Applied Quantum Mechanics (3版)

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【簡介】 Featuring new coverage of quantum engineering and quantum information processing, the third edition of this bestselling textbook continues to provide a uniquely practical introduction to the fundamentals of quantum mechanics. It features straightforward explanations of quantum effects, suitable for readers from all backgrounds; real-world engineering problems showcasing the practical application of theory to practice, providing a relevant and accessible introduction to cutting-edge quantum applications; over 60 accessible worked examples using MATLAB (as well as open-source Python), allowing deepened understanding through computational exploration and visualization; and a new chapter on quantum engineering, introducing state-of-the-art concepts in quantum information processing and quantum device design. Updated throughout and supported online by downloadable MATLAB code, exam questions, and solutions to over 150 homework problems for instructors, this is the ideal textbook for senior undergraduate and graduate students in applied science, applied physics, engineering, and materials science studying a first course in quantum mechanics. 【目錄】

Quantum Computing: An Applied Approach (2版)

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This book integrates the foundations of quantum computing with a hands-on coding approach to this emerging field; it is the first to bring these elements together in an updated manner. This work is suitable for both academic coursework and corporate technical training. The second edition includes extensive updates and revisions, both to textual content and to the code. Sections have been added on quantum machine learning, quantum error correction, Dirac notation and more. This new edition benefits from the input of the many faculty, students, corporate engineering teams, and independent readers who have used the first edition. This volume comprises three books under one cover: Part I outlines the necessary foundations of quantum computing and quantum circuits. Part II walks through the canon of quantum computing algorithms and provides code on a range of quantum computing methods in current use. Part III covers the mathematical toolkit required to master quantum computing. Additional resources include a table of operators and circuit elements and a companion GitHub site providing code and updates. Jack D. Hidary is a research scientist in quantum computing and in AI at Alphabet X, formerly Google X.

INTRODUCTION TO APPLIED NUMERICAL ANALYSIS, AN

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his book is based on lecture notes for a numerical analysis course designed mainly for senior undergraduate students majoring in mathematics, engineering, computer science and physical sciences. The book has two overarching goals. The first goal is to introduce different available numerical procedures for finding solutions to linear equations, roots of polynomial equations, interpolation and approximation, numerical differentiation and integration, differential equations, and error analysis. The second goal is to translate theory into practice through applying commonly used numerical methods in mathematics, physical sciences, biomedical sciences, and engineering. This book was crafted in an informal and user-friendly manner to motivate the study of the material being covered. Ample figures and numerical tables are presented to enhance the reader's ease of understanding of the material under consideration. Sample Chapter(s) Preface Chapter 7: Boundary Value Problems Contents: Preliminaries Solution of Linear System of Equations Roots of Nonlinear Equations Polynomial Approximation and Interpolation Differentiation and Integration Initial Value Problems Boundary Value Problems Partial Differential Equations Readership: Undergraduate students in Mathematics, Statistics, Physics, Engineering and Computer Science, biomedical, and any Course dealing with numerical calculations and computations.