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

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

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

Metamodeling and metaquerying in OWL 2 QL

OWL 2 QL is a standard profile of the OWL 2 ontology language, specifically tailored to Ontology-Based Data Management. Inspired by recent work on higher-order Description Logics, in this paper we present a new semantics for OWL 2 QL ontologies, called Metamodeling Semantics (MS), and show that, in contrast to the official Direct Semantics (DS) for OWL 2, it allows exploiting the metamodeling capabilities natively offered by the OWL 2 punning. We then extend unions of conjunctive queries with both metavariables, and the possibility of using TBox atoms, with the purpose of expressing meaningful metalevel queries. We first show that under MS both satisfiability checking and answering queries including only ABox atoms, have the same complexity as under DS. Second, we investigate the problem of answering general metaqueries, and single out a new source of complexity coming from the combined presence of a specific type of incompleteness in the ontology, and of TBox axioms among the query atoms. Then we focus on a specific class of ontologies, called TBox-complete, where there is no incompleteness in the TBox axioms, and show that general metaquery answering in this case has again the same complexity as under DS. Finally, we move to general ontologies and show that answering general metaqueries is coNP-complete with respect to ontology complexity, Π2p-complete with respect to combined complexity, and remains AC0 with respect to ABox complexity

Annual Research Review: The Power of Predictability – Patterns of Signals in Early Life Shape Neurodevelopment and Mental Health Trajectories

The global burden of early life adversity (ELA) is profound. The World Health Organization has estimated that ELA accounts for almost 30% of all psychiatric cases. Yet, our ability to identify which individuals exposed to ELA will develop mental illness remains poor and there is a critical need to identify underlying pathways and mechanisms. This review proposes unpredictability as an understudied aspect of ELA that is tractable and presents a conceptual model that includes biologically plausible mechanistic pathways by which unpredictability impacts the developing brain. The model is supported by a synthesis of published and new data illustrating the significant impacts of patterns of signals on child development. We begin with an overview of the existing unpredictability literature, which has focused primarily on longer patterns of unpredictability (e.g. years, months, and days). We then describe our work testing the impact of patterns of parental signals on a moment-to-moment timescale, providing evidence that patterns of these signals during sensitive windows of development influence neurocircuit formation across species and thus may be an evolutionarily conserved process that shapes the developing brain. Next, attention is drawn to emerging themes which provide a framework for future directions of research including the evaluation of functions, such as effortful control, that may be particularly vulnerable to unpredictability, sensitive periods, sex differences, cross-cultural investigations, addressing causality, and unpredictability as a pathway by which other forms of ELA impact development. Finally, we provide suggestions for prevention and intervention, including the introduction of a screening instrument for the identification of children exposed to unpredictable experiences

The notion of Abstraction in Ontology-based Data Management

We study a novel reasoning task in Ontology-based Data Management (OBDM), called Abstraction, which aims at associating formal semantic descriptions to data services. In OBDM a domain ontology is used to provide a semantic layer mapped to the data sources of an organization. The basic idea of the work presented in this paper is to explain the semantics of a data service in terms of a query over the ontology. We illustrate a formal framework for this problem, based on three different notions of abstraction, called sound, complete, and perfect, respectively. We present a thorough complexity analysis of two computational problems, namely verification (checking whether a query is an abstraction of a given data service), and computation (computing an abstraction of a given data service)

A review of data abstraction

It is well-known that Artificial Intelligence (AI), and in particular Machine Learning (ML), is not effective without good data preparation, as also pointed out by the recent wave of data-centric AI. Data preparation is the process of gathering, transforming and cleaning raw data prior to processing and analysis. Since nowadays data often reside in distributed and heterogeneous data sources, the first activity of data preparation requires collecting data from suitable data sources and data services, often distributed and heterogeneous. It is thus essential that providers describe their data services in a way to make them compliant with the FAIR guiding principles, i.e., make them automatically Findable, Accessible, Interoperable, and Reusable (FAIR). The notion of data abstraction has been introduced exactly to meet this need. Abstraction is a kind of reverse engineering task that automatically provides a semantic characterization of a data service made available by a provider. The goal of this paper is to review the results obtained so far in data abstraction, by presenting the formal framework for its definition, reporting about the decidability and complexity of the main theoretical problems concerning abstraction, and discuss open issues and interesting directions for future research