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Modelling Non-Markovian Quantum Systems Using Tensor Networks

represent the dynamics of general open quantum systems as tensor networks, a result which has connections with the Feynman operator calculus and;

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Modelling Non-Markovian Quantum Systems Using Tensor Networks

represent the dynamics of general open quantum systems as tensor networks, a result which has connections with the Feynman operator calculus and;

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Engineering Quantum Mechanics

non-Markovian relaxation using the quantum statistical reduced-density operator formalism. Example programs based on Fortran 77 are provided;

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Open Quantum Systems: An Introduction

Markovian and non-Markovian evolutions, is also discussed. Because of the step-by-step explanations, this work is a useful reference to novices;

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Evolution Equations

dynamical systems in Markovian and non-Markovian settings using evolution equations; Einstein's evolution equation for fluid with exponential free;

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Quantum Noise

of quantum optics. It includes new treatments of photodetection, quantum amplifier theory, non-Markovian quantum stochastic processes, quantum input;

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Quantum Noise

of quantum optics. It includes new treatments of photodetection, quantum amplifier theory, non-Markovian quantum stochastic processes, quantum input;

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Neural-Network Simulation of Strongly Correlated Quantum Systems

of quantum simulations by means of neuromorphic hardware, for using quantum physics as an input to classical neural nets and, in turn, for using;

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Neural-Network Simulation of Strongly Correlated Quantum Systems

of quantum simulations by means of neuromorphic hardware, for using quantum physics as an input to classical neural nets and, in turn, for using;

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Performance Analysis Of Communication Systems

in performance evaluation with non-Markovian stochastic petri nets, this volume takes a systematic approach with clear presentation. Each definition;

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Tensor Network Contractions

understand the main parts of the book. This book is a good source for non-specialists on quantum physics to understand tensor network algorithms and;

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Stability Analysis of Markovian Jump Systems

This book focuses on the stability analysis of Markovian jump systems (MJSs) with various settings and discusses its applications;

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Analysis and Modelling of Non-Steady Flow in Pipe and Channel Networks

solving non-steady pipe flow using the finite element method. The program also covers flows in channels. The book presents the numerical core;

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Tensor Computation for Data Analysis

, quantum physics, quantum chemistry, etc. The discussion begins with basic coverage of notations, preliminary operations in tensor;

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Theoretical Foundations of Quantum Information Processing and Communication

probabilities, open systems, and non-Markovian dynamics and decoherence. It also addresses quantum information and relativity as well as testing quantum;

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Tensor Numerical Methods in Quantum Chemistry

cannot be eliminated by using parallel architectures and high performance computing. The novel tensor numerical methods are based on a smart;

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Modelling Biological Systems

using computational and mathematical techniques. This book elucidates the concepts and innovative methods around prospective developments with;

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Quantum Information Meets Quantum Matter

. Concepts and tools in quantum information science such as entanglement, quantum circuits, and the tensor network representation prove to be highly;

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Image Textures and Gibbs Random Fields

framework to the images. This approach results in more general Gibbs models than can be either Markovian or non-Markovian and possess arbitrary;

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Quantum Networking

Quantum networks build on entanglement and quantum measurement to achieve tasks that are beyond the reach of classical systems. Using;

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Networks & Quantum Computing

This book presents and discusses research in the field of computer science, with a particular focus on network systems and quantum;

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Open Quantum Systems

This book presents four survey articles on various aspects of open quantum systems, specifically addressing quantum Markovian processes;

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Introduction to Tensor Network Methods

be able to write a tensor network program and can begin to explore the physics of many-body quantum systems. The book can also serve as a;

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Quantum Field Theory of Non-equilibrium States

quantum field theoretical applications to systems out of equilibrium. It introduces the real-time approach to non-equilibrium statistical;

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Quantum Field Theory of Non-equilibrium States

presents quantum field theoretical applications to systems out of equilibrium. It introduces the real-time approach to non-equilibrium statistical;

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The Theory Of Open Quantum Systems

of atoms, and the damped Jaynes-Cummings model. The basic features of the non-Markovian quantum behaviour of open systems are examined on the basis;

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Quantum Machine Learning: An Applied Approach

, inference, polynomial Hamiltonian simulation, and more, finishing with advanced and up-to-date research areas such as quantum walks, QML via Tensor;

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