QUANTUM COMPUTING: PHYSICS, BLOCKCHAINS, AND DEEP LEARNING SMART NETWORKS (Between Science and Economics)

Melanie Swan; Frank Witte; Renato P Dos Santos

ISBN 10: 1786348209 / ISBN 13: 9781786348203

Published by World Scientific Publishing Europe Ltd, 2020

About this Item

This is a pre-loved book that shows moderate signs of wear from previous reading. You may notice creases, edge wear, or a cracked spine, but it remains in solid, readable condition.Please note:-May include library or rental stickers, stamps, or markings.-Supplemental materials e.g., CDs, access codes, inserts are not guaranteed.-Box sets may not come with the original outer box. If it does, the box will not be in perfect condition. -Sourced from donation centers; authenticity not verified with publisher. Your satisfaction is our top priority! If you have any questions or concerns about your order, please donā t hesitate to reach out. Thank you for shopping with us and supporting small businessā happy reading!

Seller Inventory # STM.CSY

Bibliographic Details

• Title: QUANTUM COMPUTING: PHYSICS, BLOCKCHAINS, AND DEEP LEARNING SMART NETWORKS (Between Science and Economics)
• Publisher: World Scientific Publishing Europe Ltd
• Publication Date: 2020
• Language: English
• ISBN 10: 1786348209
• ISBN 13: 9781786348203
• Binding: Hardcover
• Condition: good

About this title

Synopsis

Quantum information and contemporary smart network domains are so large and complex as to be beyond the reach of current research approaches. Hence, new theories are needed for their understanding and control. Physics is implicated as smart networks are physical systems comprised of particle-many items interacting and reaching criticality and emergence across volumes of macroscopic and microscopic states. Methods are integrated from statistical physics, information theory, and computer science. Statistical neural field theory and the AdS/CFT correspondence are employed to derive a smart network field theory (SNFT) and a smart network quantum field theory (SNQFT) for the orchestration of smart network systems. Specifically, a smart network field theory (conventional or quantum) is a field theory for the organization of particle-many systems from a characterization, control, criticality, and novelty emergence perspective. This book provides insight as to how quantum information science as a paradigm shift in computing may influence other high-impact digital transformation technologies, such as blockchain and machine learning. Smart networks refer to the idea that the internet is no longer simply a communications network, but rather a computing platform. The trajectory is that of communications networks becoming computing networks (with self-executing code), and perhaps ultimately quantum computing networks. Smart network technologies are conceived as autonomous self-operating computing networks. This includes blockchain economies, deep learning neural networks, autonomous supply chains, self-piloting driving fleets, unmanned aerial vehicles, industrial robotics cloudminds, real-time bidding for advertising, high-frequency trading networks, smart city IoT sensors, and the quantum internet.

Readership: Thought-leaders, executives, industry strategists, research scientists, graduate students, advanced undergraduate students, policy-makers, government regulators, corporate practitioners, and entrepreneurs in the areas of computer science, blockchain, machine learning, quantum information science, and theoretical physics.