Quantum Mechanics And Bayesian Machines PDF Download
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Author | : George Chapline |
Publisher | : World Scientific |
Total Pages | : 194 |
Release | : 2023-04-14 |
Genre | : Computers |
ISBN | : 981323248X |
Download Quantum Mechanics And Bayesian Machines Book in PDF, ePub and Kindle
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.
Author | : Kristof T. Schütt |
Publisher | : Springer Nature |
Total Pages | : 473 |
Release | : 2020-06-03 |
Genre | : Science |
ISBN | : 3030402452 |
Download Machine Learning Meets Quantum Physics Book in PDF, ePub and Kindle
Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations for large systems and long time-scales, thus presenting a severe bottleneck both for searching the vast chemical compound space and the stupendously many dynamical configurations that a molecule can assume. To overcome this challenge, recently there have been increased efforts to accelerate quantum simulations with machine learning (ML). This emerging interdisciplinary community encompasses chemists, material scientists, physicists, mathematicians and computer scientists, joining forces to contribute to the exciting hot topic of progressing machine learning and AI for molecules and materials. The book that has emerged from a series of workshops provides a snapshot of this rapidly developing field. It contains tutorial material explaining the relevant foundations needed in chemistry, physics as well as machine learning to give an easy starting point for interested readers. In addition, a number of research papers defining the current state-of-the-art are included. The book has five parts (Fundamentals, Incorporating Prior Knowledge, Deep Learning of Atomistic Representations, Atomistic Simulations and Discovery and Design), each prefaced by editorial commentary that puts the respective parts into a broader scientific context.
Author | : Hans Christian von Baeyer |
Publisher | : Harvard University Press |
Total Pages | : 240 |
Release | : 2016-10-03 |
Genre | : Science |
ISBN | : 0674545109 |
Download QBism Book in PDF, ePub and Kindle
Short for Quantum Bayesianism, QBism adapts conventional features of quantum mechanics in light of a revised understanding of probability. Using commonsense language, without the equations or weirdness of conventional quantum theory, Hans Christian von Baeyer clarifies the meaning of quantum mechanics and suggests a new approach to general physics.
Author | : Prateek Tandon |
Publisher | : Morgan & Claypool Publishers |
Total Pages | : 178 |
Release | : 2017-01-17 |
Genre | : Science |
ISBN | : 1627056858 |
Download Quantum Robotics Book in PDF, ePub and Kindle
Quantum robotics is an emerging engineering and scientific research discipline that explores the application of quantum mechanics, quantum computing, quantum algorithms, and related fields to robotics. This work broadly surveys advances in our scientific understanding and engineering of quantum mechanisms and how these developments are expected to impact the technical capability for robots to sense, plan, learn, and act in a dynamic environment. It also discusses the new technological potential that quantum approaches may unlock for sensing and control, especially for exploring and manipulating quantum-scale environments. Finally, the work surveys the state of the art in current implementations, along with their benefits and limitations, and provides a roadmap for the future.
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 | : János A. Bergou |
Publisher | : Springer Science & Business Media |
Total Pages | : 158 |
Release | : 2013-05-18 |
Genre | : Computers |
ISBN | : 1461470927 |
Download Introduction to the Theory of Quantum Information Processing Book in PDF, ePub and Kindle
Introduction to the Theory of Quantum Information Processing provides the material for a one-semester graduate level course on quantum information theory and quantum computing for students who have had a one-year graduate course in quantum mechanics. Many standard subjects are treated, such as density matrices, entanglement, quantum maps, quantum cryptography, and quantum codes. Also included are discussions of quantum machines and quantum walks. In addition, the book provides detailed treatments of several underlying fundamental principles of quantum theory, such as quantum measurements, the no-cloning and no-signaling theorems, and their consequences. Problems of various levels of difficulty supplement the text, with the most challenging problems bringing the reader to the forefront of active research. This book provides a compact introduction to the fascinating and rapidly evolving interdisciplinary field of quantum information theory, and it prepares the reader for doing active research in this area.
Author | : Andreas Miroslaus Wichert |
Publisher | : World Scientific |
Total Pages | : 497 |
Release | : 2020-07-08 |
Genre | : Computers |
ISBN | : 9811224323 |
Download Principles Of Quantum Artificial Intelligence: Quantum Problem Solving And Machine Learning (Second Edition) Book in PDF, ePub and Kindle
This unique compendium presents an introduction to problem solving, information theory, statistical machine learning, stochastic methods and quantum computation. It indicates how to apply quantum computation to problem solving, machine learning and quantum-like models to decision making — the core disciplines of artificial intelligence.Most of the chapters were rewritten and extensive new materials were updated. New topics include quantum machine learning, quantum-like Bayesian networks and mind in Everett many-worlds.
Author | : Patrick Suppes |
Publisher | : Springer |
Total Pages | : 572 |
Release | : 1976 |
Genre | : Mathematics |
ISBN | : |
Download Logic and Probability in Quantum Mechanics Book in PDF, ePub and Kindle
During the academic years 1972-1973 and 1973-1974, an intensive sem inar on the foundations of quantum mechanics met at Stanford on a regular basis. The extensive exploration of ideas in the seminar led to the org~ization of a double issue of Synthese concerned with the foundations of quantum mechanics, especially with the role of logic and probability in quantum meChanics. About half of the articles in the volume grew out of this seminar. The remaining articles have been so licited explicitly from individuals who are actively working in the foun dations of quantum mechanics. Seventeen of the twenty-one articles appeared in Volume 29 of Syn these. Four additional articles and a bibliography on -the history and philosophy of quantum mechanics have been added to the present volume. In particular, the articles by Bub, Demopoulos, and Lande, as well as the second article by Zanotti and myself, appear for the first time in the present volume. In preparing the articles for publication I am much indebted to Mrs. Lillian O'Toole, Mrs. Dianne Kanerva, and Mrs. Marguerite Shaw, for their extensive assistance.
Author | : Christopher G. Timpson |
Publisher | : Oxford University Press |
Total Pages | : 308 |
Release | : 2013-04-25 |
Genre | : Philosophy |
ISBN | : 0199296464 |
Download Quantum Information Theory and the Foundations of Quantum Mechanics Book in PDF, ePub and Kindle
Christopher G. Timpson provides the first full-length philosophical treatment of quantum information theory and the questions it raises for our understanding of the quantum world. He argues for an ontologically deflationary account of the nature of quantum information, which is grounded in a revisionary analysis of the concepts of information.
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.