Information Physics
Physics-Information and Quantum Analogies for Complex Systems Modeling
- 1st Edition - June 14, 2021
- Latest edition
- Author: Miroslav Svitek
- Language: English
Information Physics: Physics-Information and Quantum Analogies for Complex Modeling presents a new theory of complex systems that uses analogy across various aspects of physic… Read more
Information Physics: Physics-Information and Quantum Analogies for Complex Modeling presents a new theory of complex systems that uses analogy across various aspects of physics, including electronics, magnetic circuits and quantum mechanics. The book 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 incomplete pieces of overlapping information that must be strung together to find the most consistent model. This incomplete information can be understood as a set of non-exclusive observer results. Because they are non-exclusive, each observer registers different pictures of reality.
- Provides readers with an understanding of the analogies between very sophisticated theories of electrical circuits and currently underdeveloped information circuits, including capturing positive and negative links, as well as serial and parallel ordering of information blocks
- Integrates coverage of quantum models of complex systems using wave probabilistic functions which extend the classical probability description by phase parameters that allow researchers to model such properties as entanglement, superposition and others
- Provides readers with illustrative examples of how to use the presented theories of complex systems in specific cases such as hierarchical systems, cooperation of a team of experts, the lifecycle of the company, and the link between short and long-term memory
Academics (scientists, researchers, MSc. PhD. students) from the fields of Mathematics, Computer Science, Biology, Electrical Engineering, and Information Technology. The audience includes researchers and practitioners in any field that deals with systems sciences – modelling of complex systems, description of soft systems, systems analysis and synthesis
1. Introduction to Information Physics 1.1 Dynamical systems1.2 Information representation1.3 Information source and recipient1.4 Information gate1.5 Information perception1.6 Information scenarios
1.7 Information channel
2. Classical Physics – Information Analogies 2.1 Electrics – information analogies 2.2 Magnetic – information analogies 2.3 Information elements2.4 Extended information elements 2.5 Information mem-elements
3. Information circuits3.1 Telematics 3.2 Brain adaptive resonance 3.3 Knowledge cycle
4. Quantum Physics - Information Analogies 4.1 Quantum events 4.2 Quantum objects 4.3 Two (non-)exclusive observers4.4 Composition of quantum objects4.5 Mixture of partial quantum information
4.6 Time-varying quantum objects 4.7 Quantum information coding and decoding
4.8 Quantum data flow rate4.9 Holographic approach to phase parameters
4.10 Two (non-) distinguished quantum subsystems
4.11 Quantum information gate
4.12 Quantum learning
5 Features of Quantum Information 5.1 Quantization 5.2 Quantum entanglement 5.3 Quantum environment 5.4 Quantum identity 5.5 Quantum self-organization 5.6 Quantum interference 5.7 Distance between wave components 5.8 Interaction’s speed between wave components
5.9 Component strength
5.10 Quantum node
6. Composition rules of quantum subsystems
6.1 Connected subsystems
6.2 Disconnected subsystems
6.3 Coexisted subsystems
6.4 Symmetrically disconnected subsystems
6.5 Symmetrically competing subsystems
6.6 Interactions with an environment
6.7 Illustrative examples
7. Applicability of quantum models
7.1 Quantum processes
7.2 Quantum model of hierarchical networks
7.3 Time-varying quantum systems
7.4 Quantum information gyrator
7.5 Quantum transfer functions
8. Extended quantum models
8.1 Ordering models
8.2 Incremental models
8.3 Inserted models
8.4 Intersectional extended models
9. Complex adaptive systems
9.1 Basic agent of smart services
9.2 Smart resilient cities
9.3 Intelligent transport systemts
9.4 Ontology and multiagent technologies
10. Conclusion
- Edition: 1
- Latest edition
- Published: June 14, 2021
- Language: English
MS
Miroslav Svitek
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
Affiliations and expertise
Professor, Czech Technical University, Prague, Czech RepublicRead Information Physics on ScienceDirect