Information Physics: Physics-Information and Quantum Analogies for Complex Systems Modeling - Tapa blanda

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Dr. Miroslav Svitek is a full professor in Engineering Informatics at Faculty of Transportation Sciences, Czech Technical University in Prague. He has been the Dean of Faculty of Transportation Sciences, Czech Technical University. Since 2018, he has been a Visiting Professor in Smart Cities at University of Texas at El Paso, USA. The focus of his research includes complex system sciences and their practical applications to Intelligent Transport Systems, Smart Cities and Smart Regions. He is the author or co-author of more than 200 scientific papers and 10 books, including Quantum System Theory: Principles and Applications and Stochastic Processes: Estimation, Optimisation, and Analysis. He received his Ph.D. in radioelectronics at Faculty of Electrical Engineering, Czech Technical University. In 2005, he was been nominated as the extraordinary professor in applied informatics at Faculty of Natural Sciences, University of Matej Bel in Banska Bystrica, Slovak Republic. In 2008, Dr. Svítek was the first president of the Czech Smart City Cluster, and he is a member of the Engineering Academy of the Czech Republic. In 2006 – 2018, he served as President of the Association of Transport Telematics

De la contraportada

Information Physics: Physics-Information and Quantum Analogies for Complex Modelling presents a new theory of complex systems presented by using the analogy with various aspects of physics electronics, magnetic circuits, and quantum mechanics. The key idea presented by Dr. Miroslav Svítek is the recognition of information flow and information content as the main quantities in informatics as e.g. electrical current and voltage is used in electrical engineering. With respect to this idea, the known mathematical instruments of electrical / magnetic circuit modelling can be applied to the modelling of complex information systems. Such an approach leads to better definition of an event s source that includes both an information content (quality of the information source) and an information flow (how the information source is distributed). Another result is the clear separation between an information source and an information recipient. The recipient sometimes is not able to process the transmitted information and it uses only its part. The presented model can consider such situations.

Information Physics: Physics-Information and Quantum Analogies for Complex Modelling also explains the quantum approach to system theory that can be understood as an extension of classical system models. The main idea is that in many complex systems there are a lot of incomplete pieces of overlapping information that must be composed together to find the best consistent model for the whole. The incomplete information can be understood as a set of non-exclusive observers results each of them represents the reality through its limited capabilities. Because they are non-exclusive, each observer registers different pictures of the reality. Quantum models with information pieces can be interconnected in serial, parallel, and feedback ordering. They can also be time-varying with a lot of interesting features such as entanglement, emergency, or selforganization. Dr. Svítek presents the ways in which such mathematical instruments can be applied to many fields, including the human sciences.

In quantum physics, moduli typically represent energy. In the quantum system approach to modelling, the mathematical instrument of wave probabilities has, therefore, much broader applications than in physics. In system sciences, for example, the reader can evaluate by quantum models other system features such as the ability to create alliances, the ability for adaptation (the quickest response to changes), and others. The presented methodology can be further enlarged not only to entanglement among pure events and events functions, but also it can add an enlargement of different system processes and their functions. Readers will learn that through the complexity of such a model, we are approaching Kaufmann s issue as a network representation of complex systems.