Ground-state Stabilization of Open Quantum Systems by Dissipation

Control by dissipation, or environment engineering, constitutes an important methodology within quantum coherent control which was proposed to improve the robustness and scalability of quantum control systems. The system-environment coupling, often considered to be detrimental to quantum coherence, also provides the means to steer the system to desired states. This paper aims to develop the theory for engineering of the dissipation, based on a ground-state Lyapunov stability analysis of open quantum systems via a Heisenberg-picture approach. Algebraic conditions concerning the ground-state stability and scalability of quantum systems are obtained. In particular, Lyapunov stability conditions expressed as operator inequalities allow a purely algebraic treatment of the environment engineering problem, which facilitates the integration of quantum components into a large-scale quantum system and draws an explicit connection to the classical theory of vector Lyapunov functions and decomposition-aggregation methods for control of complex systems. The implications of the results in relation to dissipative quantum computing and state engineering are also discussed in this paper.Comment: 18 pages, to appear in Automatic

Mathematical techniques for estimating operational readiness of complex systems

Development of methods for predicting operational readiness of complex systems based on probability theory is discussed. Operational readiness of systems is defined and mathematical relationships involved in determining readiness are presented. Example of reliability engineering and quality control is included

Engineering management of large scale systems

The organization of high technology and engineering problem solving, has given rise to an emerging concept. Reasoning principles for integrating traditional engineering problem solving with system theory, management sciences, behavioral decision theory, and planning and design approaches can be incorporated into a methodological approach to solving problems with a long range perspective. Long range planning has a great potential to improve productivity by using a systematic and organized approach. Thus, efficiency and cost effectiveness are the driving forces in promoting the organization of engineering problems. Aspects of systems engineering that provide an understanding of management of large scale systems are broadly covered here. Due to the focus and application of research, other significant factors (e.g., human behavior, decision making, etc.) are not emphasized but are considered

Model-driven performance evaluation for service engineering

Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Software quality aspects such as performance are of central importance for the integration of heterogeneous, distributed service-based systems. Empirical performance evaluation is a process of measuring and calculating performance metrics of the implemented software. We present an approach for the empirical, model-based performance evaluation of services and service compositions in the context of model-driven service engineering. Temporal databases theory is utilised for the empirical performance evaluation of model-driven developed service systems

Set Theory and Proofs for Engineering Education

Through evaluations of learning objectives on several Engineering courses, the majority of students at some point will struggle with demonstration of proof of a principle in their homework assignments, quizzes, and exams. An early introduction of "Set Theory and Proofs" to engineering students can enrich their intuition and ability to solve comprehensive problems. As illustrated in this paper, set theory can be recognized by students as a simple and unnecessary topic. However, the understanding of principles in set theory and its derived concepts are essential to engineering students so they can improve their problem-solving skills when approaching a more complex problem using mathematics. Set Theory is a vast field of study which includes: Operations and algebra with sets, power sets, product sets, relations, functions, quantifiers, family of sets, index sets, just to name a few [1]. At The University of Texas at Tyler, the authors experienced set theory embedded in the learning objectives of Manufacturing Systems (MENG 5318) course offered by the Mechanical Engineering Department to its graduate students. In Fall 2016 and 2017, most of the students in the class failed to apply some of the principles in set theory. Overall, set theory is an important topic to engineering students where an understanding of the principal will ensure the success in completing advanced level courses.Cockrell School of Engineerin

Regulating Complexity in Financial Markets

As the financial crisis has tragically illustrated, the complexities of modern financial markets and investment securities can trigger systemic market failures. Addressing these complexities, this Article maintains, is perhaps the greatest financial-market challenge of the future. The Article first examines and explains the nature of these complexities. It then analyzes the regulatory and other steps that should be considered to reduce the potential for failure. Because complex financial markets resemble complex engineering systems, and failures in those markets have characteristics of failures in those systems, the Article‟s analysis draws on chaos theory and other approaches used to analyze complex engineering systems

Towards a Theory of Systems Engineering Processes: A Principal-Agent Model of a One-Shot, Shallow Process

Systems engineering processes coordinate the effort of different individuals to generate a product satisfying certain requirements. As the involved engineers are self-interested agents, the goals at different levels of the systems engineering hierarchy may deviate from the system-level goals which may cause budget and schedule overruns. Therefore, there is a need of a systems engineering theory that accounts for the human behavior in systems design. To this end, the objective of this paper is to develop and analyze a principal-agent model of a one-shot (single iteration), shallow (one level of hierarchy) systems engineering process. We assume that the systems engineer maximizes the expected utility of the system, while the subsystem engineers seek to maximize their expected utilities. Furthermore, the systems engineer is unable to monitor the effort of the subsystem engineer and may not have a complete information about their types or the complexity of the design task. However, the systems engineer can incentivize the subsystem engineers by proposing specific contracts. To obtain an optimal incentive, we pose and solve numerically a bi-level optimization problem. Through extensive simulations, we study the optimal incentives arising from different system-level value functions under various combinations of effort costs, problem-solving skills, and task complexities