Electron exchange coupling for single-donor solid-state spin qubits

Intervalley interference between degenerate conduction band minima has been shown to lead to oscillations in the exchange energy between neighboring phosphorus donor electron states in silicon [B. Koiller, X. Hu, and S. Das Sarma, Phys. Rev. Lett. 88, 027903 (2002); Phys. Rev. B 66, 115201 (2002)]. These same effects lead to an extreme sensitivity of the exchange energy on the relative orientation of the donor atoms, an issue of crucial importance in the construction of silicon-based spin quantum computers. In this article we calculate the donor electron exchange coupling as a function of donor position incorporating the full Bloch structure of the Kohn-Luttinger electron wave functions. It is found that due to the rapidly oscillating nature of the terms they produce, the periodic part of the Bloch functions can be safely ignored in the Heitler-London integrals as was done by Koiller, Hu, and Das Sarma, significantly reducing the complexity of calculations. We address issues of fabrication and calculate the expected exchange coupling between neighboring donors that have been implanted into the silicon substrate using an 15 keV ion beam in the so-called top down fabrication scheme for a Kane solid-state quantum computer. In addition, we calculate the exchange coupling as a function of the voltage bias on control gates used to manipulate the electron wave functions and implement quantum logic operations in the Kane proposal, and find that these gate biases can be used to both increase and decrease the magnitude of the exchange coupling between neighboring donor electrons. The zero-bias results reconfirm those previously obtained by Koiller, Hu, and Das Sarma.

Broadening conceptions of curriculum for young people: Reports from three student-teachers on exchange

Research reports prepared by three Australian preservice teachers--Paula Shaw, Chris Sharp and Scott McDonald--undertaking their teacher education practicum in Canada, form the basis of this paper. The reports provide critical insights into three aspects of education for young people in both Canada and Australia. They also provide critical insight into the ways in which a practicum research project, along with the opportunities afforded through an international experience, enabled the preservice teachers to broaden their understanding of the curriculum for young people, of issues relevant to the diverse needs of young people, and of themselves and their priorities as teachers. The preservice teachers investigated three topics: attempts to reduce homophobia in schools; the presence or absence of Aboriginal content in the school curricula in British Columbia and Queensland; and "schools-within-schools" as a means to meet the needs of diverse student populations. Linda Farr Darling from the University of British Columbia provides a response to the three reports.

An augmented Lanczos algorithm for the efficient computation of a dot-product of a function of a large sparse symmetric matrix

The Lanczos algorithm is appreciated in many situations due to its speed. and economy of storage. However, the advantage that the Lanczos basis vectors need not be kept is lost when the algorithm is used to compute the action of a matrix function on a vector. Either the basis vectors need to be kept, or the Lanczos process needs to be applied twice. In this study we describe an augmented Lanczos algorithm to compute a dot product relative to a function of a large sparse symmetric matrix, without keeping the basis vectors.

The tree cut and merge algorithm for estimation of network reliability

This article presents Monte Carlo techniques for estimating network reliability. For highly reliable networks, techniques based on graph evolution models provide very good performance. However, they are known to have significant simulation cost. An existing hybrid scheme (based on partitioning the time space) is available to speed up the simulations; however, there are difficulties with optimizing the important parameter associated with this scheme. To overcome these difficulties, a new hybrid scheme (based on partitioning the edge set) is proposed in this article. The proposed scheme shows orders of magnitude improvement of performance over the existing techniques in certain classes of network. It also provides reliability bounds with little overhead.

A genetic algorithm/method of moments approach to the optimization of an RF coil for MRI applications - Theoretical considerations - Abstract

A Combined Genetic Algorithm and Method of Moments design methods is presented for the design of unusual near-field antennas for use in Magnetic Resonance Imaging systems. The method is successfully applied to the design of an asymmetric coil structure for use at 190MHz and demonstrates excellent radiofrequency field homogeneity.

Conformational changes in SP-B as a function of surface pressure

X-ray reflectivity of bovine and sheep surfactant-associated protein B (SP-B) monolayers is used in conjunction with pressure-area isotherms and protein models to suggest that the protein undergoes changes in its tertiary structure at the air/water interface under the influence of surface pressure, indicating the likely importance of such changes to the phenomena of protein squeeze out as well as lipid exchange between the air-water interface and subphase structures. We describe an algorithm based on the well-established box- or layer-models that greatly assists the fitting of such unknown scattering-length density profiles, and which takes the available instrumental resolution into account. Scattering-length density profiles from neutron reflectivity of bovine SP-B monolayers on aqueous subphases are shown to be consistent with the exchange of a large number of labile protons as well as the inclusion of a significant amount of water, which is partly squeezed out of the protein monolayer at elevated surface pressures.

Automated traffic route identification through the shared nearest neighbour algorithm

Many organisations need to extract useful information from huge amounts of movement data. One example is found in maritime transportation, where the automated identification of a diverse range of traffic routes is a key management issue for improving the maintenance of ports and ocean routes, and accelerating ship traffic. This paper addresses, in a first stage, the research challenge of developing an approach for the automated identification of traffic routes based on clustering motion vectors rather than reconstructed trajectories. The immediate benefit of the proposed approach is to avoid the reconstruction of trajectories in terms of their geometric shape of the path, their position in space, their life span, and changes of speed, direction and other attributes over time. For clustering the moving objects, an adapted version of the Shared Nearest Neighbour algorithm is used. The motion vectors, with a position and a direction, are analysed in order to identify clusters of vectors that are moving towards the same direction. These clusters represent traffic routes and the preliminary results have shown to be promising for the automated identification of traffic routes with different shapes and densities, as well as for handling noise data.

Multi-centre validation of an automatic algorithm for fast 4D myocardial segmentation in cine CMR datasets

Quantitative analysis of cine cardiac magnetic resonance (CMR) images for the assessment of global left ventricular morphology and function remains a routine task in clinical cardiology practice. To date, this process requires user interaction and therefore prolongs the examination (i.e. cost) and introduces observer variability. In this study, we sought to validate the feasibility, accuracy, and time efficiency of a novel framework for automatic quantification of left ventricular global function in a clinical setting.

STOCK EXCHANGE LISTING INDUCES SOPHISTICATION OF CAPITAL BUDGETING

This article compares capital budgeting techniques employed in listed and unlisted companies in Brazil. We surveyed the Chief Financial Officers (CFOs) of 398 listed companies and 300 large unlisted companies, and based on 91 respondents, the results suggest that the CFOs of listed companies tend to use less simplistic methods more often, for example: NPV and CAPM, and that CFOs of unlisted companies are less likely to estimate the cost of equity, despite being large companies. These findings indicate that stock exchange listing may require greater sophistication of the capital budgeting process.

Lanczos algorithm on the grassmann manifold

5th. European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2008) 8th. World Congress on Computational Mechanics (WCCM8)

La social stock exchange au Portugal: un nouvel allié de l'économie sociale

Résumé Cet article vise à contribuer à la connaissance de la Bolsa de Valores Sociais (BVS) — Social Stock Exchange — récemment créé au Portugal, dont le but primatial était de permettre la prise de moyens de financement des entités de l'Économie Sociale engagées dans des projets d'éducation et d'entreprenariat. Il se penchera sur la qualification juridique des divers types d'entités cotées dans la BVS, sur le concept d'investisseur social et sur la protection dont il jouira, vis-à-vis des exigences de transparence et de gouvernance qui incombent à ces entités. Le thème proposé sera examiné en soulignant les virtualités et le potentiel de la BVS, faisant référence à l'un ou à l'autre sujet qui viennent à effet, avec un accent particulier sur l'avantage d'élaborer un code de gouvernance corporative pour les entités de l'Économie Sociale. Abstract This article aims to contribute to the knowledge of the Bolsa de Valores Sociais (BVS) — Social Stock Exchange — recently created in Portugal, whose primatial purpose was to allow the taking of means of financing the Social Economy entities, engaged in projects in education and entrepreneurship. It will reflect on the legal classification of the various types of entities rated in the BVS, on the concept of social investor and on the protection he will enjoy, leading to the consequent demands for transparency and governance that falls upon those entities. The proposed theme will be discussed highlighting the virtues and potential of BVS, playing in one or two topics that comes to purpose, with particular emphasis on the relevance of drawing up a code of corporate governance for entities of the Social Economy. Resumen Este artículo tiene como objetivo contribuir al conocimiento de la Bolsa de Valores Sociales (BVS), recientemente creada en Portugal, cuya finalidad principal es que las entidades de la economía social dedicadas a proyectos en las áreas de educación y de iniciativa empresarial puedan obtener medios financieros. Se abordará la calificación jurídica de los diversos tipos de entidades que cotizan en la BVS, así como el concepto de inversor social y la protección de que éste goza, con las consiguientes exigencias en materia de transparencia y de gobierno que recaen sobre esas entidades. Se analizará la temática propuesta destacando las virtudes y potencialidades de la BVS, sin omitir algún otro tópico adyacente que resulte relevante, en especial la conveniencia de que sea elaborado un código de gobernanza corporativa para las entidades de la economía social.

Augmented LDPC Graph for Distributed Video Coding with Multiple Side Information

The advances made in channel-capacity codes, such as turbo codes and low-density parity-check (LDPC) codes, have played a major role in the emerging distributed source coding paradigm. LDPC codes can be easily adapted to new source coding strategies due to their natural representation as bipartite graphs and the use of quasi-optimal decoding algorithms, such as belief propagation. This paper tackles a relevant scenario in distributedvideo coding: lossy source coding when multiple side information (SI) hypotheses are available at the decoder, each one correlated with the source according to different correlation noise channels. Thus, it is proposed to exploit multiple SI hypotheses through an efficient joint decoding technique withmultiple LDPC syndrome decoders that exchange information to obtain coding efficiency improvements. At the decoder side, the multiple SI hypotheses are created with motion compensated frame interpolation and fused together in a novel iterative LDPC based Slepian-Wolf decoding algorithm. With the creation of multiple SI hypotheses and the proposed decoding algorithm, bitrate savings up to 8.0% are obtained for similar decoded quality.

IOPT Petri Net State Space Generation Algorithm with Maximal-Step Execution Semantics

This paper presents an algorithm to efficiently generate the state-space of systems specified using the IOPT Petri-net modeling formalism. IOPT nets are a non-autonomous Petri-net class, based on Place-Transition nets with an extended set of features designed to allow the rapid prototyping and synthesis of system controllers through an existing hardware-software co-design framework. To obtain coherent and deterministic operation, IOPT nets use a maximal-step execution semantics where, in a single execution step, all enabled transitions will fire simultaneously. This fact increases the resulting state-space complexity and can cause an arc "explosion" effect. Real-world applications, with several million states, will reach a higher order of magnitude number of arcs, leading to the need for high performance state-space generator algorithms. The proposed algorithm applies a compilation approach to read a PNML file containing one IOPT model and automatically generate an optimized C program to calculate the corresponding state-space.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.