Learning and Robust Control in Quantum Technology
Learning and Robust Control in Quantum Technology

Author: Daoyi Dong

Publisher: Springer Nature

Published: 2023-03-24

Total Pages: 265

ISBN-13: 3031202457

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This monograph provides a state-of-the-art treatment of learning and robust control in quantum technology. It presents a systematic investigation of control design and algorithm realisation for several classes of quantum systems using control-theoretic tools and machine-learning methods. The approaches rely heavily on examples and the authors cover: sliding mode control of quantum systems; control and classification of inhomogeneous quantum ensembles using sampling-based learning control; robust and optimal control design using machine-learning methods; robust stability of quantum systems; and H∞ and fault-tolerant control of quantum systems. Both theoretical algorithm design and potential practical applications are considered. Methods for enhancing robustness of performance are developed in the context of quantum state preparation, quantum gate construction, and ultrafast control of molecules. Researchers and graduates studying systems and control theory, quantum control, and quantum engineering, especially from backgrounds in electrical engineering, applied mathematics and quantum information will find Learning and Robust Control in Quantum Technology to be a valuable reference for the investigation of learning and robust control of quantum systems. The material contained in this book will also interest chemists and physicists working on chemical physics, quantum optics, and quantum information technology.

Quantum Measurement and Control
Quantum Measurement and Control

Author: Howard M. Wiseman

Publisher: Cambridge University Press

Published: 2010

Total Pages: 477

ISBN-13: 0521804426

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Modern quantum measurement for graduate students and researchers in quantum information, quantum metrology, quantum control and related fields.

Intelligent Computing and Networking
Intelligent Computing and Networking

Author: Valentina Emilia Balas

Publisher: Springer Nature

Published: 2022-02-08

Total Pages: 287

ISBN-13: 9811648638

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This book gathers high-quality peer-reviewed research papers presented at the International Conference on Intelligent Computing and Networking (IC-ICN 2021), organized by the Computer Department, Thakur College of Engineering and Technology, in Mumbai, Maharashtra, India, on February 26–27, 2021. The book includes innovative and novel papers in the areas of intelligent computing, artificial intelligence, machine learning, deep learning, fuzzy logic, natural language processing, human–machine interaction, big data mining, data science and mining, applications of intelligent systems in health ,care, finance, agriculture and manufacturing, high-performance computing, computer networking, sensor and wireless networks, Internet of Things (IoT), software-defined networks, cryptography, mobile computing, digital forensics, and blockchain technology.

Quantum Computing
Quantum Computing

Author: National Academies of Sciences, Engineering, and Medicine

Publisher: National Academies Press

Published: 2019-04-27

Total Pages: 273

ISBN-13: 030947969X

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Quantum mechanics, the subfield of physics that describes the behavior of very small (quantum) particles, provides the basis for a new paradigm of computing. First proposed in the 1980s as a way to improve computational modeling of quantum systems, the field of quantum computing has recently garnered significant attention due to progress in building small-scale devices. However, significant technical advances will be required before a large-scale, practical quantum computer can be achieved. Quantum Computing: Progress and Prospects provides an introduction to the field, including the unique characteristics and constraints of the technology, and assesses the feasibility and implications of creating a functional quantum computer capable of addressing real-world problems. This report considers hardware and software requirements, quantum algorithms, drivers of advances in quantum computing and quantum devices, benchmarks associated with relevant use cases, the time and resources required, and how to assess the probability of success.

Control of Quantum Systems
Control of Quantum Systems

Author: Shuang Cong

Publisher: John Wiley & Sons

Published: 2014-06-03

Total Pages: 0

ISBN-13: 9781118608128

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Advanced research reference examining the closed and open quantum systems Control of Quantum Systems: Theory and Methods provides an insight into the modern approaches to control of quantum systems evolution, with a focus on both closed and open (dissipative) quantum systems. The topic is timely covering the newest research in the field, and presents and summarizes practical methods and addresses the more theoretical aspects of control, which are of high current interest, but which are not covered at this level in other text books. The quantum control theory and methods written in the book are the results of combination of macro-control theory and microscopic quantum system features. As the development of the nanotechnology progresses, the quantum control theory and methods proposed today are expected to be useful in real quantum systems within five years. The progress of the quantum control theory and methods will promote the progress and development of quantum information, quantum computing, and quantum communication. Equips readers with the potential theories and advanced methods to solve existing problems in quantum optics/information/computing, mesoscopic systems, spin systems, superconducting devices, nano-mechanical devices, precision metrology. Ideal for researchers, academics and engineers in quantum engineering, quantum computing, quantum information, quantum communication, quantum physics, and quantum chemistry, whose research interests are quantum systems control.

Supervised Learning with Quantum Computers
Supervised Learning with Quantum Computers

Author: Maria Schuld

Publisher: Springer

Published: 2018-08-30

Total Pages: 293

ISBN-13: 3319964240

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Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models''. A special focus lies on supervised learning, and applications for near-term quantum devices.

Quantum Machine Learning
Quantum Machine Learning

Author: Peter Wittek

Publisher: Academic Press

Published: 2014-09-10

Total Pages: 176

ISBN-13: 0128010991

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Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum framework. Theoretical advances in quantum computing are hard to follow for computer scientists, and sometimes even for researchers involved in the field. The lack of a step-by-step guide hampers the broader understanding of this emergent interdisciplinary body of research. Quantum Machine Learning sets the scene for a deeper understanding of the subject for readers of different backgrounds. The author has carefully constructed a clear comparison of classical learning algorithms and their quantum counterparts, thus making differences in computational complexity and learning performance apparent. This book synthesizes of a broad array of research into a manageable and concise presentation, with practical examples and applications. - Bridges the gap between abstract developments in quantum computing with the applied research on machine learning - Provides the theoretical minimum of machine learning, quantum mechanics, and quantum computing - Gives step-by-step guidance to a broader understanding of this emergent interdisciplinary body of research

Intelligent Systems'2014
Intelligent Systems'2014

Author: D. Filev

Publisher: Springer

Published: 2014-09-20

Total Pages: 893

ISBN-13: 3319113100

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This two volume set of books constitutes the proceedings of the 2014 7th IEEE International Conference Intelligent Systems (IS), or IEEE IS’2014 for short, held on September 24‐26, 2014 in Warsaw, Poland. Moreover, it contains some selected papers from the collocated IWIFSGN'2014-Thirteenth International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets.The conference was organized by the Systems Research Institute, Polish Academy of Sciences, Department IV of Engineering Sciences, Polish Academy of Sciences, and Industrial Institute of Automation and Measurements - PIAP.The papers included in the two proceedings volumes have been subject to a thorough review process by three highly qualified peer reviewers.Comments and suggestions from them have considerable helped improve the quality of the papers but also the division of the volumes into parts, and assignment of the papers to the best suited parts.

Machine Learning with Quantum Computers
Machine Learning with Quantum Computers

Author: Maria Schuld

Publisher: Springer Nature

Published: 2021-10-17

Total Pages: 321

ISBN-13: 3030830985

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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. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks. The book aims at an audience of computer scientists and physicists at the graduate level onwards. The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years.

Recent Advances in Mechanical Engineering
Recent Advances in Mechanical Engineering

Author: Gaurav Manik

Publisher: Springer Nature

Published: 2022-09-08

Total Pages: 1149

ISBN-13: 9811921881

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This book presents the select proceedings of 2nd International Congress on Advances in Mechanical and Systems Engineering (CAMSE 2021). It focuses on the recent advances in mechanical and systems engineering and their growing demands for increase in several design and development activities. The contents in this book cover a blend of mechanical engineering, computer-aided engineering, control engineering, and systems engineering to design and manufacture useful products. Various additional topics covered include mechanics, machines, materials science, thermo-fluids, and control with state-of-the-art computational methods to analyse, innovate, design, implement and operate complex systems which are economic, reliable, efficient and sustainable. Given the contents, this book will be useful for researchers and professionals working in the field of mechanical engineering and allied fields.