Optimal control of many-body quantum dynamics: chaos and complexity

Achieving full control of the time-evolution of a many-body quantum system is currently a major goal in physics. In this work we investigate the different ways in which the controllability of a quantum system can be influenced by its complexity, or even its chaotic properties. By using optimal control theory, we are able to derive the control fields necessary to drive various physical processes in a spin chain. Then, we study the spectral properties of such fields and how they relate to different aspects of the system complexity. We find that the spectral bandwidth of the fields is, quite generally, independent of the system dimension. Conversely, the spectral complexity of such fields does increase with the number of particles. Nevertheless, we find that the regular o chaotic nature of the system does not affect signficantly its controllability.Comment: 9 pages, 5 figure

Time-optimal control fields for quantum systems with multiple avoided crossings

We study time-optimal protocols for controlling quantum systems which show several avoided level crossings in their energy spectrum. The structure of the spectrum allows us to generate a robust guess which is time-optimal at each crossing. We correct the field applying optimal control techniques in order to find the minimal evolution or quantum speed limit (QSL) time. We investigate its dependence as a function of the system parameters and show that it gets proportionally smaller to the well-known two-level case as the dimension of the system increases. Working at the QSL, we study the control fields derived from the optimization procedure, and show that they present a very simple shape, which can be described by a few parameters. Based on this result, we propose a simple expression for the control field, and show that the full time-evolution of the control problem can be analytically solved.Comment: 11 pages, 7 figure

Finding a reflexive voice : -- researching the problems of implementing new learning practices within a New Zealand manufacturing organisation : a 100pt thesis presented in partial fulfilment of the requirements for the degree of Master of Management in Human Resources Management at Massey University

This study explored the social forces mediating manager's participation in a new reflexive participative learning practice designed to improve profitability within a New Zealand manufacturing organisation. Despite a large theoretical and managerial body of literature on organisational learning there has been little empirical investigation of how people experience and engage their reflexivity towards challenging the status-quo to create high level learning and new knowledge. Power was identified as a potential moderator of the reflexive learning experience and the variable relations of power and learning were constructed from a review of literature and these relationships were explored and investigated within the case study. Two prevailing discourses were identified as powerful moderators of public reflexivity, the traditionalist discourse which constructed managers actions and conversations towards insularism and survivalist concerns and the productionist discourse in which institutionalised production practices encircled and mediated managers actions and what constituted legitimacy in conversations. This study used a critical action research method to place the reflexive experience of managers and the researcher at the centre of the study and provide data representative of the social discourses that constructed variable freedoms and constraints upon the reflexive voice

Maximum population transfer in a periodically driven two-level system

We study the dynamics of a two-level quantum system under the influence of sinusoidal driving in the intermediate frequency regime. Analyzing the Floquet quasienergy spectrum, we find combinations of the field parameters for which population transfer is optimal and takes place through a series of well defined steps of fixed duration. We also show how the corresponding evolution operator can be approximated at all times by a very simple analytical expression. We propose this model as being specially suitable for treating periodic driving at avoided crossings found in complex multi-level systems, and thus show a relevant application of our results to designing a control protocol in a realistic molecular modelComment: 7 pages, 6 figure

Solar radiation forecasting using ad-hoc time series preprocessing and neural networks

In this paper, we present an application of neural networks in the renewable energy domain. We have developed a methodology for the daily prediction of global solar radiation on a horizontal surface. We use an ad-hoc time series preprocessing and a Multi-Layer Perceptron (MLP) in order to predict solar radiation at daily horizon. First results are promising with nRMSE < 21% and RMSE < 998 Wh/m2. Our optimized MLP presents prediction similar to or even better than conventional methods such as ARIMA techniques, Bayesian inference, Markov chains and k-Nearest-Neighbors approximators. Moreover we found that our data preprocessing approach can reduce significantly forecasting errors.Comment: 14 pages, 8 figures, 2009 International Conference on Intelligent Computin

Characterizing dynamics with covariant Lyapunov vectors

A general method to determine covariant Lyapunov vectors in both discrete- and continuous-time dynamical systems is introduced. This allows to address fundamental questions such as the degree of hyperbolicity, which can be quantified in terms of the transversality of these intrinsic vectors. For spatially extended systems, the covariant Lyapunov vectors have localization properties and spatial Fourier spectra qualitatively different from those composing the orthonormalized basis obtained in the standard procedure used to calculate the Lyapunov exponents.Comment: 4 pages, 3 figures, submitted to Physical Review letter

Factors Influencing Chat-Based Cultural Discussions for Learning History in a 3D Virtual World

In a fast-changing world, there is an increasingly felt need to bring what we teach and how we teach it intothe 21st Century. Learning@Europe is an attempt in this direction: a shared online virtual world where students from different European countries meet to play and learn about European history. Chat-based discussions of study material, research homework to prepare in col-laboration with remote peers on online forums, team games and a cultural com-petition are the main ingredients of this innovative experience, already tested by over 6000 high-school students and teachers from 18 European countries. This paper focuses on a particular Learning@Europe activity – chat-based cultural discussions about history – and analyzes the elements that are essential to its success. Basing on evaluation data and our 3-years experience, we describe strategies deal with the different elements to be taken into account: Technology; Content; Interaction Design; and – mostimportant of all – Social Behavior