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This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data.

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.

This book highlights recent advances in quantum control technologies with regard to hybrid quantum systems. It addresses the following topics: phonon engineering based on phononic crystals, carbon-based nano materials like graphene and nanotubes, Terahertz light technology for single-molecule and quantum dots, nuclear-spin-based metrology for semiconductor quantum systems, quantum anomalous Hall effect in magnetic topological insulators, chiral three-dimensional photonic crystals, and bio-inspired magnonic systems. Each topic, as a component in the framework of hybrid quantum systems, is concisely presented by experts at the forefront of the field. Accordingly, the book offers a valuable asset, and will help readers find advanced technologies and materials suitable for their purposes.

This book covers recent developments in the understanding, quantification, and exploitation of entanglement in spin chain models from both condensed matter and quantum information perspectives. Spin chain models are at the foundation of condensed matter physics and quantum information technologies and elucidate many fundamental phenomena such as information scrambling, quantum phase transitions, and many-body localization. Moreover, many quantum materials and emerging quantum devices are well described by spin chains. Comprising accessible, self-contained chapters written by leading researchers, this book is essential reading for graduate students and researchers in quantum materials and quantum information.  The coverage is comprehensive, from the fundamental entanglement aspects of quantum criticality, non-equilibrium dynamics, classical and quantum simulation of spin chains through to their experimental realizations, and beyond into machine learning applications.

This book introduces the fundamentals of the theory of quantum computing, illustrated with code samples written in Q#, a quantum-specific programming language, and its related Quantum Development Kit. Quantum computing (QC) is a multidisciplinary field that sits at the intersection of quantum physics, quantum information theory, computer science and mathematics, and which may revolutionize the world of computing and software engineering.  The book begins by covering historical aspects of quantum theory and quantum computing, as well as offers a gentle, algebra-based, introduction to quantum mechanics, specifically focusing on concepts essential for the field of quantum programming. Quantum state description, state evolution, quantum measurement and the Bell's theorem are among the topics covered. The readers also get a tour of the features of Q# and familiarize themselves with the QDK.  Next, the core QC topics are discussed, complete with the necessary mathematical formalism. This includes the notions of qubit, quantum gates and quantum circuits. In addition to that, the book provides a detailed treatment of a series of important concepts from quantum information theory, in particular entanglement and the no-cloning theorem, followed by discussion about quantum key distribution and its various protocols. Finally, the canon of most important QC algorithms and algorithmic techniques is covered in-depth - from the Deutsch-Jozsa algorithm, through Grover's search, to Quantum Fourier Transform, quantum phase estimation and Shor's algorithm.   The book is an accessible introduction into the vibrant and fascinating field of quantum computing, offering a blend of academic diligence with pragmatism that is so central to software development world. All of the discussed theoretical aspects of QC are accompanied by runnable code examples, providing the reader with two different angles - mathematical and programmatic - of looking at the same problem space. 

This text presents an algebraic approach to the construction of several important families of quantum codes derived from classical codes by applying the well-known Calderbank-Shor-Steane (CSS), Hermitian, and Steane enlargement constructions to certain classes of classical codes.

This book presents state-of-the-art research on quantum hybridization, manipulation, and measurement in the context of hybrid quantum systems. It covers a broad range of experimental and theoretical topics relevant to quantum hybridization, manipulation, and measurement technologies, including a magnetic field sensor based on spin qubits in diamond NV centers, coherently coupled superconductor qubits, novel coherent couplings between electron and nuclear spin, photons and phonons, and coherent coupling of atoms and photons. Each topic is concisely described by an expert at the forefront of the field, helping readers quickly catch up on the latest advances in fundamental sciences and technologies of hybrid quantum systems, while also providing an essential overview.

This book presents theoretical methods and experimental results on the study of multipartite quantum correlations in spin-squeezed Bose-Einstein condensates. In particular, we introduce criteria for detecting and characterizing multipartite entanglement, Einstein-Podolsky-Rosen steering, and Bell correlations.

Rising concerns about the security of our data have made quantum cryptography a very active research field in recent years. Quantum cryptographic protocols promise everlasting security by exploiting distinctive quantum properties of nature.

This book describes the experimental and theoretical bases for the development of specifically quantum-mechanical approaches to metrology, imaging, and communication. The particular techniques explored include two-photon interferometry, two-photon optical aberration and dispersion cancellation, lithography, microscopy, and cryptography.

The revised edition of this book offers an extended overview of quantum walks and explains their role in building quantum algorithms, in particular search algorithms.Updated throughout, the book focuses on core topics including Grover's algorithm and the most important quantum walk models, such as the coined, continuous-time, and Szedgedy's quantum walk models. There is a new chapter describing the staggered quantum walk model. The chapter on spatial search algorithms has been rewritten to offer a more comprehensive approach and a new chapter describing the element distinctness algorithm has been added. There is a new appendix on graph theory highlighting the importance of graph theory to quantum walks.As before, the reader will benefit from the pedagogical elements of the book, which include exercises and references to deepen the reader's understanding, and guidelines for the use of computer programs to simulate the evolution of quantum walks.Review of the first edition:"The book is nicely written, the concepts are introduced naturally, and many meaningful connections between them are highlighted. The author proposes a series of exercises that help the reader get some working experience with the presented concepts, facilitating a better understanding. Each chapter ends with a discussion of further references, pointing the reader to major results on the topics presented in the respective chapter." - Florin Manea, zbMATH.

This book presents a distinctive way of understanding quantum correlations beyond entanglement, introducing readers to this less explored yet very fundamental aspect of quantum theory.

This book reviews progress towards quantum simulators based on photonic and hybrid light-matter systems, covering theoretical proposals and recent experimental work. Quantum simulators are specially designed quantum computers. Their main aim is to simulate and understand complex and inaccessible quantum many-body phenomena found or predicted in condensed matter physics, materials science and exotic quantum field theories. Applications will include the engineering of smart materials, robust optical or electronic circuits, deciphering quantum chemistry and even the design of drugs.Technological developments in the fields of interfacing light and matter, especially in many-body quantum optics, have motivated recent proposals for quantum simulators based on strongly correlated photons and polaritons generated in hybrid light-matter systems. The latter have complementary strengths to cold atom and ion based simulators and they can probe for example out of equilibrium phenomena in a natural driven-dissipative setting. This book covers some of the most important works in this area reviewing the proposal for Mott transitions and Luttinger liquid physics with light, to simulating interacting relativistic theories, topological insulators and gauge field physics. The stage of the field now is at a point where on top of the numerous theory proposals; experiments are also reported.Connecting to the theory proposals presented in the chapters, the main experimental quantum technology platforms developed from groups worldwide to realize photonic and polaritonic simulators in the laboratory are also discussed. These include coupled microwave resonator arrays in superconducting circuits, semiconductor based polariton systems, and integrated quantum photonic chips.This is the first book dedicated to photonic approaches to quantum simulation, reviewing the fundamentals for the researcher new to the field, and providing a complete reference for the graduate student starting or already undergoing PhD studies in this area.

This book presents the basics and applications of superconducting devices in quantum optics. Superconducting detectors provide unparalleled performance for the detection of infrared photons in quantum cryptography, enable fundamental advances in quantum optics, and provide a direct route to on-chip optical quantum information processing.

This book approaches condensed matter physics from the perspective of quantum information science, focusing on systems with strong interaction and unconventional order for which the usual condensed matter methods like the Landau paradigm or the free fermion framework break down.

This book provides an overview of state-of-the-art implementations of quantum random number generators (QRNGs), and especially examines their relation to classical statistical randomness models and numerical techniques for computing random numbers.

During the last few years cavity-optomechanics has emerged as a new field of research. It is valuable to researchers in nano science, quantum optics, quantum information, gravitational wave detection and other cutting edge fields.

During the last few years cavity-optomechanics has emerged as a new field of research. It is valuable to researchers in nano science, quantum optics, quantum information, gravitational wave detection and other cutting edge fields.

In light of recent explorations of their non-intuitive dynamics, this book presents proposals as well as actual experiments on how quantum walks can be implemented in the laboratory, underpinned by a range of quantum, classical and hybrid technologies.

This book explores quantum walks, which are important in building quantum algorithms. Coverage includes Grover's algorithm; Analytical solutions of quantum walks using Fourier transforms; Quantum walks on generic graphs; Spatial search algorithms and more.

Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making.