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Write algorithms and program in the new field of quantum computing. This book covers major topics such as the physical components of a quantum computer: qubits, entanglement, logic gates, circuits, and how they differ from a traditional computer. Also, Practical Quantum Computing for Developers discusses quantum computing in the cloud using IBM Q Experience including: the composer, quantum scores, experiments, circuits, simulators, real quantum devices, and more. You’ll be able to run experiments in the cloud on a real quantum device. Furthermore, this book shows you how to do quantum programming using the QISKit (Quantum Information Software Kit), Python SDK, and other APIs such as QASM (Quantum Assembly). You’ll learn to write code using these languages and execute it against simulators (local or remote) or a real quantum computer provided by IBM’s Q Experience. Finally, you’ll learn the current quantum algorithms for entanglement, random number generation, linear search, integer factorization, and others. You’ll peak inside the inner workings of the Bell states for entanglement, Grover’s algorithm for linear search, Shor’s algorithm for integer factorization, and other algorithms in the fields of optimization, and more. Along the way you’ll also cover game theory with the Magic Square, an example of quantum pseudo-telepathy where parties sharing entangled states can be observed to have some kind of communication between them. In this game Alice and Bob play against a referee. Quantum mechanics allows Alice and Bob to always win! By the end of this book, you will understand how this emerging technology provides massive parallelism and significant computational speedups over classical computers, and will be prepared to program quantum computers which are expected to replace traditional computers in the data center. You will: Use the Q Experience Composer, the first-of-its-kind web console to create visual programs/experiments and submit them to a quantum simulator or real device on the cloud Run programs remotely using the Q Experience REST API Write algorithms that provide superior performance over their classical counterparts Build a Node.js REST client for authenticating, listing remote devices, querying information about quantum processors, and listing or running experiments remotely in the cloud Create a quantum number generator: The quintessential coin flip with a quantum twist Discover quantum teleportation: This algorithm demonstrates how the exact state of a qubit (quantum information) can be transmitted from one location to another, with the help of classical communication and quantum entanglement between the sender and receiver Peek into single qubit operations with the classic game of Battleships with a quantum twist Handle the counterfeit coin problem: a classic puzzle that consists of finding a counterfeit coin in a beam balance among eight coins in only two turns.

Mathematics --- Computer science --- Programming --- Information systems --- Computer. Automation --- quantumcomputers --- Python (informatica) --- cloud computing --- computers --- programmeertalen --- wiskunde --- gegevensanalyse --- computerkunde --- Programming languages (Electronic computers). --- Neural networks (Computer science) . --- Quantum computers. --- Big data. --- Python (Computer program language) --- Programming Languages, Compilers, Interpreters. --- Mathematical Models of Cognitive Processes and Neural Networks. --- Quantum Computing. --- Big Data. --- Python.

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This monograph concisely but thoroughly introduces the reader to the field of mathematical immunology. The book covers first basic principles of formulating a mathematical model, and an outline on data-driven parameter estimation and model selection. The authors then introduce the modeling of experimental and human infections and provide the reader with helpful exercises. The target audience primarily comprises researchers and graduate students in the field of mathematical biology who wish to be concisely introduced into mathematical immunology. .

Mathematics. --- Immunology. --- Biomedical engineering. --- Neural networks (Computer science). --- Biomathematics. --- Statistics. --- Physiological, Cellular and Medical Topics. --- Biomedical Engineering/Biotechnology. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Mathematical Models of Cognitive Processes and Neural Networks. --- Virus diseases --- Molecular diagnosis. --- Viral diseases --- Viral infections --- Virus infections --- Communicable diseases --- Medical virology --- Pathogenic viruses --- Physiology --- Immunobiology --- Life sciences --- Serology --- Animal physiology --- Animals --- Biology --- Anatomy --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Clinical engineering --- Medical engineering --- Bioengineering --- Biophysics --- Engineering --- Medicine --- Statistics . --- Neural networks (Computer science) . --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing

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Contributions in this volume focus on computationally efficient algorithms and rigorous mathematical theories for analyzing large-scale networks. Researchers and students in mathematics, economics, statistics, computer science and engineering will find this collection a valuable resource filled with the latest research in network analysis. Computational aspects and applications of large-scale networks in market models, neural networks, social networks, power transmission grids, maximum clique problem, telecommunication networks, and complexity graphs are included with new tools for efficient network analysis of large-scale networks. This proceeding is a result of the 7th International Conference in Network Analysis, held at the Higher School of Economics, Nizhny Novgorod in June 2017. The conference brought together scientists, engineers, and researchers from academia, industry, and government.

Network analysis (Planning) --- Project networks --- Planning --- Combinatorics. --- Distribution (Probability theory. --- Operations Research, Management Science. --- Mathematical Models of Cognitive Processes and Neural Networks. --- Probability Theory and Stochastic Processes. --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Combinatorics --- Algebra --- Mathematical analysis --- Operations research. --- Management science. --- Neural networks (Computer science) . --- Probabilities. --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing --- Quantitative business analysis --- Management --- Problem solving --- Operations research --- Statistical decision --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory

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Write algorithms and program in the new field of quantum computing. This book covers major topics such as the physical components of a quantum computer: qubits, entanglement, logic gates, circuits, and how they differ from a traditional computer. Also, Practical Quantum Computing for Developers discusses quantum computing in the cloud using IBM Q Experience including: the composer, quantum scores, experiments, circuits, simulators, real quantum devices, and more. You’ll be able to run experiments in the cloud on a real quantum device. Furthermore, this book shows you how to do quantum programming using the QISKit (Quantum Information Software Kit), Python SDK, and other APIs such as QASM (Quantum Assembly). You’ll learn to write code using these languages and execute it against simulators (local or remote) or a real quantum computer provided by IBM’s Q Experience. Finally, you’ll learn the current quantum algorithms for entanglement, random number generation, linear search, integer factorization, and others. You’ll peak inside the inner workings of the Bell states for entanglement, Grover’s algorithm for linear search, Shor’s algorithm for integer factorization, and other algorithms in the fields of optimization, and more. Along the way you’ll also cover game theory with the Magic Square, an example of quantum pseudo-telepathy where parties sharing entangled states can be observed to have some kind of communication between them. In this game Alice and Bob play against a referee. Quantum mechanics allows Alice and Bob to always win! By the end of this book, you will understand how this emerging technology provides massive parallelism and significant computational speedups over classical computers, and will be prepared to program quantum computers which are expected to replace traditional computers in the data center. You will: Use the Q Experience Composer, the first-of-its-kind web console to create visual programs/experiments and submit them to a quantum simulator or real device on the cloud Run programs remotely using the Q Experience REST API Write algorithms that provide superior performance over their classical counterparts Build a Node.js REST client for authenticating, listing remote devices, querying information about quantum processors, and listing or running experiments remotely in the cloud Create a quantum number generator: The quintessential coin flip with a quantum twist Discover quantum teleportation: This algorithm demonstrates how the exact state of a qubit (quantum information) can be transmitted from one location to another, with the help of classical communication and quantum entanglement between the sender and receiver Peek into single qubit operations with the classic game of Battleships with a quantum twist Handle the counterfeit coin problem: a classic puzzle that consists of finding a counterfeit coin in a beam balance among eight coins in only two turns.

Quantum computing. --- Computation, Quantum --- Computing, Quantum --- Information processing, Quantum --- Quantum computation --- Quantum information processing --- Electronic data processing --- Computer science. --- Big data. --- Python (Computer program language). --- Programming Languages, Compilers, Interpreters. --- Mathematical Models of Cognitive Processes and Neural Networks. --- Quantum Computing. --- Big Data. --- Python. --- Scripting languages (Computer science) --- Data sets, Large --- Large data sets --- Data sets --- Informatics --- Science --- Programming languages (Electronic computers). --- Neural networks (Computer science) . --- Quantum computers. --- Computers --- Computer languages --- Computer program languages --- Computer programming languages --- Machine language --- Languages, Artificial --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence --- Natural computation --- Soft computing

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Focused on solving competition-based problems, this book designs, proposes, develops, analyzes and simulates various neural network models depicted in centralized and distributed manners. Specifically, it defines four different classes of centralized models for investigating the resultant competition in a group of multiple agents. With regard to distributed competition with limited communication among agents, the book presents the first distributed WTA (Winners Take All) protocol, which it subsequently extends to the distributed coordination control of multiple robots. Illustrations, tables, and various simulative examples, as well as a healthy mix of plain and professional language, are used to explain the concepts and complex principles involved. Thus, the book provides readers in neurocomputing and robotics with a deeper understanding of the neural network approach to competition-based problem-solving, offers them an accessible introduction to modeling technology and the distributed coordination control of redundant robots, and equips them to use these technologies and approaches to solve concrete scientific and engineering problems.

Neural networks (Computer science) --- Robotics. --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Engineering. --- Artificial intelligence. --- Neural networks (Computer science). --- Computational intelligence. --- Automation. --- Computational Intelligence. --- Robotics and Automation. --- Artificial Intelligence (incl. Robotics). --- Mathematical Models of Cognitive Processes and Neural Networks. --- Automation --- Machine theory --- Automatic factories --- Automatic production --- Computer control --- Engineering cybernetics --- Factories --- Industrial engineering --- Mechanization --- Assembly-line methods --- Automatic control --- Automatic machinery --- CAD/CAM systems --- Robotics --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Natural computation --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Artificial Intelligence. --- Neural networks (Computer science) . --- Control engineering. --- Control, Robotics, Automation. --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Programmable controllers