Hamiltonian and Phase-Space Representation of Spatial Solitons

We use Hamiltonian ray tracing and phase-space representation to describe the propagation of a single spatial soliton and soliton collisions in a Kerr nonlinear medium. Hamiltonian ray tracing is applied using the iterative nonlinear beam propagation method, which allows taking both wave effects and Kerr nonlinearity into consideration. Energy evolution within a single spatial soliton and the exchange of energy when two solitons collide are interpreted intuitively by ray trajectories and geometrical shearing of the Wigner distribution functions.Comment: 12 pages, 5 figure

Design, fabrication and characterization of a distributed Bragg reflector for reducing the étendue of a wavelength converting system

In this work, the design, fabrication and characterization are reported for a distributed Bragg reflector (DBR) filter with a specific wavelength and angular dependency, which aims to improve the light collection from a wavelength-converter-based light source into a smaller angle than the full angle Lambertian emission. The desired design is obtained by optimizing the transmission characteristics of a multi-layer structure. Titania (TiO2) and silica (SiO2) are used as high and low refractive index materials, respectively. The deposition is made by electron beam evaporation without substrate heating, followed by a post-annealing procedure. The optical properties of the evaporated layers are analyzed by ellipsometer and spectrometer measurements. The angular and wavelength dependency of the fabricated DBR is in good agreement with simulations for the designed structure. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreemen

Multiple Transactions Model: A Panel Data Approach to Estimate Housing Market Indices

In this paper, a multiple transactions model with a panel data approach is used to estimate housing market indices. The multiple transactions model keeps the same features of the repeat transactions index model (i.e., tracking the price appreciation of same houses). However, the multiple transactions model overcomes the shortcomings of the repeat transactions model by avoiding the correlated error terms. The indicative empirical analysis on a small sample of actual house transaction data demonstrates that the proposed multiple transactions model is superior to the repeat transactions model in terms of index variance, robustness of estimate, index revision volatility, and out-of-sample prediction of individual house prices.

A Qualitative Study of Information challenges in the Cloud

This paper explores the modified information management and information governance challenges faced by organizations when shifting from traditional on-site model to the cloud. The specific cloud information management and governance challenges, often ignored by businesses due to their experience in traditional information governance and outsourcing, have the potential to threaten the sustainability of a business that is new to the cloud. As cloud solutions from powerful vendors are being thrust at unsuspecting customers, it is imperative that organizations understand information related changes required in the cloud to ensure regulatory compliance. A series of qualitative interviews involving expert practitioners has helped investigate the information challenges; and the barriers and drivers of cloud adoption in the current market with some unexpected observations

Dual Long Short-Term Memory Networks for Sub-Character Representation Learning

Characters have commonly been regarded as the minimal processing unit in Natural Language Processing (NLP). But many non-latin languages have hieroglyphic writing systems, involving a big alphabet with thousands or millions of characters. Each character is composed of even smaller parts, which are often ignored by the previous work. In this paper, we propose a novel architecture employing two stacked Long Short-Term Memory Networks (LSTMs) to learn sub-character level representation and capture deeper level of semantic meanings. To build a concrete study and substantiate the efficiency of our neural architecture, we take Chinese Word Segmentation as a research case example. Among those languages, Chinese is a typical case, for which every character contains several components called radicals. Our networks employ a shared radical level embedding to solve both Simplified and Traditional Chinese Word Segmentation, without extra Traditional to Simplified Chinese conversion, in such a highly end-to-end way the word segmentation can be significantly simplified compared to the previous work. Radical level embeddings can also capture deeper semantic meaning below character level and improve the system performance of learning. By tying radical and character embeddings together, the parameter count is reduced whereas semantic knowledge is shared and transferred between two levels, boosting the performance largely. On 3 out of 4 Bakeoff 2005 datasets, our method surpassed state-of-the-art results by up to 0.4%. Our results are reproducible, source codes and corpora are available on GitHub.Comment: Accepted & forthcoming at ITNG-201

Inefficient Star Formation In Extremely Metal Poor Galaxies

The first galaxies contain stars born out of gas with little or no metals. The lack of metals is expected to inhibit efficient gas cooling and star formation but this effect has yet to be observed in galaxies with oxygen abundance relative to hydrogen below a tenth of that of the Sun. Extremely metal poor nearby galaxies may be our best local laboratories for studying in detail the conditions that prevailed in low metallicity galaxies at early epochs. Carbon Monoxide (CO) emission is unreliable as tracers of gas at low metallicities, and while dust has been used to trace gas in low-metallicity galaxies, low-spatial resolution in the far-infrared has typically led to large uncertainties. Here we report spatially-resolved infrared observations of two galaxies with oxygen abundances below 10 per cent solar, and show that stars form very inefficiently in seven star-forming clumps of these galaxies. The star formation efficiencies are more than ten times lower than found in normal, metal rich galaxies today, suggesting that star formation may have been very inefficient in the early Universe.Comment: Author's version (10 pages, 4 figures). Published in Natur

The Weak Carbon Monoxide Emission In An Extremely Metal Poor Galaxy, Sextans A

Carbon monoxide (CO) is one of the primary coolants of gas and an easily accessible tracer of molecular gas in spiral galaxies but it is unclear if CO plays a similar role in metal poor dwarfs. We carried out a deep observation with IRAM 30 m to search for CO emission by targeting the brightest far-IR peak in a nearby extremely metal poor galaxy, Sextans A, with 7% Solar metallicity. A weak CO J=1-0 emission is seen, which is already faint enough to place a strong constraint on the conversion factor (a_CO) from the CO luminosity to the molecular gas mass that is derived from the spatially resolved dust mass map. The a_CO is at least seven hundred times the Milky Way value. This indicates that CO emission is exceedingly weak in extremely metal poor galaxies, challenging its role as a coolant in these galaxies.Comment: 4 pages, 1 table, 4 figures. ApJL in pres

Investigation of the Impact of User Gaming in the Next Generation National Airspace System

Over the past three decades, growth in the demand for air transportation has exceeded the growth in the national airspace system (NAS) capacity. Systems operating near capacity inevitably have delays and NAS d elays have increased in recent years. The desire to minimize delay costs has placed attention on the NAS air traffic management (ATM) syste m.One initiative that has helped to provide user representation in the ATM solution is the collaborative decision making (CDM) process. CDM addresses this issue by bringing users (referred to here as airline operation centers [AOCs]) and ATM providers together for information e xchange and cooperative planning. Such cooperative planning has been instituted, for instance, for the purpose of planning airport slot control strategies and rerouting strategies. While the CDM initiatives ha ve met with much success, they have also introduced the potential for AOCs to manipulate the system in unforeseen, unintended, and perhaps undesirable ways, from a system-wide, synoptic perspective. This type of manipulation is sometimes referred to as "gaming" the system. This study uses a high-fidelity simulation tool to investigate several models of user decision making behavior which could be considered to be gaming behavior and the emergent system dynamics and interactions between AOCs and traffic management