12 resultados para Combinatorial Grassmannian
em Cambridge University Engineering Department Publications Database
Er3+-doped glass-polymer composite thin films fabricated using combinatorial pulsed laser deposition
Resumo:
Siloxane Polymer exhibits low loss in the 800-1500 nm range which varies between 0.01 and 0.66 dB cm1. It is for such low loss the material is one of the most promising candidates in the application of engineering passive and active optical devices [1, 2]. However, current polymer fabrication techniques do not provide a methodology which allows high structurally solubility of Er3+ ions in siloxane matrix. To address this problem, Yang et al.[3] demonstrated a channel waveguide amplifier with Nd 3+-complex doped polymer, whilst Wong and co-workers[4] employed Yb3+ and Er3+ co-doped polymer hosts for increasing the gain. In some recent research we demonstrated pulsed laser deposition of Er-doped tellurite glass thin films on siloxane polymer coated silica substrates[5]. Here an alternative methodology for multilayer polymer-glass composite thin films using Er3+ - Yb3+ co-doped phosphate modified tellurite (PT) glass and siloxane polymer is proposed by adopting combinatorial pulsed laser deposition (PLD). © 2011 IEEE.
Resumo:
Establishing fabrication methods of carbon nanotubes (CNTs) is essential to realize many applications expected for CNTs. Catalytic growth of CNTs on substrates by chemical vapor deposition (CVD) is promising for direct fabrication of CNT devices, and catalyst nanoparticles play a crucial role in such growth. We have developed a simple method called "combinatorial masked deposition (CMD)", in which catalyst particles of a given series of sizes and compositions are formed on a single substrate by annealing gradient catalyst layers formed by sputtering through a mask. CMD enables preparation of hundreds of catalysts on a wafer, growth of single-walled CNTs (SWCNTs), and evaluation of SWCNT diameter distributions by automated Raman mapping in a single day. CMD helps determinations of the CVD and catalyst windows realizing millimeter-tall SWCNT forest growth in 10 min, and of growth curves for a series of catalysts in a single measurement when combined with realtime monitoring. A catalyst library prepared using CMD yields various CNTs, ranging from individuals, networks, spikes, and to forests of both SWCNTs and multi-walled CNTs, and thus can be used to efficiently evaluate self-organized CNT field emitters, for example. The CMD method is simple yet effective for research of CNT growth methods. © 2010 The Japan Society of Applied Physics.
Resumo:
We consider the problem of blind multiuser detection. We adopt a Bayesian approach where unknown parameters are considered random and integrated out. Computing the maximum a posteriori estimate of the input data sequence requires solving a combinatorial optimization problem. We propose here to apply the Cross-Entropy method recently introduced by Rubinstein. The performance of cross-entropy is compared to Markov chain Monte Carlo. For similar Bit Error Rate performance, we demonstrate that Cross-Entropy outperforms a generic Markov chain Monte Carlo method in terms of operation time.
Resumo:
Simulated annealing is a popular method for approaching the solution of a global optimization problem. Existing results on its performance apply to discrete combinatorial optimization where the optimization variables can assume only a finite set of possible values. We introduce a new general formulation of simulated annealing which allows one to guarantee finite-time performance in the optimization of functions of continuous variables. The results hold universally for any optimization problem on a bounded domain and establish a connection between simulated annealing and up-to-date theory of convergence of Markov chain Monte Carlo methods on continuous domains. This work is inspired by the concept of finite-time learning with known accuracy and confidence developed in statistical learning theory.
Resumo:
Simulated annealing is a popular method for approaching the solution of a global optimization problem. Existing results on its performance apply to discrete combinatorial optimization where the optimization variables can assume only a finite set of possible values. We introduce a new general formulation of simulated annealing which allows one to guarantee finite-time performance in the optimization of functions of continuous variables. The results hold universally for any optimization problem on a bounded domain and establish a connection between simulated annealing and up-to-date theory of convergence of Markov chain Monte Carlo methods on continuous domains. This work is inspired by the concept of finite-time learning with known accuracy and confidence developed in statistical learning theory.
Resumo:
Decision-making in the façade design process has a significant influence on several aspects of indoor environment, thereby making it a complex and multi-objective optimisation process. There are two principal barriers in the process of indentifying an optimal façade solution. Firstly, most existing indoor environmental evaluation methods do not account for all the indoor environmental quality (IEQ) aspects relevant to façade design. Secondly, the relationship between the physical properties of a particular façade design option and the resulting economic benefits accrued during its service-life is unknown. In this paper, we introduce the bases for establishing relationships between occupant productivity and the combinatorial effects of four key façade-related IEQ aspects, namely, thermal comfort, aural comfort, visual comfort and air quality, on occupant productivity. The proposed framework's potential is tested against seven existing experimental investigations and its applicability is illustrated by a simple façade design example. The proposed approach ultimately aims to provide a quantitative economic measure of alternative façade design options that would be applicable to early design stage. Aspects of the work that require further experimental validation are identified. © 2012 Elsevier Ltd.