Quantum Information Processing with spin systems: from modeling to possible implementations

The physical implementation of quantum information processing is one of the major challenges of current research. In the last few years, several theoretical proposals and experimental demonstrations on a small number of qubits have been carried out, but a quantum computing architecture that is straightforwardly scalable, universal, and realizable with state-of-the-art technology is still lacking. In particular, a major ultimate objective is the construction of quantum simulators, yielding massively increased computational power in simulating quantum systems. Here we investigate promising routes towards the actual realization of a quantum computer, based on spin systems. The first one employs molecular nanomagnets with a doublet ground state to encode each qubit and exploits the wide chemical tunability of these systems to obtain the proper topology of inter-qubit interactions. Indeed, recent advances in coordination chemistry allow us to arrange these qubits in chains, with tailored interactions mediated by magnetic linkers. These act as switches of the effective qubit-qubit coupling, thus enabling the implementation of one- and two-qubit gates. Molecular qubits can be controlled either by uniform magnetic pulses, either by local electric fields. We introduce here two different schemes for quantum information processing with either global or local control of the inter-qubit interaction and demonstrate the high performance of these platforms by simulating the system time evolution with state-of-the-art parameters. The second architecture we propose is based on a hybrid spin-photon qubit encoding, which exploits the best characteristic of photons, whose mobility is exploited to efficiently establish long-range entanglement, and spin systems, which ensure long coherence times. The setup consists of spin ensembles coherently coupled to single photons within superconducting coplanar waveguide resonators. The tunability of the resonators frequency is exploited as the only manipulation tool to implement a universal set of quantum gates, by bringing the photons into/out of resonance with the spin transition. The time evolution of the system subject to the pulse sequence used to implement complex quantum algorithms has been simulated by numerically integrating the master equation for the system density matrix, thus including the harmful effects of decoherence. Finally a scheme to overcome the leakage of information due to inhomogeneous broadening of the spin ensemble is pointed out. Both the proposed setups are based on state-of-the-art technological achievements. By extensive numerical experiments we show that their performance is remarkably good, even for the implementation of long sequences of gates used to simulate interesting physical models. Therefore, the here examined systems are really promising buildingblocks of future scalable architectures and can be used for proof-of-principle experiments of quantum information processing and quantum simulation.

Numerically optimized implementations, mitigation and simulations of polarisation mode dispersion in real-time transmission systems

The aim of this thesis is to present numerical investigations of the polarisation mode dispersion (PMD) effect. Outstanding issues on the side of the numerical implementations of PMD are resolved and the proposed methods are further optimized for computational efficiency and physical accuracy. Methods for the mitigation of the PMD effect are taken into account and simulations of transmission system with added PMD are presented. The basic outline of the work focusing on PMD can be divided as follows. At first the widely-used coarse-step method for simulating the PMD phenomenon as well as a method derived from the Manakov-PMD equation are implemented and investigated separately through the distribution of a state of polarisation on the Poincaré sphere, and the evolution of the dispersion of a signal. Next these two methods are statistically examined and compared to well-known analytical models of the probability distribution function (PDF) and the autocorrelation function (ACF) of the PMD phenomenon. Important optimisations are achieved, for each of the aforementioned implementations in the computational level. In addition the ACF of the coarse-step method is considered separately, based on the result which indicates that the numerically produced ACF, exaggerates the value of the correlation between different frequencies. Moreover the mitigation of the PMD phenomenon is considered, in the form of numerically implementing Low-PMD spun fibres. Finally, all the above are combined in simulations that demonstrate the impact of the PMD on the quality factor (Q=factor) of different transmission systems. For this a numerical solver based on the coupled nonlinear Schrödinger equation is created which is otherwise tested against the most important transmission impairments in the early chapters of this thesis.

An investigation into enterprise structure and ERP implementations:a contribution to praxis

This professional doctoral research reports on the relationship between Enterprise Systems, specifically Enterprise Resource Planning Systems, and enterprise structures. It offers insights and guidance to practitioners on factors for consideration in the implementation of ERP systems in organisations operating in modern enterprise structures. It reports on reflective ethnographic action research conducted in a number of companies from a diverse range of industries covering supply chains for both goods and services. The primary contribution is in highlighting areas in which clients, practitioners and ERP software vendors can bring a greater awareness of internet era enterprise structures and business requirements into the ERP arena. The concepts and insights have been explored in a focus group setting, comprised of practitioners from the enterprise systems implementation and consulting fraternity and revealed limitations and constraints in the implementation of enterprise systems. However, it also showed that current systems do not have the full capabilities required to support, in use, modern era enterprise structures, as required by practitioners and decision makers.

Combining algorithms to predict bacterial protein sub-cellular location:parallel versus concurrent implementations

We describe a novel and potentially important tool for candidate subunit vaccine selection through in silico reverse-vaccinology. A set of Bayesian networks able to make individual predictions for specific subcellular locations is implemented in three pipelines with different architectures: a parallel implementation with a confidence level-based decision engine and two serial implementations with a hierarchical decision structure, one initially rooted by prediction between membrane types and another rooted by soluble versus membrane prediction. The parallel pipeline outperformed the serial pipeline, but took twice as long to execute. The soluble-rooted serial pipeline outperformed the membrane-rooted predictor. Assessment using genomic test sets was more equivocal, as many more predictions are made by the parallel pipeline, yet the serial pipeline identifies 22 more of the 74 proteins of known location.

VLSI Watermark Implementations and Applications

This paper presents an up to date review of digital watermarking (WM) from a VLSI designer point of view. The reader is introduced to basic principles and terms in the field of image watermarking. It goes through a brief survey on WM theory, laying out common classification criterions and discussing important design considerations and trade-offs. Elementary WM properties such as robustness, computational complexity and their influence on image quality are discussed. Common attacks and testing benchmarks are also briefly mentioned. It is shown that WM design must take the intended application into account. The difference between software and hardware implementations is explained through the introduction of a general scheme of a WM system and two examples from previous works. A versatile methodology to aid in a reliable and modular design process is suggested. Relating to mixed-signal VLSI design and testing, the proposed methodology allows an efficient development of a CMOS image sensor with WM capabilities.

Hardware Implementations of Video Watermarking

Various digital watermarking (WM) techniques for still imaging have been studied in the last several years. Recently, many new WM schemes have been proposed for other types of digital multimedia data, such as text, audio and video. This paper presents a brief overview of existing digital video WM. We classify WM techniques and discuss the properties of video WM. Since each WM application has its own specific requirements, WM design must take the intended application into consideration. Video WM applications are also discussed in the paper. The features of video WM implementations in software and hardware and their differences are presented through the description of four examples of existing work.

Quantitative comparison of low-cost OFDMA-PON transceiver implementations

A quantitative comparison of up to 40 Gb/s low-cost orthogonal frequency-division multiplexing access (OFDMA)-passive optical networks (PON) implementations for both upstream (US) and downstream (DS) directions is evaluated based on different modulation and detection techniques. © 2012 IEEE.

Coding Strategies and Implementations of Compressive Sensing

This dissertation studies the coding strategies of computational imaging to overcome the limitation of conventional sensing techniques. The information capacity of conventional sensing is limited by the physical properties of optics, such as aperture size, detector pixels, quantum efficiency, and sampling rate. These parameters determine the spatial, depth, spectral, temporal, and polarization sensitivity of each imager. To increase sensitivity in any dimension can significantly compromise the others.

This research implements various coding strategies subject to optical multidimensional imaging and acoustic sensing in order to extend their sensing abilities. The proposed coding strategies combine hardware modification and signal processing to exploiting bandwidth and sensitivity from conventional sensors. We discuss the hardware architecture, compression strategies, sensing process modeling, and reconstruction algorithm of each sensing system.

Optical multidimensional imaging measures three or more dimensional information of the optical signal. Traditional multidimensional imagers acquire extra dimensional information at the cost of degrading temporal or spatial resolution. Compressive multidimensional imaging multiplexes the transverse spatial, spectral, temporal, and polarization information on a two-dimensional (2D) detector. The corresponding spectral, temporal and polarization coding strategies adapt optics, electronic devices, and designed modulation techniques for multiplex measurement. This computational imaging technique provides multispectral, temporal super-resolution, and polarization imaging abilities with minimal loss in spatial resolution and noise level while maintaining or gaining higher temporal resolution. The experimental results prove that the appropriate coding strategies may improve hundreds times more sensing capacity.

Human auditory system has the astonishing ability in localizing, tracking, and filtering the selected sound sources or information from a noisy environment. Using engineering efforts to accomplish the same task usually requires multiple detectors, advanced computational algorithms, or artificial intelligence systems. Compressive acoustic sensing incorporates acoustic metamaterials in compressive sensing theory to emulate the abilities of sound localization and selective attention. This research investigates and optimizes the sensing capacity and the spatial sensitivity of the acoustic sensor. The well-modeled acoustic sensor allows localizing multiple speakers in both stationary and dynamic auditory scene; and distinguishing mixed conversations from independent sources with high audio recognition rate.

Enterprise resources planning systems impacts: A Delphi study of Australian public sector

The business value of Enterprise Resource Planning systems (ERP systems), and in general large software implementations, has been extensively debated in both popular press and in the academic literature for over two decades. Organisations invest enormous sums of money and resources in Enterprise Resource Planning systems (and related infrastructure), presumably expecting positive impacts to the organisation and its functions. Some studies have reported large productivity improvements and substantial benefits from ERP systems, while others have reported that ERP systems have not had any bottom-line impact. This paper discusses initial findings from a study that focuses on identifying and assessing important ERP impacts in 23 Australian public sector organizations.

Knowledge management for ERP success

The business value of Enterprise Resource Planning (ERP) systems and in general large software implementations has been extensively debated in both popular press and academic literature for over three decades. Despite the positive motives for adoption, various organizations have reported negative impacts from these large investments. This ‘disconnect’ between large IS investments and firms’ organizational performance may be attributable to the economic transition from an era of competitive advantage based on information to one that is based on Knowledge. This paper discusses the initial findings of a two-phased study that focuses on empirically assessing the impact of knowledge management on the success of Enterprise Resource Planning systems. The research study uses information gathered from twenty-seven public sector organizations in Queensland, Australia. Validation of the a priori model constructs through factor analysis identified two dimensions of knowledge management. Further analysis assessed the comparative differences in perceptions of knowledge management in ERP, across four employment cohorts.

K-tree : large scale document clustering

We introduce K-tree in an information retrieval context. It is an efficient approximation of the k-means clustering algorithm. Unlike k-means it forms a hierarchy of clusters. It has been extended to address issues with sparse representations. We compare performance and quality to CLUTO using document collections. The K-tree has a low time complexity that is suitable for large document collections. This tree structure allows for efficient disk based implementations where space requirements exceed that of main memory.

Report a review of the concepts and definitions of the various forms of relational contracting

Partnering has been defined in many ways. It can be considered as an individual project mechanism or can be considered as a long term strategy. Alliancing is normally assumed to be a long term business strategy linking together client, contractor and supply chain. Relational contracting goes further than this and brings in the whole philosophy of the value chain and the linking of the interdependent parts within the construction project as a key business objective. This document aims to review existing definitions of these three concepts and present and overview of the current state of-the-art in terms of their use and implementation. The document should be useful for all of those project team members looking to sharpen their understanding of the various concepts and will also provide a platform for debating the current state of the definitions and implementations being used in Main Roads and Public Works Departments.

Automated code checking

Most buildings constructed in Australia must comply with the Building Code of Australia (BCA). Checking for compliance against the BCA is a major task for both designers and building surveyors. This project carries out a prototype research using the EDM Model Checker and the SMC Model Checker for automated design checking against the Building Codes of Australia for use in professional practice. In this project, we develop a means of encoding design requirements and domain specific knowledge for building codes and investigate the flexibility of building models to contain design information. After assessing two implementations of EDM and SMC that check compliance against deemed-to-satisfy provision of building codes relevant to access by people with disabilities, an approach to automated code checking using a shared object-oriented database is established. This project can be applied in other potential areas – including checking a building design for non-compliance of many types of design requirements. Recommendations for future development and use in other potential areas in construction industries are discussed