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This volume presents papers on the topics covered at the National Academy of Engineering's 2018 US Frontiers of Engineering Symposium. Every year the symposium brings together 100 outstanding young leaders in engineering to share their cutting-edge research and innovations in selected areas. The 2018 symposium was held September 5-7 and hosted by MIT Lincoln Laboratory in Lexington, Massachusetts. The intent of this book is to convey the excitement of this unique meeting and to highlight innovative developments in engineering research and technical work.
Quantum mechanics, the subfield of physics that describes the behavior of very small (quantum) particles, provides the basis for a new paradigm of computing. First proposed in the 1980s as a way to improve computational modeling of quantum systems, the field of quantum computing has recently garnered significant attention due to progress in building small-scale devices. However, significant technical advances will be required before a large-scale, practical quantum computer can be achieved. Quantum Computing: Progress and Prospects provides an introduction to the field, including the unique characteristics and constraints of the technology, and assesses the feasibility and implications of creating a functional quantum computer capable of addressing real-world problems. This report considers hardware and software requirements, quantum algorithms, drivers of advances in quantum computing and quantum devices, benchmarks associated with relevant use cases, the time and resources required, and how to assess the probability of success.
"Combinatorial Optimization Problems: Quantum Computing" is an introductory guide that bridges the gap between combinatorial optimization and quantum computing for absolute beginners. This book unpacks fundamental concepts in optimization and explores how quantum computing can revolutionize the way we approach complex problems. Through clear explanations and relatable examples, readers will gain an understanding of both fields without needing any prior knowledge of quantum mechanics or advanced mathematics. Ideal for those curious about the future of technology, this book serves as a stepping stone into the fascinating world of quantum algorithms and their applications in optimization.
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"Quantum Computing" is a comprehensive and accessible exploration of one of the most exciting and rapidly evolving fields in modern science. Written with both beginners and advanced enthusiasts in mind, this book offers a captivating journey through the world of quantum computing without the need for complex mathematical formulas. With 50 engaging chapters covering a wide range of topics, readers will discover the fascinating principles behind quantum mechanics and how they are harnessed to revolutionize computing, cryptography, telecommunications, and even our understanding of consciousness and the universe itself. From the basics of qubits and superposition to advanced applications like quantum cryptography and artificial intelligence, this book presents complex concepts in a clear and easy-to-understand manner, making it suitable for readers of all backgrounds. Whether you're a curious novice or a seasoned quantum enthusiast, "Quantum Computing" offers a captivating glimpse into the extraordinary possibilities of the quantum world.
This book targets computer scientists and engineers who are familiar with concepts in classical computer systems but are curious to learn the general architecture of quantum computing systems. It gives a concise presentation of this new paradigm of computing from a computer systems' point of view without assuming any background in quantum mechanics. As such, it is divided into two parts. The first part of the book provides a gentle overview on the fundamental principles of the quantum theory and their implications for computing. The second part is devoted to state-of-the-art research in designing practical quantum programs, building a scalable software systems stack, and controlling quantum hardware components. Most chapters end with a summary and an outlook for future directions. This book celebrates the remarkable progress that scientists across disciplines have made in the past decades and reveals what roles computer scientists and engineers can play to enable practical-scale quantum computing.
Generative AI: Quantum Computing Methods explores the innovative convergence of generative artificial intelligence and quantum computing. This book provides a comprehensive overview of how quantum computing techniques can enhance generative models in AI, offering insights into their applications and potential impacts across various domains. With a focus on bridging theoretical foundations and practical implementations, it serves as a vital resource for researchers and practitioners eager to understand and leverage the transformative possibilities at the intersection of these cutting-edge technologies.
"From Schrödinger's Equation to Deep Learning: A Quantum Approach" offers a captivating exploration that bridges the realms of quantum mechanics and deep learning. Tailored for scientists, researchers, and enthusiasts in both quantum physics and artificial intelligence, this book delves into the symbiotic relationship between quantum principles and cutting-edge deep learning techniques. Covering topics such as quantum-inspired algorithms, neural networks, and computational advancements, the book provides a comprehensive overview of how quantum approaches enrich and influence the field of deep learning. With clarity and depth, it serves as an enlightening resource for those intrigued by the dynamic synergy between quantum mechanics and the transformative potential of deep learning.
In the swiftly evolving realm of technology, the challenge of classical computing's constraints in handling intricate problems has become pronounced. While classical computers excel in many areas, they struggle with complex issues in cryptography, optimization, and molecular simulation. Addressing these escalating challenges requires a disruptive solution to push the boundaries of computation and innovation. Principles and Applications of Quantum Computing Using Essential Math, authored by A. Daniel, M. Arvindhan, Kiranmai Bellam, and N. Krishnaraj. This guide pioneers the transformative potential of quantum computing by seamlessly blending rigorous mathematics with quantum theory. It equips scholars, researchers, and aspiring technologists with insights to grasp and harness quantum computing's capabilities. By delving into quantum gates, algorithms, and error correction techniques, the book demystifies quantum computing, inviting exploration of quantum machine learning, cryptography, and the dynamic interplay between classical and quantum computing. As the quantum landscape expands, this book acts as a vital companion, navigating readers through the converging realms of industry, academia, and innovation. Principles and Applications of Quantum Computing Using Essential Math arrives as a timely answer to the limitations of classical computing, providing scholars with an essential roadmap to navigate the quantum technology landscape. With its clear explanations, practical applications, and forward-looking perspectives, this book serves as an indispensable tool for unraveling quantum computing's mysteries and driving innovation into uncharted domains.