-PDF Download- Reinforcement Learning With Hybrid Quantum Approximation In The Nisq Context EBOOK

Reinforcement Learning with Hybrid Quantum Approximation in the NISQ Context

Author: Leonhard Kunczik

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 145

ISBN-13: 3658376163

This book explores the combination of Reinforcement Learning and Quantum Computing in the light of complex attacker-defender scenarios. Reinforcement Learning has proven its capabilities in different challenging optimization problems and is now an established method in Operations Research. However, complex attacker-defender scenarios have several characteristics that challenge Reinforcement Learning algorithms, requiring enormous computational power to obtain the optimal solution. The upcoming field of Quantum Computing is a promising path for solving computationally complex problems. Therefore, this work explores a hybrid quantum approach to policy gradient methods in Reinforcement Learning. It proposes a novel quantum REINFORCE algorithm that enhances its classical counterpart by Quantum Variational Circuits. The new algorithm is compared to classical algorithms regarding the convergence speed and memory usage on several attacker-defender scenarios with increasing complexity. In addition, to study its applicability on today's NISQ hardware, the algorithm is evaluated on IBM's quantum computers, which is accompanied by an in-depth analysis of the advantages of Quantum Reinforcement Learning.

Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference

Author: Rashid Mehmood

Publisher: Springer Nature

Published: 2023-07-25

Total Pages: 527

ISBN-13: 3031383184

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The present book brings together experience, current work, and promising future trends associated with distributed computing, artificial intelligence, and their application in order to provide efficient solutions to real problems. DCAI 2023 is a forum to present applications of innovative techniques for studying and solving complex problems in artificial intelligence and computing areas. This year’s technical program presents both high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 108 papers were submitted, by authors from 31 different countries representing a truly “wide area network” of research activity. The DCAI’23 technical program has selected 50 full papers in the Special Sessions (ASET, AIMPM, AI4CS, CLIRAI, TECTONIC, PSO-ML, SmartFoF, IoTalentum) and, as in past editions, it will be special issues in ranked journals. This symposium is organized by the LASI and Centro Algoritmi of the University of Minho (Portugal). The authors like to thank all the contributing authors, the members of the Program Committee, National Associations (AEPIA, APPIA), and the sponsors (AIR Institute).

Real-World Challenges in Quantum Electronics and Machine Computing

Author: Ananth, Christo

Publisher: IGI Global

Published: 2024-08-05

Total Pages: 457

ISBN-13:

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Quantum computers are unparalleled in terms of computational power, and they have a multitude of promising applications. However, these computers are prone to noise and instability caused by environmental interactions, making the use of these advanced machines rather impractical in most scenarios. Despite these challenges, Real-World Challenges in Quantum Electronics and Machine Computing provides innovative solutions to navigate the complexities of quantum computation, thus offering hope during this time of turbulence. By delving into the intricacies of quantum electronics and machine computing, this book equips readers with the tools to overcome the hurdles obstructing the path to practical quantum computing. It serves as a roadmap for students, practitioners, and professionals, guiding them through the intricacies of error correction techniques and hardware development. With its comprehensive coverage of cutting-edge topics and innovative solutions, the book empowers readers to tackle the most pressing challenges facing the quantum computing landscape. As researchers and engineers strive to unlock the full potential of quantum computation, this book stands as an indispensable resource, guiding them toward a future where quantum computing transcends the realm of theory and becomes a tangible reality.

Data Analysis Techniques for High-Energy Physics

Author: Rudolf Frühwirth

Publisher: Cambridge University Press

Published: 2000-08-17

Total Pages: 412

ISBN-13: 9780521635486

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Now thoroughly revised and up-dated, this book describes techniques for handling and analysing data obtained from high-energy and nuclear physics experiments. The observation of particle interactions involves the analysis of large and complex data samples. Beginning with a chapter on real-time data triggering and filtering, the book describes methods of selecting the relevant events from a sometimes huge background. The use of pattern recognition techniques to group the huge number of measurements into physically meaningful objects like particle tracks or showers is then examined and the track and vertex fitting methods necessary to extract the maximum amount of information from the available measurements are explained. The final chapter describes tools and methods which are useful to the experimenter in the physical interpretation and in the presentation of the results. This indispensable guide will appeal to graduate students, researchers and computer and electronic engineers involved with experimental physics.

Post-Quantum Cryptography

Author: Daniel J. Bernstein

Publisher: Springer Science & Business Media

Published: 2009-02-01

Total Pages: 246

ISBN-13: 3540887024

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Quantum computers will break today's most popular public-key cryptographic systems, including RSA, DSA, and ECDSA. This book introduces the reader to the next generation of cryptographic algorithms, the systems that resist quantum-computer attacks: in particular, post-quantum public-key encryption systems and post-quantum public-key signature systems. Leading experts have joined forces for the first time to explain the state of the art in quantum computing, hash-based cryptography, code-based cryptography, lattice-based cryptography, and multivariate cryptography. Mathematical foundations and implementation issues are included. This book is an essential resource for students and researchers who want to contribute to the field of post-quantum cryptography.

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.

Electronic Structure Methods for Complex Materials

Author: Wai-Yim Ching

Publisher: OUP Oxford

Published: 2012-05-17

Total Pages: 328

ISBN-13: 0191635065

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Density functional theory (DFT) has blossomed in the past few decades into a powerful tool that is used by experimentalists and theoreticians alike. This book highlights the extensive contributions that the DFT-based OLCAO method has made to progress in this field, and it demonstrates its competitiveness for performing ab initio calculations on large and complex models of practical systems. A brief historical account and introduction to the elements of the theory set the stage for discussions on semiconductors, insulators, crystalline metals and alloys, complex crystals, non-crystalline solids and liquids, microstructure containing systems and those containing impurities, defects, and surfaces, biomolecular systems, and the technique of ab initio core level spectroscopy calculation.

Introduction to Chinese Natural Language Processing

Author: Kam-Fai Wong

Publisher: Springer Nature

Published: 2022-06-01

Total Pages: 148

ISBN-13: 3031021339

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This book introduces Chinese language-processing issues and techniques to readers who already have a basic background in natural language processing (NLP). Since the major difference between Chinese and Western languages is at the word level, the book primarily focuses on Chinese morphological analysis and introduces the concept, structure, and interword semantics of Chinese words. The following topics are covered: a general introduction to Chinese NLP; Chinese characters, morphemes, and words and the characteristics of Chinese words that have to be considered in NLP applications; Chinese word segmentation; unknown word detection; word meaning and Chinese linguistic resources; interword semantics based on word collocation and NLP techniques for collocation extraction. Table of Contents: Introduction / Words in Chinese / Challenges in Chinese Morphological Processing / Chinese Word Segmentation / Unknown Word Identification / Word Meaning / Chinese Collocations / Automatic Chinese Collocation Extraction / Appendix / References / Author Biographies

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.

Music Through Fourier Space

Author: Emmanuel Amiot

Publisher: Springer

Published: 2016-10-26

Total Pages: 214

ISBN-13: 3319455818

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This book explains the state of the art in the use of the discrete Fourier transform (DFT) of musical structures such as rhythms or scales. In particular the author explains the DFT of pitch-class distributions, homometry and the phase retrieval problem, nil Fourier coefficients and tilings, saliency, extrapolation to the continuous Fourier transform and continuous spaces, and the meaning of the phases of Fourier coefficients. This is the first textbook dedicated to this subject, and with supporting examples and exercises this is suitable for researchers and advanced undergraduate and graduate students of music, computer science and engineering. The author has made online supplementary material available, and the book is also suitable for practitioners who want to learn about techniques for understanding musical notions and who want to gain musical insights into mathematical problems.