Diffusive shock acceleration at laser-driven shocks: studying cosmic-ray accelerators in the laboratory

The non-thermal particle spectra responsible for the emission from many astrophysical systems are thought to originate from shocks via a first order Fermi process otherwise known as diffusive shock acceleration. The same mechanism is also widely believed to be responsible for the production of high energy cosmic rays. With the growing interest in collisionless shock physics in laser produced plasmas, the possibility of reproducing and detecting shock acceleration in controlled laboratory experiments should be considered. The various experimental constraints that must be satisfied are reviewed. It is demonstrated that several currently operating laser facilities may fulfil the necessary criteria to confirm the occurrence of diffusive shock acceleration of electrons at laser produced shocks. Successful reproduction of Fermi acceleration in the laboratory could open a range of possibilities, providing insight into the complex plasma processes that occur near astrophysical sources of cosmic rays.

Global quantum correlations in finite-size spin chains

We perform an extensive study of the properties of global quantum correlations in finite-size one-dimensional quantum spin models at finite temperature. By adopting a recently proposed measure for global quantum correlations (Rulli and Sarandy 2011 Phys. Rev. A 84 042109), called global discord, we show that critical points can be neatly detected even for many-body systems that are not in their ground state. We consider the transverse Ising model, the cluster-Ising model where three-body couplings compete with an Ising-like interaction, and the nearest-neighbor XX Hamiltonian in transverse magnetic field. These models embody our canonical examples showing the sensitivity of global quantum discord close to criticality. For the Ising model, we find a universal scaling of global discord with the critical exponents pertaining to the Ising universality class.

Scaling of the entanglement spectrum near quantum phase transitions

The entanglement spectrum describing quantum correlations in many-body systems has been recently recognized as a key tool to characterize different quantum phases, including topological ones. Here we derive its analytically scaling properties in the vicinity of some integrable quantum phase transitions and extend our studies also to nonintegrable quantum phase transitions in one-dimensional spin models numerically. Our analysis shows that, in all studied cases, the scaling of the difference between the two largest nondegenerate Schmidt eigenvalues yields with good accuracy critical points and mass scaling exponents.

Area laws and entanglement distillability of thermal states

We study the entanglement distillability properties of thermal states of many-body systems Following the ideas presented in [6, A Ferraro et al., Phys. Rev Lett 100, 080502 (2008)], we first discuss the appearance of bound entanglement in those systems satisfying an entanglement area law Then, we extend these results to other topologies, not necessarily satisfying an entanglement area law We also study whether bound entanglement survives in the macroscopic limit of an infinite number of particles.

Reconstructing the quantum state of oscillator networks with a single qubit

We introduce a scheme to reconstruct arbitrary states of networks composed of quantum oscillators-e. g., the motionalstate of trapped ions or the radiation state of coupled cavities. The scheme involves minimal resources and minimal access, in the sense that it (i) requires only the interaction between a one-qubit probe and a single node of the network; (ii) provides the Weyl characteristic function of the network directly from the data, avoiding any tomographic transformation; (iii) involves the tuning of only one coupling parameter. In addition, we show that a number of quantum properties can be extracted without full reconstruction of the state. The scheme can be used for probing quantum simulations of anharmonic many-body systems and quantum computations with continuous variables. Experimental implementation with trapped ions is also discussed and shown to be within reach of current technology.

A Characteristic Function Approach to Inconsistency Measures for Knowledge Bases.

Knowledge is an important component in many intelligent systems.
Since items of knowledge in a knowledge base can be conflicting, especially if
there are multiple sources contributing to the knowledge in this base, significant
research efforts have been made on developing inconsistency measures for
knowledge bases and on developing merging approaches. Most of these efforts
start with flat knowledge bases. However, in many real-world applications, items
of knowledge are not perceived with equal importance, rather, weights (which
can be used to indicate the importance or priority) are associated with items of
knowledge. Therefore, measuring the inconsistency of a knowledge base with
weighted formulae as well as their merging is an important but difficult task. In
this paper, we derive a numerical characteristic function from each knowledge
base with weighted formulae, based on the Dempster-Shafer theory of evidence.
Using these functions, we are able to measure the inconsistency of the knowledge
base in a convenient and rational way, and are able to merge multiple knowledge
bases with weighted formulae, even if knowledge in these bases may be
inconsistent. Furthermore, by examining whether multiple knowledge bases are
dependent or independent, they can be combined in different ways using their
characteristic functions, which cannot be handled (or at least have never been
considered) in classic knowledge based merging approaches in the literature.

The effect of AMS δ13C values on 14C ages measured on a 0.5MV NEC compact accelerator

Many AMS systems can measure 14C, 13C and 12C simultaneously thus providing δ13C values which can be used for fractionation normalization without the need for offline 13C /12C measurements on isotope ratio mass spectrometers (IRMS). However AMS δ13C values on our 0.5MV NEC Compact Accelerator often differ from IRMS values on the same material by 4-5‰ or more. It has been postulated that the AMS δ13C values account for the potential graphitization and machine induced fractionation, in addition to natural fractionation, but how much does this affect the 14C ages or F14C? We present an analysis of F14C as a linear least squares fit with AMS δ13C results for several of our secondary standards. While there are samples for which there is an obvious correlation between AMS δ13C and F14C, as quantified with the calculated probability of no correlation, we find that the trend lies within one standard deviation of the variance on our F14C measurements. Our laboratory produces both zinc and hydrogen reduced graphite, and we present our results for each type. Additionally, we show the variance on our AMS δ13C measurements of our secondary standards.

Energy Saving - Another Perspective for Parameter Optimization of P and PI Controllers

Modern control methods like optimal control and model predictive control (MPC) provide a framework for simultaneous regulation of the tracking performance and limiting the control energy, thus have been widely deployed in industrial applications. Yet, due to its simplicity and robustness, the conventional P (Proportional) and PI (Proportional–Integral) control are still the most common methods used in many engineering systems, such as electric power systems, automotive, and Heating, Ventilation and Air Conditioning (HVAC) for buildings, where energy efficiency and energy saving are the critical issues to be addressed. Yet, little has been done so far to explore the effect of its parameter tuning on both the system performance and control energy consumption, and how these two objectives are correlated within the P and PI control framework. In this paper, the P and PI controllers are designed with a simultaneous consideration of these two aspects. Two case studies are investigated in detail, including the control of Voltage Source Converters (VSCs) for transmitting offshore wind power to onshore AC grid through High Voltage DC links, and the control of HVAC systems. Results reveal that there exists a better trade-off between the tracking performance and the control energy through a proper choice of the P and PI controller parameters.

Electron-phonon thermalization in a scalable method for real-time quantum dynamics

We present a quantum simulation method that follows the dynamics of out-of-equilibrium many-body systems of electrons and oscillators in real time. Its cost is linear in the number of oscillators and it can probe time scales from attoseconds to hundreds of picoseconds. Contrary to Ehrenfest dynamics, it can thermalize starting from a variety of initial conditions, including electronic population inversion. While an electronic temperature can be defined in terms of a nonequilibrium entropy, a Fermi-Dirac distribution in general emerges only after thermalization. These results can be used to construct a kinetic model of electron-phonon equilibration based on the explicit quantum dynamics.

Properties of self-assembled diluted magnetic semiconductor nanostructures

Este trabalho centra-se na investigação da possibilidade de se conseguir um semicondutor magnético diluído (SMD) baseado em ZnO. Foi levado a cabo um estudo detalhado das propriedades magnéticas e estruturais de estruturas de ZnO, nomeadamente nanofios (NFs), nanocristais (NCs) e filmes finos, dopadas com metais de transição (MTs). Foram usadas várias técnicas experimentais para caracterizar estas estruturas, designadamente difracção de raios-X, microscopia electrónica de varrimento, ressonância magnética, SQUID, e medidas de transporte. Foram incorporados substitucionalmente nos sítios do Zn iões de Mn2+ e Co2+ em ambos os NFs e NCs de ZnO. Revelou-se para ambos os iões dopantes, que a incorporação é heterogénea, uma vez que parte do sinal de ressonância paramagnética electrónica (RPE) vem de iões de MTs em ambientes distorcidos ou enriquecidos com MTs. A partir das intensidades relativas dos espectros de RPE e de modificações da superfície, demonstra-se ainda que os NCs exibem uma estrutura core-shell. Os resultados, evidenciam que, com o aumento da concentração de MTs, a dimensão dos NCs diminui e aumentam as distorções da rede. Finalmente, no caso dos NCs dopados com Mn, obteve-se o resultado singular de que a espessura da shell é da ordem de 0.3 nm e de que existe uma acumulação de Mn na mesma. Com o objectivo de esclarecer o papel dos portadores de carga na medição das interacções ferromagnéticas, foram co-dopados filmes de ZnO com Mn e Al ou com Co e Al. Os filmes dopados com Mn, revelaram-se simplesmente paramagnéticos, com os iões de Mn substitucionais nos sítios do Zn. Por outro lado, os filmes dopados com Co exibem ferromagnetismo fraco não intrínseco, provavelmente devido a decomposição spinodal. Foram ainda efectuados estudos comparativos com filmes de ligas de Zn1-xFexO. Como era de esperar, detectaram-se segundas fases de espinela e de óxido de ferro nestas ligas; todas as amostras exibiam curvas de histerese a 300 K. Estes resultados suportam a hipótese de que as segundas fases são responsáveis pelo comportamento magnético observado em muitos sistemas baseados em ZnO. Não se observou nenhuma evidência de ferromagnetismo mediado por portadores de carga. As experiências mostram que a análise de RPE permite demonstrar directamente se e onde estão incorporados os iões de MTs e evidenciam a importância dos efeitos de superfície para dimensões menores que ~15 nm, para as quais se formam estruturas core-shell. As investigações realizadas no âmbito desta tese demonstram que nenhuma das amostras de ZnO estudadas exibiram propriedades de um SMD intrínseco e que, no futuro, são necessários estudos teóricos e experimentais detalhados das interacções de troca entre os iões de MTs e os átomos do ZnO para determinar a origem das propriedades magnéticas observadas.

Microalgae taxonomy and breeding

Microalgae are a diverse group of organisms that form the basic component of many eco­- systems. The systemic classification of algae is primarily based on their pigment composition and is divided into nine classes. The largest groups are Chlorophyceae (green algae), Phaeophyceae (brown algae), Pyrrophyceae (dinoflagellates), Chrysophyceae (golden brown algae), Bacillariophyceae (diatoms) and Rhodo­ phyceae (red algae). It has been estimated that between 22,000 and 26,000 species exist (Norton et al., 1996), of which only a few species have been identified to be useful for commercial application, such as Spirulina, Chlorella, Haematococcus, Dunaliella, Botryococcus, Phaeodactylum and Porphyridium. Several other species that are also cultivated commercially for the hatcheries in the aquaculture field include Chaetoceros, Crypthecodinium, Isochrysis, Nannochloris, Nitzschia, Schizo­chytrium, Tetraselmis and Skeletonema (Raja et al., 2008).

Enabling Scientific Workflow Sharing through Coarse-Grained Interoperability

E-scientists want to run their scientific experiments on Distributed Computing Infrastructures (DCI) to be able to access large pools of resources and services. To run experiments on these infrastructures requires specific expertise that e-scientists may not have. Workflows can hide resources and services as a virtualization layer providing a user interface that e-scientists can use. There are many workflow systems used by research communities but they are not interoperable. To learn a workflow system and create workflows in this workflow system may require significant efforts from e-scientists. Considering these efforts it is not reasonable to expect that research communities will learn new workflow systems if they want to run workflows developed in other workflow systems. The solution is to create workflow interoperability solutions to allow workflow sharing. The FP7 Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs (SHIWA) project developed two interoperability solutions to support workflow sharing: Coarse-Grained Interoperability (CGI) and Fine-Grained Interoperability (FGI). The project created the SHIWA Simulation Platform (SSP) to implement the Coarse-Grained Interoperability approach as a production-level service for research communities. The paper describes the CGI approach and how it enables sharing and combining existing workflows into complex applications and run them on Distributed Computing Infrastructures. The paper also outlines the architecture, components and usage scenarios of the simulation platform.

Analyzing and Modeling Medical Data on Distributed Computing Infrastructures

Researchers want to analyse Health Care data which may requires large pools of compute and data resources. To have them they need access to Distributed Computing Infrastructures (DCI). To use them it requires expertise which researchers may not have. Workflows can hide infrastructures. There are many workflow systems but they are not interoperable. To learn a workflow system and create workflows in a workflow system may require significant effort. Considering these efforts it is not reasonable to expect that researchers will learn new workflow systems if they want to run workflows of other workflow systems. As a result, the lack of interoperability prevents workflow sharing and a vast amount of research efforts is wasted. The FP7 Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs (SHIWA) project developed the Coarse-Grained Interoperability (CGI) to enable workflow sharing. The project created the SHIWA Simulation Platform (SSP) to support CGI as a production-level service. The paper describes how the CGI approach can be used for analysis and simulation in Health Care.

Self-similarity principle: the reduced description of randomness

A new general fitting method based on the Self-Similar (SS) organization of random sequences is presented. The proposed analytical function helps to fit the response of many complex systems when their recorded data form a self-similar curve. The verified SS principle opens new possibilities for the fitting of economical, meteorological and other complex data when the mathematical model is absent but the reduced description in terms of some universal set of the fitting parameters is necessary. This fitting function is verified on economical (price of a commodity versus time) and weather (the Earth’s mean temperature surface data versus time) and for these nontrivial cases it becomes possible to receive a very good fit of initial data set. The general conditions of application of this fitting method describing the response of many complex systems and the forecast possibilities are discussed.

Notch1 and T-cell development: insights from conditional knockout mice.

Notch proteins influence cell-fate decisions in many developmental systems. Gain-of-function studies have suggested a crucial role for Notch1 signaling at several stages during lymphocyte development, including the B/T, alphabeta/gammadelta and CD4/CD8 lineage choices. Here, we critically re-evaluate these conclusions in the light of recent studies that describe inducible and tissue-specific targeting of the Notch1 gene.