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Quantum Computing for the Brain argues that the brain is the killer
application for quantum computing. No other system is as complex,
as multidimensional in time and space, as dynamic, as less
well-understood, as of peak interest, and as in need of
three-dimensional modeling as it functions in real-life, as the
brain.Quantum computing has emerged as a platform suited to
contemporary data processing needs, surpassing classical computing
and supercomputing. This book shows how quantum computing's
increased capacity to model classical data with quantum states and
the ability to run more complex permutations of problems can be
employed in neuroscience applications such as neural signaling and
synaptic integration. State-of-the-art methods are discussed such
as quantum machine learning, tensor networks, Born machines,
quantum kernel learning, wavelet transforms, Rydberg atom arrays,
ion traps, boson sampling, graph-theoretic models, quantum optical
machine learning, neuromorphic architectures, spiking neural
networks, quantum teleportation, and quantum walks.Quantum
Computing for the Brain is a comprehensive one-stop resource for an
improved understanding of the converging research frontiers of
foundational physics, information theory, and neuroscience in the
context of quantum computing.
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.
This practical introduction explains the field of Blockchain
Economics, the economic models emerging with the implementation of
distributed ledger technology. These models are characterized by
three factors: open platform business models, cryptotoken money
supplies, and Initial Coin Offerings as a new and official form of
financing. The book covers a variety of approaches from a business
and academic perspective, ranging from financial theory,
complexity, and open innovation networks to behavioral economics,
self-determination theory, public policy, and financial
inclusion.Unlike existing titles, this book draws on worldwide
blockchain industry experts to define the new discipline of
Blockchain Economics and provide novel theoretical and conceptual
resources for the future of this fast-developing economy. The
primer also highlights the wider theme of blockchain as an
institutional technology, in that many value transfer interactions
might be shifted to automated networks, decreasing the number of
human-operated institutions.As well as stimulating further
research, and implementation by business innovators and public
policy strategists, the book can also be used as a foundational
textbook in courses on Blockchain Economics.
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Michael Buble
CD
(1)
R172
R154
Discovery Miles 1 540
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