This practically-focused study guide introduces the fundamentals of discrete mathematics through an extensive set of classroom-tested problems. Each chapter presents a concise introduction to the relevant theory, followed by a detailed account of common challenges and methods for overcoming these. The reader is then encouraged to practice solving such problems for themselves, by tackling a varied selection of questions and assignments of different levels of complexity. This updated second edition now covers the design and analysis of algorithms using Python, and features more than 50 new problems, complete with solutions. Topics and features: provides a substantial collection of problems and examples of varying levels of difficulty, suitable for both laboratory practical training and self-study; offers detailed solutions to each problem, applying commonly-used methods and computational schemes; introduces the fundamentals of mathematical logic, the theory of algorithms, Boolean algebra, graph theory, sets, relations, functions, and combinatorics; presents more advanced material on the design and analysis of algorithms, including Turing machines, asymptotic analysis, and parallel algorithms; includes reference lists of trigonometric and finite summation formulae in an appendix, together with basic rules for differential and integral calculus. This hands-on workbook is an invaluable resource for undergraduate students of computer science, informatics, and electronic engineering. Suitable for use in a one- or two-semester course on discrete mathematics, the text emphasizes the skills required to develop and implement an algorithm in a specific programming language.

This practically-oriented textbook presents an accessible introduction to discrete mathematics through a substantial collection of classroom-tested exercises. Each chapter opens with concise coverage of the theory underlying the topic, reviewing the basic concepts and establishing the terminology, as well as providing the key formulae and instructions on their use. This is then followed by a detailed account of the most common problems in the area, before the reader is invited to practice solving such problems for themselves through a varied series of questions and assignments. Topics and features: provides an extensive set of exercises and examples of varying levels of complexity, suitable for both laboratory practical training and self-study; offers detailed solutions to many problems, applying commonly-used methods and computational schemes; introduces the fundamentals of mathematical logic, the theory of algorithms, Boolean algebra, graph theory, sets, relations, functions, and combinatorics; presents more advanced material on the design and analysis of algorithms, including asymptotic analysis, and parallel algorithms; includes reference lists of trigonometric and finite summation formulae in an appendix, together with basic rules for differential and integral calculus. This hands-on study guide is designed to address the core needs of undergraduate students training in computer science, informatics, and electronic engineering, emphasizing the skills required to develop and implement an algorithm in a specific programming language.

An authoritative manual on the fundamental principles of discrete mathematics, which is a cornerstone of computer science and information technology, "Fundamentals of Discrete Mathematics" provides readers with a thorough and approachable introduction to the subject. Crafted with lucidity and pedagogical expertise, this book is specifically designed for individuals who are professionals, students, and educators are in search of a comprehensive comprehension of fundamental principles within the discipline. The book commences with a fundamental examination of set theory and logic, establishing the necessary conditions for the subsequent chapters which undertake discrete structures, graph theory, and combinatorics. Practical exercises and real-world illustrations are included to reinforce theoretical knowledge and clearly present each subject. By effectively integrating theoretical rigor and practical applications, this text proves to be an indispensable asset for individuals seeking to cultivate robust problem-solving capabilities. To cater to a wide range of readers, "Fundamentals of Discrete Mathematics" follows a coherent structure that integrates previously covered material to promote a smooth and effective educational journey. This book offers a dependable guide through the intricacies of discrete mathematics, catering to both individuals who are just beginning their exploration of the subject and those who wish to enhance their comprehension. By embracing the challenges that are presented within the pages of this book, one can effectively master the fundamental principles of discrete mathematics.

The purpose of this book is to provide users with an introduction to the basic principles and methods of discrete mathematics, as well as the many applications of these concepts and techniques in a variety of domains. The field of mathematics known as discrete mathematics is a fundamental subfield that focuses on countable structures and processes. On the other hand, discrete mathematics is concerned with things that can be counted or numbered, such as integers, graphs, or sets. This is in contrast to continuous mathematics, which is concerned with notions such as real numbers and continuous functions. Even though it is an abstract field, discrete mathematics has a tremendous number of practical applications in a wide variety of fields, including computer science, operations research, engineering, cryptography, and many more. One of the most important aspects of the book is that it has a strong focus on problem-solving strategies and applications that are applicable in the real world. This makes the book approachable and relevant to students who come from a variety of academic backgrounds. For the purpose of assisting readers in developing a thorough comprehension of the content, it contains a large number of examples, exercises, and applications. This book is written for students who come from a diverse range of backgrounds and have a broad variety of interests. Students will get a strong foundation in discrete mathematics by reading this book, regardless of whether you are studying mathematics, computer science, engineering, or any other area that involves abilities in mathematical reasoning and problem-solving.

This textbook is intended for practical, laboratory sessions associated with the course of quantum computing and quantum algorithms, as well as for self-study. It contains basic theoretical concepts and methods for solving basic types of problems and gives an overview of basic qubit operations, entangled states, quantum circuits, implementing functions, quantum Fourier transform, phase estimation, etc. The book serves as a basis for the application of new information technologies in education and corporate technical training: theoretical material and examples of practical problems, as well as exercises with, in most cases, detailed solutions, have relation to information technologies. A large number of detailed examples serve to better develop professional competencies in computer science.

This book teaches algebra and geometry. The authors dedicate chapters to the key issues of matrices, linear equations, matrix algorithms, vector spaces, lines, planes, second-order curves, and elliptic curves. The text is supported throughout with problems, and the authors have included source code in Python in the book. The book is suitable for advanced undergraduate and graduate students in computer science.

Explore the tools and concepts for Quantum Computing KEY FEATURES ● Offers a diverse range of perspectives from small businesses to multinational conglomerates on the potential of Quantum computing. ● Provides fundamental principles of quantum, optical, and DNA computing and artificial intelligence. ● Collection of hand-picked quantum computing-related frameworks, tools, and utilities for creating new computing spaces. DESCRIPTION Quantum Computing is a hardware, software and technical architectural design paradigm that change traditional computing including Boolean logic with quantum laws and principles at the algorithmic and hardware level. Its use cases and applications can be found in artificial intelligence machine learning, metaverse, cryptography and blockchain technology. This book will help the readers quickly and accurately to understand quantum computing and related technologies by allowing them to make more informed and intelligent business and technical decisions. This book covers almost every aspect of quantum computing from concepts to algorithms to industrial applications. In addition, the book discusses practical guidelines and best practices for quantum computers and related technologies such as artificial intelligence, photonic and DNA computing wherever possible and as needed. This book prepares readers for the future and will assist them in dealing with any challenges associated with quantum computers. If you're interested in writing code, a quick overview of Q#, a quantum programming language, is included in the book's appendix. Almost every chapter contains some quick answers to frequently asked questions, so you can get what you need right away. At the end of each chapter, a textual summary of the chapter and mind maps is provided for the readers, making it possible for them to obtain an overall impression of the ideas presented in a single moment. WHAT YOU WILL LEARN ● Learn the basics of modern computing that includes quantum, optical, and DNA computing, AI and cloud computing. ● Explore strategies for setting up a development environment for quantum computing implementation. ● Acquire knowledge of the frameworks and algorithms used in Quantum Computing, such as Deutch, Shor's, and Grover's. ● Understand the principles and operations of quantum computing. WHO THIS BOOK IS FOR This book is for anyone who is interested in learning more about quantum computing, the various tools available for its implementation, and seeing how to meet the needs of modern businesses. In addition, those already in artificial intelligence, blockchain, or complex computing will find this book very appealing. TABLE OF CONTENTS 1. Tools for Imaginations, Innovation, Technologies, and Creativity 2. Quantum Physics as an Enabler of a Quantum Computer 3. Mathematics of Quantum Computers: The Fundamentals 4. From Bits to Qubits to Qubytes 5. Artificial Intelligence and Associated Technologies: A Review 6. Quantum Algorithms for Everyone …!!! 7. Quantum Machine Learning 8. Quantum Cryptography: The Future of Security 9. The Architecture of a Quantum Computer 10. DNA, Quantum and Photonic Computers 11. Let’s Realize It: Quantum Start-Ups and Giants in Action 12. The Quantum Strategies 13. The Human Side of Quantum Computer Annexure 1: Q# for quantum computation Annexure 2: Python for Quantum computing Annexure 3: Miscellaneous topics: reduction in emissions, global warming, fearless leadership and important facts Annexure 4: References, Notes and Bibliography

The book discusses the fundamentals of high-performance computing. The authors combine visualization, comprehensibility, and strictness in their material presentation, and thus influence the reader towards practical application and learning how to solve real computing problems. They address both key approaches to programming modern computing systems: multithreading-based parallelizing in shared memory systems, and applying message-passing technologies in distributed systems. The book is suitable for undergraduate and graduate students, and for researchers and practitioners engaged with high-performance computing systems. Each chapter begins with a theoretical part, where the relevant terminology is introduced along with the basic theoretical results and methods of parallel programming, and concludes with a list of test questions and problems of varying difficulty. The authors include many solutions and hints, and often sample code.

Math really is for everyone—so let’s prove it. You’ve heard it from kids, from friends, and from celebrities: "I’m bad at math." It’s a line that society tends to accept without examination—after all, some people just aren’t "math people," right? Wrong. As we do with other essential skills, we need to expose the stereotypes, challenge the negative mindsets, and finally confront the systemic opportunity gaps in math education, and replace them with a new vision for what math is, who it’s for, and who can excel at it. In this book you’ll find Research on teacher and student mindsets and their effect on student achievement Audience-specific and differentiated tools, reflection questions, and suggested actions for educators at all levels of the system Examples from popular media, as well as personal stories and anecdotes Quotes, data-driven figures, and suggestions for deeper learning on all aspects of a positive and equitable vision of math education Both social commentary and a toolkit of solutions, this bold new book directly challenges the constructs that have historically dictated our perceptions of what makes someone a "math person". Only by dismantling those misplaced assumptions can we reform math education so it works for everyone. Because in truth, we are all math people.

Parameterized complexity is currently a thriving field in complexity theory and algorithm design. A significant part of the success of the field can be attributed to Michael R. Fellows. This Festschrift has been published in honor of Mike Fellows on the occasion of his 60th birthday. It contains 20 papers that showcase the important scientific contributions of this remarkable man, describes the history of the field of parameterized complexity, and also reflects on other parts of Mike Fellows’s unique and broad range of interests, including his work on the popularization of discrete mathematics for young children. The volume contains several surveys that introduce the reader to the field of parameterized complexity and discuss important notions, results, and developments in this field.