Introduction To Quantum Neural Technologies PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Introduction To Quantum Neural Technologies PDF full book. Access full book title Introduction To Quantum Neural Technologies.
| Author | : Alexandr A. Ezhov |
| Publisher | : |
| Total Pages | : 248 |
| Release | : 2003 |
| Genre | : Neural networks (Computer science) |
| ISBN | : |
Download Introduction to Quantum Neural Technologies Book in PDF, ePub and Kindle
This is a first introductory book in Quantum Neural Technology -- a new and promising area of informatics. Combination of the ideas from quantum computing and neural computing raises the possibility of dramatically decreasing the complexity of neural systems by replacing networks of classical neurons with a single quantum neuron. In the first two chapters, the fundamentals of neural technologies and of quantum computing are presented. In the third chapter, it is outlined how the problems typical for classical neural technology can be solved by using quantum neural technology. This book is very useful to students, teachers, researchers, and engineers, who are working in informatics or just interested in being briefly aware of it.
| Author | : Maria Schuld |
| Publisher | : Springer |
| Total Pages | : 293 |
| Release | : 2018-08-30 |
| Genre | : Science |
| ISBN | : 3319964240 |
Download Supervised Learning with Quantum Computers Book in PDF, ePub and Kindle
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.
| Author | : Maria Schuld |
| Publisher | : Springer Nature |
| Total Pages | : 321 |
| Release | : 2021-10-17 |
| Genre | : Science |
| ISBN | : 3030830985 |
Download Machine Learning with Quantum Computers Book in PDF, ePub and Kindle
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.
| Author | : Vladimir G. Ivancevic |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 938 |
| Release | : 2010-01-18 |
| Genre | : Computers |
| ISBN | : 9048133505 |
Download Quantum Neural Computation Book in PDF, ePub and Kindle
Quantum Neural Computation is a graduate–level monographic textbook. It presents a comprehensive introduction, both non-technical and technical, into modern quantum neural computation, the science behind the fiction movie Stealth. Classical computing systems perform classical computations (i.e., Boolean operations, such as AND, OR, NOT gates) using devices that can be described classically (e.g., MOSFETs). On the other hand, quantum computing systems perform classical computations using quantum devices (quantum dots), that is devices that can be described only using quantum mechanics. Any information transfer between such computing systems involves a state measurement. This book describes this information transfer at the edge of classical and quantum chaos and turbulence, where mysterious quantum-mechanical linearity meets even more mysterious brain’s nonlinear complexity, in order to perform a super–high–speed and error–free computations. This monograph describes a crossroad between quantum field theory, brain science and computational intelligence.
| Author | : Gennady P. Berman |
| Publisher | : World Scientific |
| Total Pages | : 200 |
| Release | : 1998 |
| Genre | : Computers |
| ISBN | : 9789810235499 |
Download Introduction to Quantum Computers Book in PDF, ePub and Kindle
Quantum computing promises to solve problems which are intractable on digital computers. Highly parallel quantum algorithms can decrease the computational time for some problems by many orders of magnitude. This important book explains how quantum computers can do these amazing things. Several algorithms are illustrated: the discrete Fourier transform, Shor's algorithm for prime factorization; algorithms for quantum logic gates; physical implementations of quantum logic gates in ion traps and in spin chains; the simplest schemes for quantum error correction; correction of errors caused by imperfect resonant pulses; correction of errors caused by the nonresonant actions of a pulse; and numerical simulations of dynamical behavior of the quantum Control-Not gate. An overview of some basic elements of computer science is presented, including the Turing machine, Boolean algebra, and logic gates. The required quantum ideas are explained.
| Author | : Kusum Deep |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 1048 |
| Release | : 2012-04-15 |
| Genre | : Technology & Engineering |
| ISBN | : 8132204875 |
Download Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011 Book in PDF, ePub and Kindle
The objective is to provide the latest developments in the area of soft computing. These are the cutting edge technologies that have immense application in various fields. All the papers will undergo the peer review process to maintain the quality of work.
| Author | : Dr. M. Sreedevi |
| Publisher | : DRAFT2DIGITAL |
| Total Pages | : 80 |
| Release | : 2022-07-21 |
| Genre | : Computers |
| ISBN | : |
Download Introduction to Quantum Computing & Machine Learning Technologies Book in PDF, ePub and Kindle
Quantum computing is a sophisticated approach to making parallel calculations, using the physics that governs subatomic particles to replace the more simplistic transistors in today’s computers. Therefore it holds the promise to solve some of our planet's biggest challenges - in the areas of environment, agriculture, health, energy, climate, materials science, and others we haven't encountered yet. For some of these problems, classical computing is increasingly challenged as the size of the system grows. When designed to scale, quantum systems will presumably have some capabilities that exceed our most powerful supercomputers. As the global community of quantum researchers, scientists, engineers, and business leaders continue to collaborate to advance the quantum ecosystem, we expect to see quantum impact accelerate across every industry. Like the first digital computers, quantum computers offer the possibility of technology exponentially more powerful than current systems. They stand to change companies, entire industries, and the world by solving problems that seem impossible today. A recent report by Gartner states that by 2023, 20% of organizations will be budgeting for quantum computing projects. As this new technology develops, organizations will face a shortage of quantum computing experts. The time to learn about quantum computing is now. Discover the business and technical implications of this new frontier in computing and how you can apply quantum computing to your organization is a greater challenge. Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy. It is undeniably one of the most influential and powerful technologies in today’s world. More importantly, we are far from seeing its full potential. There’s no doubt, it will continue to be making headlines for the foreseeable future. Machine learning is a tool for turning information into knowledge. In the past 50 years, there has been an explosion of data. This mass of data is useless unless we analyze it and find the patterns hidden within. Machine learning techniques are used to automatically find the valuable underlying patterns within complex data that we would otherwise struggle to discover. The hidden patterns and knowledge about a problem can be used to predict future events and perform all kinds of complex decision making.
| Author | : Igor Aleksander |
| Publisher | : Van Nostrand Reinhold Company |
| Total Pages | : 276 |
| Release | : 1990 |
| Genre | : Computers |
| ISBN | : |
Download An Introduction to Neural Computing Book in PDF, ePub and Kindle
The second edition of this text has been updated and includes material on new developments including neurocontrol, pattern analysis and dynamic systems. The book should be useful for undergraduate students of neural networks.
| Author | : Alto Osada |
| Publisher | : Springer |
| Total Pages | : 0 |
| Release | : 2022-12-14 |
| Genre | : Science |
| ISBN | : 9789811946431 |
Download Introduction to Quantum Technologies Book in PDF, ePub and Kindle
This book is a concise primer of quantum technology aiming at providing a comprehensive material of fundamentals to help beginners understand the common concepts and background theories to technologies for individual quantum systems. Further, it also describes how the concepts and theories are applied to technologies in various systems. This book consists of three parts. The first part looks back over basics of quantum mechanics necessary for the main content, including quantum state and operators, time evolution and perturbation theory. The second part explains in detail key components indispensable to follow quantum technologies: two-level systems, harmonic oscillator and cavity quantum electrodynamics and resonators. In the third part, the physical quantum systems are treated in a more abstract way by introducing quantum logic gates, quantum measurement and quantum error correction. Technical supplements are included in Appendices. The well-compiled topics and concise presentation feature the book as a supplemental primer in the courses of quantum technologies including quantum computing, quantum communication, quantum sensing and quantum simulation.
| Author | : Jon Adams |
| Publisher | : Green Mountain Computing |
| Total Pages | : 157 |
| Release | : |
| Genre | : Computers |
| ISBN | : |
Download AI Foundations Of Quantum Machine Learning Book in PDF, ePub and Kindle
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.
