Quantum Machines

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Quantum Machine Learning

Author : Peter Wittek
Publisher : Academic Press
ISBN 13 : 0128010991
Total Pages : 176 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Quantum Machine Learning by : Peter Wittek

Download or read book Quantum Machine Learning written by Peter Wittek and published by Academic Press. This book was released on 2014-09-10 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Schrodinger's Machines

Author : Gerard J. Milburn
Publisher : W. H. Freeman
ISBN 13 : 9780716731061
Total Pages : 208 pages
Book Rating : 4.7/5 (31 download)

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Book Synopsis Schrodinger's Machines by : Gerard J. Milburn

Download or read book Schrodinger's Machines written by Gerard J. Milburn and published by W. H. Freeman. This book was released on 1997-04-15 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: In his foreword to Schrödinger's Machines, Paul Davies writes, "The nineteenth century was known as the machine age, the twentieth century will go down in history as the information age. I believe the twenty-first century will be the quantum age." Perhaps the most successful scientific theory in history, quantum mechanics has already ushered in the information age with inventions like the transistor and the laser. In Schrödinger's Machines, renowned quantum physicist Gerard Milburn explores how our ever-increasing ability to manipulate atomic and subatomic processes is turning purely hypothetical situations and concepts (of a truly weird nature) into concrete, practical devices-- resulting in a complete transformation of our world view. Imagine the creation of machines the size of molecules, detectors sensitive enough to pick up the sound of a pin dropping on the other side of the earth, the fabrication of new and exotic materials, and extraordinarily powerful computers that can process information in many alternative realities simultaneously, creating a whole new type of mathematics. This isn't science fiction, but just some of the breathtaking possibilities offered by quantum technology over the next fifty years. Leaving the common sense of Newtonian machines far behind, Schrödinger's Machines is an advance preview of the strange new world ahead. Clearly presented, and with an acute awareness of recent advances in the field, it's indispensable reading for anyone interested in the future.

Quantum Machines

Author : Michel Devoret
Publisher : Oxford University Press, USA
ISBN 13 : 019968118X
Total Pages : 601 pages
Book Rating : 4.1/5 (996 download)

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Book Synopsis Quantum Machines by : Michel Devoret

Download or read book Quantum Machines written by Michel Devoret and published by Oxford University Press, USA. This book was released on 2014 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is a quantum machine? Can we say that lasers and transistors are quantum machines? After all, physicists advertise these devices as the two main spin-offs of the understanding of quantum physics. In a true quantum machine, the signal collective variables must themselves be treated as quantum operators. Other engineered quantum systems based on natural, rather than artificial, degrees of freedom can also qualify as quantum machines. This book provides the basic knowledge needed to understand and investigate the physics of these novel systems.

Machine Learning with Quantum Computers

Author : Maria Schuld
Publisher : Springer Nature
ISBN 13 : 3030830985
Total Pages : 321 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Machine Learning with Quantum Computers by : Maria Schuld

Download or read book Machine Learning with Quantum Computers written by Maria Schuld and published by Springer Nature. This book was released on 2021-10-17 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Programming Quantum Computers

Author : Eric R. Johnston
Publisher : O'Reilly Media
ISBN 13 : 1492039659
Total Pages : 333 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Programming Quantum Computers by : Eric R. Johnston

Download or read book Programming Quantum Computers written by Eric R. Johnston and published by O'Reilly Media. This book was released on 2019-07-03 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum computers are set to kick-start a second computing revolution in an exciting and intriguing way. Learning to program a Quantum Processing Unit (QPU) is not only fun and exciting, but it's a way to get your foot in the door. Like learning any kind of programming, the best way to proceed is by getting your hands dirty and diving into code. This practical book uses publicly available quantum computing engines, clever notation, and a programmer’s mindset to get you started. You'll be able to build up the intuition, skills, and tools needed to start writing quantum programs and solve problems that you care about.

Supervised Learning with Quantum Computers

Author : Maria Schuld
Publisher : Springer
ISBN 13 : 3319964240
Total Pages : 293 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Supervised Learning with Quantum Computers by : Maria Schuld

Download or read book Supervised Learning with Quantum Computers written by Maria Schuld and published by Springer. This book was released on 2018-08-30 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Concise Guide to Quantum Machine Learning

Author : Davide Pastorello
Publisher : Springer Nature
ISBN 13 : 9811968977
Total Pages : 144 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Concise Guide to Quantum Machine Learning by : Davide Pastorello

Download or read book Concise Guide to Quantum Machine Learning written by Davide Pastorello and published by Springer Nature. This book was released on 2022-12-16 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a brief but effective introduction to quantum machine learning (QML). QML is not merely a translation of classical machine learning techniques into the language of quantum computing, but rather a new approach to data representation and processing. Accordingly, the content is not divided into a “classical part” that describes standard machine learning schemes and a “quantum part” that addresses their quantum counterparts. Instead, to immerse the reader in the quantum realm from the outset, the book starts from fundamental notions of quantum mechanics and quantum computing. Avoiding unnecessary details, it presents the concepts and mathematical tools that are essential for the required quantum formalism. In turn, it reviews those quantum algorithms most relevant to machine learning. Later chapters highlight the latest advances in this field and discuss the most promising directions for future research. To gain the most from this book, a basic grasp of statistics and linear algebra is sufficient; no previous experience with quantum computing or machine learning is needed. The book is aimed at researchers and students with no background in quantum physics and is also suitable for physicists looking to enter the field of QML.

Quantum Machine Learning

Author : Claudio Conti
Publisher : Springer Nature
ISBN 13 : 3031442261
Total Pages : 393 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Quantum Machine Learning by : Claudio Conti

Download or read book Quantum Machine Learning written by Claudio Conti and published by Springer Nature. This book was released on 2024-01-28 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Quantum Computers, Algorithms and Chaos

Author : G. Casati
Publisher : IOS Press
ISBN 13 : 1614990182
Total Pages : 635 pages
Book Rating : 4.6/5 (149 download)

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Book Synopsis Quantum Computers, Algorithms and Chaos by : G. Casati

Download or read book Quantum Computers, Algorithms and Chaos written by G. Casati and published by IOS Press. This book was released on 2006-12-19 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last ten years Quantum Information Processing and Communication (QIPC) has established itself as one of the new hot topic fields in physics, with the potential to revolutionize many areas of science and technology. QIPC replaces the laws of classical physics applied to computation and communication with the more fundamental laws of quantum mechanics. This becomes increasingly important due to technological progress going down to smaller and smaller scales where quantum effects start to be dominant. In addition to its fundamental nature, QIPC promises to advance computing power beyond the capabilities of any classical computer, to guarantee secure communication and establish direct links to emerging quantum technologies, such as, for example, quantum based sensors and clocks. One of the outstanding feature of QIPC is its interdisciplinary character: it brings together researchers from physics, mathematics and computer science. In particular, within physics we have seen the emergence of a new QIPC community, which ranges from theoretical to experimental physics, and crosses boundaries of traditionally separated disciplines such as atomic physics, quantum optics, statistical mechanics and solid state physics, all working on different and complementary aspects of QIPC. This publication covers the following topics: Introduction to quantum computing; Quantum logic, information and entanglement; Quantum algorithms; Error-correcting codes for quantum computations; Quantum measurements and control; Quantum communication; Quantum optics and cold atoms for quantum information; Quantum computing with solid state devices; Theory and experiments for superconducting qubits; Interactions in many-body systems: quantum chaos, disorder and random matrices; Decoherence effects for quantum computing; and Flature prospects of quantum information processing.

Quantum Computer Systems

Author : Yongshan Ding
Publisher : Springer Nature
ISBN 13 : 303101765X
Total Pages : 203 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Quantum Computer Systems by : Yongshan Ding

Download or read book Quantum Computer Systems written by Yongshan Ding and published by Springer Nature. This book was released on 2022-05-31 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book targets computer scientists and engineers who are familiar with concepts in classical computer systems but are curious to learn the general architecture of quantum computing systems. It gives a concise presentation of this new paradigm of computing from a computer systems' point of view without assuming any background in quantum mechanics. As such, it is divided into two parts. The first part of the book provides a gentle overview on the fundamental principles of the quantum theory and their implications for computing. The second part is devoted to state-of-the-art research in designing practical quantum programs, building a scalable software systems stack, and controlling quantum hardware components. Most chapters end with a summary and an outlook for future directions. This book celebrates the remarkable progress that scientists across disciplines have made in the past decades and reveals what roles computer scientists and engineers can play to enable practical-scale quantum computing.

Quantum Mechanics And Bayesian Machines

Author : George Chapline
Publisher : World Scientific
ISBN 13 : 981323248X
Total Pages : 194 pages
Book Rating : 4.8/5 (132 download)

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Book Synopsis Quantum Mechanics And Bayesian Machines by : George Chapline

Download or read book Quantum Mechanics And Bayesian Machines written by George Chapline and published by World Scientific. This book was released on 2023-04-14 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: This compendium brings together the fields of Quantum Computing, Machine Learning, and Neuromorphic Computing. It provides an elementary introduction for students and researchers interested in quantum or neuromorphic computing to the basics of machine learning and the possibilities for using quantum devices for pattern recognition and Bayesian decision tree problems. The volume also highlights some possibly new insights into the meaning of quantum mechanics, for example, why a description of Nature requires probabilistic rather than deterministic methods.

Quantum Computing

Author : Nihal Mehta Ph.D.
Publisher : Pragmatic Bookshelf
ISBN 13 : 1680508091
Total Pages : 753 pages
Book Rating : 4.6/5 (85 download)

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Book Synopsis Quantum Computing by : Nihal Mehta Ph.D.

Download or read book Quantum Computing written by Nihal Mehta Ph.D. and published by Pragmatic Bookshelf. This book was released on 2020-08-26 with total page 753 pages. Available in PDF, EPUB and Kindle. Book excerpt: You've heard that quantum computing is going to change the world. Now you can check it out for yourself. Learn how quantum computing works, and write programs that run on the IBM Q quantum computer, one of the world's first functioning quantum computers. Learn a simple way to apply quantum mechanics to computer programming. Create algorithms to solve intractable problems for classical computers, and discover how to explore the entire problem space at once to determine the optimal solution. Get your hands on the future of computing today. Quantum computing overhauls computer science. Problems such as designing life-saving drugs and super-large logistics problems that have been difficult or impossible for classical computers to handle can now be solved in moments. Quantum computing makes it possible to explore all possible solutions simultaneously and determine those that work, instead of iterating through each possibility sequentially. Work with quantum computers directly, instead of talking about them theoretically. Discover a new visual way of looking at quantum bits that makes quantum computing intuitive for computer programmers. Master the special properties that make them different, and more powerful, than classical bits. Control quantum bits with gates and create circuits to model complex problems. Write programs that run on real quantum machines to solve problems that classical computers struggle with. Dive into quantum optimization and cryptography. Get a head start on the technology that will drive computer science into the future. What You Need: Access to the IBM quantum computer, via any internet connection

Quantum Machine Learning

Author : Siddhartha Bhattacharyya
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110670704
Total Pages : 131 pages
Book Rating : 4.1/5 (16 download)

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Book Synopsis Quantum Machine Learning by : Siddhartha Bhattacharyya

Download or read book Quantum Machine Learning written by Siddhartha Bhattacharyya and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-06-08 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method. Such algorithms typically require one to encode the given classical dataset into a quantum computer, so as to make it accessible for quantum information processing. After this, quantum information processing routines can be applied and the result of the quantum computation is read out by measuring the quantum system. While many proposals of quantum machine learning algorithms are still purely theoretical and require a full-scale universal quantum computer to be tested, others have been implemented on small-scale or special purpose quantum devices.

A Practical Guide to Quantum Machine Learning and Quantum Optimization

Author : Elias F. Combarro
Publisher : Packt Publishing Ltd
ISBN 13 : 1804618306
Total Pages : 680 pages
Book Rating : 4.8/5 (46 download)

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Book Synopsis A Practical Guide to Quantum Machine Learning and Quantum Optimization by : Elias F. Combarro

Download or read book A Practical Guide to Quantum Machine Learning and Quantum Optimization written by Elias F. Combarro and published by Packt Publishing Ltd. This book was released on 2023-03-31 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work with fully explained algorithms and ready-to-use examples that can be run on quantum simulators and actual quantum computers with this comprehensive guide Key FeaturesGet a solid grasp of the principles behind quantum algorithms and optimization with minimal mathematical prerequisitesLearn the process of implementing the algorithms on simulators and actual quantum computersSolve real-world problems using practical examples of methodsBook Description This book provides deep coverage of modern quantum algorithms that can be used to solve real-world problems. You'll be introduced to quantum computing using a hands-on approach with minimal prerequisites. You'll discover many algorithms, tools, and methods to model optimization problems with the QUBO and Ising formalisms, and you will find out how to solve optimization problems with quantum annealing, QAOA, Grover Adaptive Search (GAS), and VQE. This book also shows you how to train quantum machine learning models, such as quantum support vector machines, quantum neural networks, and quantum generative adversarial networks. The book takes a straightforward path to help you learn about quantum algorithms, illustrating them with code that's ready to be run on quantum simulators and actual quantum computers. You'll also learn how to utilize programming frameworks such as IBM's Qiskit, Xanadu's PennyLane, and D-Wave's Leap. Through reading this book, you will not only build a solid foundation of the fundamentals of quantum computing, but you will also become familiar with a wide variety of modern quantum algorithms. Moreover, this book will give you the programming skills that will enable you to start applying quantum methods to solve practical problems right away. What you will learnReview the basics of quantum computingGain a solid understanding of modern quantum algorithmsUnderstand how to formulate optimization problems with QUBOSolve optimization problems with quantum annealing, QAOA, GAS, and VQEFind out how to create quantum machine learning modelsExplore how quantum support vector machines and quantum neural networks work using Qiskit and PennyLaneDiscover how to implement hybrid architectures using Qiskit and PennyLane and its PyTorch interfaceWho this book is for This book is for professionals from a wide variety of backgrounds, including computer scientists and programmers, engineers, physicists, chemists, and mathematicians. Basic knowledge of linear algebra and some programming skills (for instance, in Python) are assumed, although all mathematical prerequisites will be covered in the appendices.

Quantum Mechanics for Scientists and Engineers

Author : David A. B. Miller
Publisher : Cambridge University Press
ISBN 13 : 1139471279
Total Pages : 575 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Quantum Mechanics for Scientists and Engineers by : David A. B. Miller

Download or read book Quantum Mechanics for Scientists and Engineers written by David A. B. Miller and published by Cambridge University Press. This book was released on 2008-04-21 with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you need a book that relates the core principles of quantum mechanics to modern applications in engineering, physics, and nanotechnology, this is it. Students will appreciate the book's applied emphasis, which illustrates theoretical concepts with examples of nanostructured materials, optics, and semiconductor devices. The many worked examples and more than 160 homework problems help students to problem solve and to practise applications of theory. Without assuming a prior knowledge of high-level physics or classical mechanics, the text introduces Schrödinger's equation, operators, and approximation methods. Systems, including the hydrogen atom and crystalline materials, are analyzed in detail. More advanced subjects, such as density matrices, quantum optics, and quantum information, are also covered. Practical applications and algorithms for the computational analysis of simple structures make this an ideal introduction to quantum mechanics for students of engineering, physics, nanotechnology, and other disciplines. Additional resources available from www.cambridge.org/9780521897839.

AI Foundations Of Quantum Machine Learning

Author : Jon Adams
Publisher : Green Mountain Computing
ISBN 13 :
Total Pages : 157 pages
Book Rating : 4./5 ( download)

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Book Synopsis AI Foundations Of Quantum Machine Learning by : Jon Adams

Download or read book AI Foundations Of Quantum Machine Learning written by Jon Adams and published by Green Mountain Computing. This book was released on with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dive into the cutting-edge intersection of quantum computing and machine learning with "AI Foundations of Quantum Machine Learning." This comprehensive guide invites readers into the exciting world where the realms of artificial intelligence (AI) and quantum mechanics merge, setting the stage for a revolution in AI technologies. With the burgeoning interest in quantum computing's vast potential, this book serves as a beacon, illuminating the intricate concepts and groundbreaking promises of quantum machine learning. Contents Quantum Computing: An Introduction - Begin your journey with a primer on quantum computing, understanding the fundamental quantum mechanics that power advanced data processing. Fundamentals of Machine Learning - Lay the groundwork with an overview of machine learning principles, setting the stage for their quantum leap. Quantum Algorithms for Machine Learning - Discover the transformative potential of quantum algorithms, capable of processing large datasets with unprecedented speed and efficiency. Data Encoding in Quantum Systems - Explore the innovative techniques for encoding data into quantum systems, a crucial step for quantum machine learning. Quantum Machine Learning Models - Delve into the heart of quantum machine learning, examining models that harness quantum mechanics to enhance machine learning capabilities. Training Quantum Neural Networks - Unpack the methodologies for training quantum neural networks, a pioneering approach to AI development. Applications of Quantum Machine Learning - Witness the practical implications of quantum machine learning across various fields, from healthcare to environmental science. Challenges and the Future Landscape - Reflect on the hurdles facing quantum machine learning and envision the future of AI shaped by quantum advancements. Introduction "AI Foundations of Quantum Machine Learning" offers a compelling narrative on the symbiosis of quantum computing and machine learning. Through accessible language and vivid examples, it demystifies complex concepts and showcases the transformative power of quantum technologies in AI. Readers are taken on an enlightening journey, from the basic principles of quantum computing to the forefront of quantum machine learning models and their applications. This book is not merely an academic text; it is a roadmap to the future, encouraging readers to envision a world where AI is redefined by quantum phenomena. Ideal for students, academics, and tech enthusiasts alike, this book bridges the gap between theoretical quantum mechanics and practical machine learning applications. Whether you're looking to understand the basics or explore the future of technology, "AI Foundations of Quantum Machine Learning" is an indispensable resource for anyone eager to grasp the next wave of technological innovation.

Quantum Machine Learning and Optimisation in Finance

Author : Antoine Jacquier
Publisher : Packt Publishing Ltd
ISBN 13 : 1801817871
Total Pages : 443 pages
Book Rating : 4.8/5 (18 download)

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Book Synopsis Quantum Machine Learning and Optimisation in Finance by : Antoine Jacquier

Download or read book Quantum Machine Learning and Optimisation in Finance written by Antoine Jacquier and published by Packt Publishing Ltd. This book was released on 2022-10-31 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the principles of quantum machine learning and how to apply them While focus is on financial use cases, all the methods and techniques are transferable to other fields Purchase of Print or Kindle includes a free eBook in PDF Key Features Discover how to solve optimisation problems on quantum computers that can provide a speedup edge over classical methods Use methods of analogue and digital quantum computing to build powerful generative models Create the latest algorithms that work on Noisy Intermediate-Scale Quantum (NISQ) computers Book Description With recent advances in quantum computing technology, we finally reached the era of Noisy Intermediate-Scale Quantum (NISQ) computing. NISQ-era quantum computers are powerful enough to test quantum computing algorithms and solve hard real-world problems faster than classical hardware. Speedup is so important in financial applications, ranging from analysing huge amounts of customer data to high frequency trading. This is where quantum computing can give you the edge. Quantum Machine Learning and Optimisation in Finance shows you how to create hybrid quantum-classical machine learning and optimisation models that can harness the power of NISQ hardware. This book will take you through the real-world productive applications of quantum computing. The book explores the main quantum computing algorithms implementable on existing NISQ devices and highlights a range of financial applications that can benefit from this new quantum computing paradigm. This book will help you be one of the first in the finance industry to use quantum machine learning models to solve classically hard real-world problems. We may have moved past the point of quantum computing supremacy, but our quest for establishing quantum computing advantage has just begun! What you will learn Train parameterised quantum circuits as generative models that excel on NISQ hardware Solve hard optimisation problems Apply quantum boosting to financial applications Learn how the variational quantum eigensolver and the quantum approximate optimisation algorithms work Analyse the latest algorithms from quantum kernels to quantum semidefinite programming Apply quantum neural networks to credit approvals Who this book is for This book is for Quants and developers, data scientists, researchers, and students in quantitative finance. Although the focus is on financial use cases, all the methods and techniques are transferable to other areas.