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...
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ISBN:
(数字)9781484242186
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,;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.;Developers and programmers interested in this new field of computing.
Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introdu...
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ISBN:
(数字)9783031015434
ISBN:
(纸本)9783031004155
Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introduction to the subject, covering the theoretical foundations as well as more recent developments in a coherent and readable manner. The text is centered on the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under uncertainty. Chapter 3 is a brief introduction to game theory, explaining classical concepts like Nash equilibrium. Chapter 4 deals with the fundamental problem of coordinating a team of collaborative agents. Chapter 5 studies the problem of multiagent reasoning and decision making under partial observability. Chapter 6 focuses on the design of protocols that are stable against manipulations by self-interested agents. Chapter 7 provides a short introduction to the rapidly expanding field of multiagent reinforcement learning. The material can be used for teaching a half-semester course on multiagent systems covering, roughly, one chapter per lecture.
This volume compiles selected papers focusing on the applications of differential equations across various scientific domains, presented at the International Conference "New Trends in the Applications of Differen...
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ISBN:
(数字)9783031833984
ISBN:
(纸本)9783031833977;9783031834004
This volume compiles selected papers focusing on the applications of differential equations across various scientific domains, presented at the International Conference "New Trends in the Applications of Differential Equations in Sciences" (NTADES), which took place in Saints Constantine and Helena, Bulgaria, in July 2024.
The book is organized around several key themes, including applications in mathematical physics, mathematical biology, financial mathematics, fractional analysis, numerical methods, and neuroscience. The covered applications encompass diverse topics such as mechanics, neuralnetworks in insurance, credit portfolios, predator-prey systems with fractional derivatives, recent findings regarding COVID-19 epidemic waves, memristive cellular nonlinear networks, and more.
By promoting fundamental research in mathematics, this book aims to develop new methods and techniques that can effectively address real-life challenges through the application of differential equations.
This handbook gathers together the state of the art on mathematicalmodels and algorithms for imaging and vision. Its emphasis lies on rigorous mathematical methods, which represent the optimal sol...
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ISBN:
(数字)9783030030094
This handbook gathers together the state of the art on mathematicalmodels and algorithms for imaging and vision. Its emphasis lies on rigorous mathematical methods, which represent the optimal solutions to a class of imaging and vision problems, and on effective algorithms, which are necessary for the methods to be translated to practical use in various applications. Viewing discrete images as data sampled from functional surfaces enables the use of advanced tools from calculus, functions and calculus of variations, and nonlinear optimization, and provides the basis of high-resolution imaging through geometry and variational models. Besides, optimization naturally connects traditional model-driven approaches to the emerging data-driven approaches of machine and deep learning. No other framework can provide comparable accuracy and precision to imaging and vision.
Written by leading researchers in imaging and vision, the chapters in this handbook all start with gentle introductions, which make this work accessible to graduate students. For newcomers to the field, the book provides a comprehensive and fast-track introduction to the content, to save time and get on with tackling new and emerging challenges. For researchers, exposure to the state of the art of research works leads to an overall view of the entire field so as to guide new research directions and avoid pitfalls in moving the field forward and looking into the next decades of imaging and information services. This work can greatly benefit graduate students, researchers, and practitioners in imaging and vision; applied mathematicians; medical imagers; engineers; and computer scientists.
This book delves into a wide array of topics, ranging from memristor and its emulator to chaotic circuits based on memristor, memristor-based en/decryption systems, filter design based on memristive family, memristive...
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ISBN:
(数字)9789819603329
ISBN:
(纸本)9789819603312;9789819603343
This book delves into a wide array of topics, ranging from memristor and its emulator to chaotic circuits based on memristor, memristor-based en/decryption systems, filter design based on memristive family, memristive filter for signal processing, memristor network-based swarm intelligence, dynamic analysis of memristive neuralnetworks, and the application of memristor-based neuralnetworks. It provides a comprehensive and systematic exploration of how memristors empower and drive cutting-edge research in neuromorphic computing and artificial intelligence. This book encourages fostering interdisciplinary information literacy and cultivating cross-disciplinary computational thinking. This book plays a pivotal role in embracing and advancing the development of neuromorphic computing. Through profound foundational theories and academic analysis methods, this book guides artificial intelligence graduate students and engineering professionals in constructing a comprehensive knowledge and technological framework for memristor research.
This book describes a novel methodology for studying algorithmic skills, intended as cognitive activities related to rule-based symbolic transformation, and argues that some human computational abilities may be interp...
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ISBN:
(数字)9783319518411
ISBN:
(纸本)9783319518411
This book describes a novel methodology for studying algorithmic skills, intended as cognitive activities related to rule-based symbolic transformation, and argues that some human computational abilities may be interpreted and analyzed as genuine examples of extended cognition. It shows that the performance of these abilities relies not only on innate neurocognitive systems or language-related skills, but also on external tools and general agentenvironment interactions. Further, it asserts that a low-level analysis, based on a set of core neurocognitive systems linking numbers and language, is not sufficient to explain some specific forms of high-level numerical skills, like those involved in algorithm execution. To this end, it reports on the design of a cognitive architecture for modeling all the relevant features involved in the execution of algorithmic strategies, including external tools, such as paper and pencils. The first part of the book discusses the philosophical premises for endorsing and justifying a position in philosophy of mind that links a modified form of computationalism with some recent theoretical and scientific developments, like those introduced by the so-called dynamical approach to cognition. The second part is dedicated to the description of a Turing-machine-inspired cognitive architecture, expressly designed to formalize all kinds of algorithmic strategies.
This book presents the latest research in computational methods for modeling and simulating brain disorders. In particular, it shows how mathematicalmodels can be used to study the relationship between a given disord...
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ISBN:
(数字)9783319499598
ISBN:
(纸本)9783319499581
This book presents the latest research in computational methods for modeling and simulating brain disorders. In particular, it shows how mathematicalmodels can be used to study the relationship between a given disorder and the specific brain structure associated with that disorder. It also describes the emerging field of computational psychiatry, including the study of pathological behavior due to impaired functional connectivity, pathophysiological activity, and/or aberrant decision-making. Further, it discusses the data analysis techniques that will be required to analyze the increasing amount of data being generated about the brain. Lastly, the book offers some tips on the application of computational models in the field of quantitative systems pharmacology. Mainly written for computational scientists eager to discover new application fields for their model, this book also benefits neurologists and psychiatrists wanting to learn about new methods.
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