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Theory is what remains true when technology is changing. So, it is important to know and master the basic concepts and the theoretical tools that underlie the design of the systems we are using today and the systems we will use tomorrow. This means that, given a computing model, we need to know what can be done and what cannot be done in that model. Considering systems built on top of an asynchronous read/write shared memory prone to process crashes, this monograph presents and develops the fundamental notions that are universal constructions, consensus numbers, distributed recursivity, power of the BG simulation, and what can be done when one has to cope with process anonymity and/or memory anonymity. Numerous distributed algorithms are presented, the aim of which is being to help the reader better understand the power and the subtleties of the notions that are presented. In addition, the reader can appreciate the simplicity and beauty of some of these algorithms.
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Teaching quantum computation and information is notoriously difficult, because it requires covering subjects from various fields of science, organizing these subjects consistently in a unified way despite their tendency to favor their specific languages, and overcoming the subjects’ abstract and theoretical natures, which offer few examples of actual realizations. In this book, we have organized all the subjects required to understand the principles of quantum computation and information processing in a manner suited to physics, mathematics, and engineering courses as early as undergraduate studies.In addition, we provide a supporting package of quantum simulation software from Wolfram Mathematica, specialists in symbolic calculation software. Throughout the book’s main text, demonstrations are provided that use the software package, allowing the students to deepen their understanding of each subject through self-practice. Readers can change the code so as to experiment with their own ideas and contemplate possible applications. The information in this book reflects many years of experience teaching quantum computation and information. The quantum simulation-based demonstrations and the unified organization of the subjects are both time-tested and have received very positive responses from the students who have experienced them.
Algebra --- Mathematical control systems --- Quantum mechanics. Quantumfield theory --- Information systems --- Computer. Automation --- algebra --- lineaire algebra --- quantumfysica --- informatica --- informatietechnologie --- informatietheorie --- Quantum physics. --- Algebras, Linear. --- Data structures (Computer science). --- Information theory. --- Quantum Physics. --- Linear Algebra. --- Data Structures and Information Theory.
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This book constitutes the proceedings of the 21st International Conference on Computer Information Systems and Industrial Management Applications, CISIM 2022, held in Barranquilla, Colombia, in July 2022. The 28 papers presented together with 3 keynotes were carefully reviewed and selected from 68 submissions. The main topics covered by the chapters in this book are biometrics, security systems, multimedia, classification and clustering, and industrial management as well as interesting papers on computer information systems as applied to wireless networks, computer graphics, and intelligent systems.
Computer networks --- Information technology—Management. --- Artificial intelligence. --- Computer engineering. --- Computer networks. --- Computers. --- Software engineering. --- Data structures (Computer science). --- Information theory. --- Computer Application in Administrative Data Processing. --- Artificial Intelligence. --- Computer Engineering and Networks. --- Computing Milieux. --- Software Engineering. --- Data Structures and Information Theory.
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This book constitutes the proceedings of the 8th International Conference on Algorithms and Discrete Applied Mathematics, CALDAM 2022, which was held in Puducherry, India, during February 10-12, 2022. The 24 papers presented in this volume were carefully reviewed and selected from 80 submissions. The papers were organized in topical sections named: graph theory, graph algorithms, computational geometry, algorithms and optimization.
Computer science --- Algorithms --- Mathematics --- Computer science—Mathematics. --- Algorithms. --- Data structures (Computer science). --- Information theory. --- Discrete mathematics. --- Mathematics of Computing. --- Data Structures and Information Theory. --- Discrete Mathematics in Computer Science. --- Discrete mathematical structures --- Mathematical structures, Discrete --- Structures, Discrete mathematical --- Numerical analysis --- Communication theory --- Communication --- Cybernetics --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Electronic data processing --- File organization (Computer science) --- Abstract data types (Computer science) --- Algorism --- Algebra --- Arithmetic --- Foundations
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Teaching quantum computation and information is notoriously difficult, because it requires covering subjects from various fields of science, organizing these subjects consistently in a unified way despite their tendency to favor their specific languages, and overcoming the subjects’ abstract and theoretical natures, which offer few examples of actual realizations. In this book, we have organized all the subjects required to understand the principles of quantum computation and information processing in a manner suited to physics, mathematics, and engineering courses as early as undergraduate studies.In addition, we provide a supporting package of quantum simulation software from Wolfram Mathematica, specialists in symbolic calculation software. Throughout the book’s main text, demonstrations are provided that use the software package, allowing the students to deepen their understanding of each subject through self-practice. Readers can change the code so as to experiment with their own ideas and contemplate possible applications. The information in this book reflects many years of experience teaching quantum computation and information. The quantum simulation-based demonstrations and the unified organization of the subjects are both time-tested and have received very positive responses from the students who have experienced them.
Quantum theory --- Mathematics. --- Data processing. --- Quantum dynamics --- Quantum mechanics --- Quantum physics --- Physics --- Mechanics --- Thermodynamics --- Quantum physics. --- Algebras, Linear. --- Data structures (Computer science). --- Information theory. --- Quantum Physics. --- Linear Algebra. --- Data Structures and Information Theory. --- Communication theory --- Communication --- Cybernetics --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Electronic data processing --- File organization (Computer science) --- Abstract data types (Computer science) --- Linear algebra --- Algebra, Universal --- Generalized spaces --- Mathematical analysis --- Calculus of operations --- Line geometry --- Topology
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This book constitutes the proceedings of the 8th International Conference on Algorithms and Discrete Applied Mathematics, CALDAM 2022, which was held in Puducherry, India, during February 10-12, 2022. The 24 papers presented in this volume were carefully reviewed and selected from 80 submissions. The papers were organized in topical sections named: graph theory, graph algorithms, computational geometry, algorithms and optimization.
Computer science—Mathematics. --- Algorithms. --- Data structures (Computer science). --- Information theory. --- Discrete mathematics. --- Mathematics of Computing. --- Data Structures and Information Theory. --- Discrete Mathematics in Computer Science. --- Discrete mathematical structures --- Mathematical structures, Discrete --- Structures, Discrete mathematical --- Numerical analysis --- Communication theory --- Communication --- Cybernetics --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Electronic data processing --- File organization (Computer science) --- Abstract data types (Computer science) --- Algorism --- Algebra --- Arithmetic --- Foundations --- Algorismes --- Matemàtica discreta --- Matemàtica aplicada
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Chapter(s) “Chapter Name or No.” is/are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Computer science. --- Numerical analysis. --- Computer science—Mathematics. --- Discrete mathematics. --- Image processing—Digital techniques. --- Computer vision. --- Data structures (Computer science). --- Information theory. --- Theory of Computation. --- Numerical Analysis. --- Discrete Mathematics in Computer Science. --- Symbolic and Algebraic Manipulation. --- Computer Imaging, Vision, Pattern Recognition and Graphics. --- Data Structures and Information Theory. --- Discrete mathematical structures --- Mathematical structures, Discrete --- Structures, Discrete mathematical --- Numerical analysis --- Communication theory --- Communication --- Cybernetics --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Electronic data processing --- File organization (Computer science) --- Abstract data types (Computer science) --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Mathematical analysis --- Informatics --- Science --- Computer science --- Mathematics. --- Digital techniques.
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This open access book surveys the progress in addressing selected challenges related to the growth of big data in combination with increasingly complicated hardware. It emerged from a research program established by the German Research Foundation (DFG) as priority program SPP 1736 on Algorithmics for Big Data where researchers from theoretical computer science worked together with application experts in order to tackle problems in domains such as networking, genomics research, and information retrieval. Such domains are unthinkable without substantial hardware and software support, and these systems acquire, process, exchange, and store data at an exponential rate. The chapters of this volume summarize the results of projects realized within the program and survey-related work. This is an open access book.
Computer networks. --- Data structures (Computer science). --- Information theory. --- Computer science—Mathematics. --- Algorithms. --- Computer Communication Networks. --- Data Structures and Information Theory. --- Mathematics of Computing. --- Design and Analysis of Algorithms. --- Algorism --- Algebra --- Arithmetic --- Communication theory --- Communication --- Cybernetics --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Electronic data processing --- File organization (Computer science) --- Abstract data types (Computer science) --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Foundations --- Distributed processing
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This book addresses controversies concerning the epistemological foundations of data science: Is it a genuine science? Or is data science merely some inferior practice that can at best contribute to the scientific enterprise, but cannot stand on its own? The author proposes a coherent conceptual framework with which these questions can be rigorously addressed. Readers will discover a defense of inductivism and consideration of the arguments against it: an epistemology of data science more or less by definition has to be inductivist, given that data science starts with the data. As an alternative to enumerative approaches, the author endorses Federica Russo’s recent call for a variational rationale in inductive methodology. Chapters then address some of the key concepts of an inductivist methodology including causation, probability and analogy, before outlining an inductivist framework. The inductivist framework is shown to be adequate and useful for an analysis of the epistemological foundations of data science. The author points out that many aspects of the variational rationale are present in algorithms commonly used in data science. Introductions to algorithms and brief case studies of successful data science such as machine translation are included. Data science is located with reference to several crucial distinctions regarding different kinds of scientific practices, including between exploratory and theory-driven experimentation, and between phenomenological and theoretical science. Computer scientists, philosophers and data scientists of various disciplines will find this philosophical perspective and conceptual framework of great interest, especially as a starting point for further in-depth analysis of algorithms used in data science. .
Knowledge, Theory of. --- Analysis (Philosophy) --- Mathematical statistics. --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Epistemology --- Theory of knowledge --- Philosophy --- Psychology --- Statistical methods --- Technology --- Data structures (Computer science). --- Information theory. --- System theory. --- Computer science --- Analysis (Philosophy). --- Philosophy of Technology. --- Data Structures and Information Theory. --- Complex Systems. --- Probability and Statistics in Computer Science. --- Analytic Philosophy. --- Philosophy. --- Mathematics. --- Analysis, Linguistic (Philosophy) --- Analysis, Logical --- Analysis, Philosophical --- Analytic philosophy --- Analytical philosophy --- Linguistic analysis (Philosophy) --- Logical analysis --- Philosophical analysis --- Philosophy, Analytical --- Language and languages --- Methodology --- Logical positivism --- Semantics (Philosophy) --- Computer mathematics --- Electronic data processing --- Systems, Theory of --- Systems science --- Science --- Communication theory --- Communication --- Cybernetics --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- File organization (Computer science) --- Abstract data types (Computer science) --- Technology and civilization
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This book constitutes the proceedings of the 15th International Workshop on Frontiers in Algorithmics, FAW 2021, held in conjunction with second International Joint Conference on Theoretical Computer Science (IJTCS 2021), as IJTCS-FAW 2021, in Beijing, China, in August 2021. The conference IJTCS-FAW 2021 was held in hybrid mode due to the COVID-19 pandemic. The 5 full papers presented in this volume were carefully reviewed and selected from 9 submissions. The joint conference provides a focused forum on Algorithmic Game Theory, Blockchain, Multi-agent Reinforcement Learning, Quantum Computation, Theory of Machine Learning, Machine Learning, Formal Method, Algorithm and Complexity, and EconCS.
Computer algorithms. --- Algorithms --- Computer science—Mathematics. --- Discrete mathematics. --- Numerical analysis. --- Data structures (Computer science). --- Information theory. --- Computer engineering. --- Computer networks. --- Software engineering. --- Algorithms. --- Discrete Mathematics in Computer Science. --- Numerical Analysis. --- Data Structures and Information Theory. --- Computer Engineering and Networks. --- Software Engineering. --- Design and Analysis of Algorithms. --- Algorism --- Algebra --- Arithmetic --- Computer software engineering --- Engineering --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Electronic data processing --- Network computers --- Computers --- Communication theory --- Communication --- Cybernetics --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- File organization (Computer science) --- Abstract data types (Computer science) --- Mathematical analysis --- Discrete mathematical structures --- Mathematical structures, Discrete --- Structures, Discrete mathematical --- Numerical analysis --- Foundations --- Distributed processing --- Design and construction --- Computer science --- Mathematics. --- Computer mathematics --- Mathematics
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