Description: Further DetailsTitle: Quantum Machine LearningCondition: NewSubtitle: Thinking and Exploration in Neural Network Models for Quantum Science and Quantum ComputingEAN: 9783031442254ISBN: 9783031442254Edition: 1st ed. 2024Publisher: Springer International Publishing AGFormat: HardbackRelease Date: 01/03/2024Description: This book presents a new way of thinking about quantum mechanics and machine learning by merging the two. Quantum mechanics and machine learning may seem theoretically disparate, but their link becomes clear through the density matrix operator which can be readily approximated by neural network models, permitting a formulation of quantum physics in which physical observables can be computed via neural networks. As well as demonstrating the natural affinity of quantum physics and machine learning, this viewpoint opens rich possibilities in terms of computation, efficient hardware, and scalability. One can also obtain trainable models to optimize applications and fine-tune theories, such as approximation of the ground state in many body systems, and boosting quantum circuits’ performance. The book begins with the introduction of programming tools and basic concepts of machine learning, with necessary background material from quantum mechanics and quantum information also provided. This enables the basic building blocks, neural network models for vacuum states, to be introduced. The highlights that follow include: non-classical state representations, with squeezers and beam splitters used to implement the primary layers for quantum computing; boson sampling with neural network models; an overview of available quantum computing platforms, their models, and their programming; and neural network models as a variational ansatz for many-body Hamiltonian ground states with applications to Ising machines and solitons. The book emphasizes coding, with many open source examples in Python and TensorFlow, while MATLAB and Mathematica routines clarify and validate proofs. This book is essential reading for graduate students and researchers who want to develop both the requisite physics and coding knowledge to understand the rich interplay of quantum mechanics and machine learning.Language: EnglishCountry/Region of Manufacture: CHItem Height: 235mmItem Length: 155mmAuthor: Claudio ContiGenre: Science Nature & MathBook Series: Quantum Science and TechnologyTopic: Computing & InternetRelease Year: 2024 Missing Information?Please contact us if any details are missing and where possible we will add the information to our listing.
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Publication Name: Quantum Machine Learning
Title: Quantum Machine Learning
Subtitle: Thinking and Exploration in Neural Network Models for Quantum Sci
EAN: 9783031442254
ISBN: 9783031442254
Edition: 1st ed. 2024
Release Date: 01/03/2024
Release Year: 2024
Country/Region of Manufacture: CH
Item Height: 235mm
Series: Quantum Science and Technology
Book Title: Quantum Machine Learning : Thinking and Exploration in Neural Network Models for Quantum Science and Quantum Computing
Number of Pages: Xxiii, 378 Pages
Language: English
Publisher: Springer International Publishing A&G
Topic: Physics / Quantum Theory, Probability & Statistics / General, Intelligence (Ai) & Semantics, General
Publication Year: 2024
Illustrator: Yes
Genre: Mathematics, Computers, Science
Item Weight: 27.2 Oz
Item Length: 9.3 in
Author: Claudio Conti
Item Width: 6.1 in
Book Series: Quantum Science and Technology Ser.
Format: Hardcover