of the image are weak, messy, and uninterpretable to human eyes, they still carry enough information which when fed into a well-trained machine learning model spits out precisely the true structure of the object being imaged. This is just another case where Artificial Intelligence (AI) outperforms human. To the best knowledge of the author, this thesis is not only a success but also the first attempt to reconstruct an OCT image at a pixel level. To even give a try on this kind of task, it would require fully annotated OCT images and a lot of them (hundreds or even thousands). This is clearly impossible without a powerful simulation tool like the one developed in this thesis.

Miniature pulse compressor of deep-etched gratings

We propose a miniature pulse compressor that can be used to compensate the group velocity dispersion that is produced by a commercial femtosecond laser cavity. The compressor is composed of two identical highly efficient deep-etched transmissive gratings. Compared with prism pairs, highly efficient deep-etched transmissive grating pairs are lightweight and small. With an optimized groove depth and a duty cycle, 98% diffraction efficiency of the -1 transmissive order can be achieved at a wavelength of 800 nm under Littrow conditions. The deep-etched gratings are fabricated in fused silica by inductively coupled plasma etching. With a pair of the fabricated gratings, the input positively chirped 73.9 fs pulses are neatly compressed into the nearly Fourier transform-limited 43.2 fs pulses. The miniature deep-etched grating-based pulse compressor should be of interest for practical applications. (c) 2008 Optical Society of America

Modal analysis of deep-etched low-contrast two-port beam splitter grating

Modal analysis of a deep-etched low-contrast two-port beam splitter grating under Littrow Mounting is presented. The guideline for the design of a subwavelength transmission fused-silica phase grating as high-efficiency grating, polarizing beam splitter (PBS), and two-port beam splitter, is summarized. As an example, a polarization-independent two-port beam splitter grating is designed at wavelength of 1064 nm. We firstly analyzed the physical essence of the grating by the simplified modal method. The guideline for the grating design and the approximate grating parameters are obtained. Then using the rigorous coupled-wave analysis (RCWA) with parameters varying around the approximate ones, Optimum grating parameters can be determined. With the design guideline, the time for the rigorous calculation of the grating profile parameters can be reduced significantly. (C) 2008 Elsevier B.V. All rights reserved

Polarizing beam splitter of deep-etched triangular-groove fused-silica gratings

We investigated the use of a deep-etched fused-silica grating with triangular-shaped grooves as a highly efficient polarizing beam splitter (PBS). A triangular-groove PBS grating is designed at a wavelength of 1550 nm to be used in optical communication. When it is illuminated in Littrow mounting, the transmitted TE- and TM-polarized waves are mainly diffracted in the minus-first and zeroth orders, respectively. The design condition is based on the average differences of the grating mode indices, which is verified by using rigorous coupled-wave analysis. The designed PBS grating is highly efficient over the C+L band range for both TE and TM polarizations (> 97.68 %). It is shown that such a triangular-groove PBS grating can exhibit a higher diffraction efficiency, a larger extinction ratio, and less reflection loss than the binary-phase fused-silica PBS grating. (C) 2008 Optical Society of America.

Delivery of Targeted Nanoparticles Across the Blood-Brain Barrier Using a Detachable Targeting Ligand

Chronic diseases of the central nervous system are poorly treated due to the inability of most therapeutics to cross the blood-brain barrier. The blood-brain barrier is an anatomical and physiological barrier that severely restricts solute influx, including most drugs, from the blood to the brain. One promising method to overcome this obstacle is to use endogenous solute influx systems at the blood-brain barrier to transport drugs. Therapeutics designed to enter the brain through transcytosis by binding the transferrin receptor, however, are restricted within endothelial cells. The focus of this work was to develop a method to increase uptake of transferrin-containing nanoparticles into the brain by overcoming these restrictive processes.

To accomplish this goal, nanoparticles were prepared with surface transferrin molecules bound through various liable chemical bonds. These nanoparticles were designed to shed the targeting molecule during transcytosis to allow increased accumulation of nanoparticles within the brain.

Transferrin was added to the surface of nanoparticles through either redox or pH sensitive chemistry. First, nanoparticles with transferrin bound through disulfide bonds were prepared. These nanoparticles showed decreased avidity for the transferrin receptor after exposure to reducing agents and increased ability to enter the brain in vivo compared to those lacking the disulfide link.

Next, transferrin was attached through a chemical bond that cleaves at mildly acidic pH. Nanoparticles containing a cleavable link between transferrin and gold nanoparticle cores were found to both cross an in vitro model of the blood-brain barrier and accumulate within the brain in significantly higher numbers than similar nanoparticles lacking the cleavable bond. Also, this increased accumulation was not seen when using this same strategy with an antibody to transferrin receptor, indicating that behavior of nanoparticles at the blood-brain barrier varies depending on what type of targeting ligand is used.

Finally, polymeric nanoparticles loaded with dopamine and utilizing a superior acid-cleavable targeting chemistry were investigated as a potential treatment for Parkinson’s disease. These nanoparticles were capable of increasing dopamine quantities in the brains of healthy mice, highlighting the therapeutic potential of this design. Overall, this work describes a novel method to increase targeted nanoparticle accumulation in the brain.

Deep silicon grating as high-extinction-ratio polarizing beam splitter

A deep binary silicon grating as high-extinction-ratio reflective polarizing beam splitter (PBS) at the wavelength of 1550 nm is presented. The design is based on the phenomenon of total internal reflection (TIR) by using the rigorous coupled wave analysis (RCWA). The extinction ratio of the rectangular PBS grating can reach 2.5×105 with the optimum grating period of 397 nm and groove depth of 1.092 μm. The effciencies of TM-polarized wave in the 0th order and TE-polarized wave in the −1st order can both reach unity at the Littrow angle. Holographic recording technology and inductively coupled plasma (ICP) etching could be used to fabricate the silicon PBS grating.

Deep learning review and its applications

Deep neural networks have recently gained popularity for improv- ing state-of-the-art machine learning algorithms in diverse areas such as speech recognition, computer vision and bioinformatics. Convolutional networks especially have shown prowess in visual recognition tasks such as object recognition and detection in which this work is focused on. Mod- ern award-winning architectures have systematically surpassed previous attempts at tackling computer vision problems and keep winning most current competitions. After a brief study of deep learning architectures and readily available frameworks and libraries, the LeNet handwriting digit recognition network study case is developed, and lastly a deep learn- ing network for playing simple videogames is reviewed.

Never-resting microglia: physiological roles in the healthy brain and pathological implications

Microglia are largely known as the major orchestrators of the brain inflammatory response. As such, they have been traditionally studied in various contexts of disease, where their activation has been assumed to induce a wide range of detrimental effects. In the last few years, a series of discoveries have challenged the current view of microglia, showing their active and positive contribution to normal brain function. This Research Topic will review the novel physiological roles of microglia in the developing, mature and aging brain, under non-pathological conditions. In particular, this Research Topic will discuss the cellular and molecular mechanisms by which microglia contribute to the formation, pruning and plasticity of synapses; the maintenance of the blood brain barrier; the regulation of adult neurogenesis and hippocampal learning; and neuronal survival, among other important roles. Because these novel findings defy our understanding of microglial function in health as much as in disease, this Research Topic will also summarize the current view of microglial nomenclature, phenotypes, origin and differentiation, sex differences, and contribution to various brain pathologies. Additionally, novel imaging approaches and molecular tools to study microglia in their non-activated state will be discussed. In conclusion, this Research Topic seeks to emphasize how the current research in neuroscience is challenged by never-resting microglia.