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學(xué)習(xí)量子比特(影印版)(英文版)

學(xué)習(xí)量子比特(影印版)(英文版)

出版社:東南大學(xué)出版社出版時(shí)間:2020-08-01
開本: 16開 頁數(shù): 488
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學(xué)習(xí)量子比特(影印版)(英文版) 版權(quán)信息

  • ISBN:9787564189747
  • 條形碼:9787564189747 ; 978-7-5641-8974-7
  • 裝幀:一般膠版紙
  • 冊(cè)數(shù):暫無
  • 重量:暫無
  • 所屬分類:>

學(xué)習(xí)量子比特(影印版)(英文版) 本書特色

量子計(jì)算正在改變我們對(duì)于計(jì)算機(jī)的思考方式。量子比特(quantum bits),又稱qubits,可以解決當(dāng)前計(jì)算技術(shù)難以解決的問題。 真正理解量子計(jì)算需要大量的數(shù)學(xué)知識(shí),而本書也不會(huì)回避必要的數(shù)學(xué)概念。每個(gè)主題均以清晰的文字和有用的示例進(jìn)行介紹和詳盡解釋。 你將從本書中學(xué)到: 量子計(jì)算的工作原理、與眾不同之處及其如此強(qiáng)大的原因 探索量子系統(tǒng)背后令人費(fèi)解的復(fù)雜支撐機(jī)制 理解經(jīng)典計(jì)算和量子計(jì)算背后的必要概念 復(fù)習(xí)并擴(kuò)展基礎(chǔ)數(shù)學(xué)、計(jì)算理論和量子理論知識(shí) 探索量子計(jì)算在科學(xué)計(jì)算、人工智能和其他領(lǐng)域的主要應(yīng)用 考察有關(guān)量子比特、量子電路和量子算法的詳細(xì)概述

學(xué)習(xí)量子比特(影印版)(英文版) 內(nèi)容簡介

量子計(jì)算正在改變我們對(duì)于計(jì)算機(jī)的思考方式。量子比特(quantum bits),又稱qubits,可以解決當(dāng)前計(jì)算技術(shù)難以解決的問題。 本書首先概述了量子計(jì)算與傳統(tǒng)計(jì)算如此不同的原因,并講述了可能會(huì)對(duì)量子計(jì)算產(chǎn)生重大影響的一些行業(yè)案例。對(duì)理解諸如疊加、糾纏和干涉等概念所必需的經(jīng)典計(jì)算理論和數(shù)學(xué)基礎(chǔ)進(jìn)行了更全面的講解。接下來是電路和算法。既有基礎(chǔ)的,也有更復(fù)雜的。然后,對(duì)構(gòu)建量子計(jì)算硬件背后的物理和工程思想娓娓道來。很后,本書展望了未來前景并提供了指引,幫助讀者了解日后的發(fā)展會(huì)如何影響到個(gè)人。 真正理解量子計(jì)算需要大量的數(shù)學(xué)知識(shí),而本書也不會(huì)回避必要的數(shù)學(xué)概念。每個(gè)主題均以清晰的文字和有用的示例進(jìn)行介紹和詳盡解釋。 你將從本書中學(xué)到: 量子計(jì)算的工作原理、與眾不同之處及其如此強(qiáng)大的原因; 探索量子系統(tǒng)背后令人費(fèi)解的復(fù)雜支撐機(jī)制; 理解經(jīng)典計(jì)算和量子計(jì)算背后的必要概念; 復(fù)習(xí)并擴(kuò)展基礎(chǔ)數(shù)學(xué)、計(jì)算理論和量子理論知識(shí); 探索量子計(jì)算在科學(xué)計(jì)算、人工智能和其他領(lǐng)域的主要應(yīng)用; 考察有關(guān)量子比特、量子電路和量子算法的詳細(xì)概述。

學(xué)習(xí)量子比特(影印版)(英文版) 目錄

Preface 1 Why Quantum Computing? 1.1 The mysterious quantum bit 1.2 I'm awake! 1.3 Why quantum computing is different 1.4 Applications to artificial intelligence 1.5 Applications to financial services 1.6 What about cryptography? 1.7 Summary I Foundations 2 They're Not Old, They're Classics 2.1 What's inside a computer? 2.2 The power of two 2.3 True or false? 2.4 Logic circuits 2.5 Addition, logically 2.6 Algorithmically speaking 2.7 Growth, exponential and otherwise 2.8 How hard can that be? 2.8.1 Sorting 2.8.2 Searching 2.9 Summary 3 More Numbers than You Can Imagine 3.1 Natural numbers 3.2 Whole numbers 3.3 Integers 3.4 Rational numbers 3.4.1 Fractions 3.4.2 Getting formal again 3.5 Real numbers 3.5.1 Decimals 3.5.2 Irrationals and limits 3.5.3 Binary forms 3.5.4 Continued fractions 3.6 Structure 3.6.1 Groups 3.6.2 Rings 3.6.3 Fields 3.6.4 Even greater abstraction 3.7 Modular arithmetic 3.8 Doubling down 3.9 Complex numbers, algebraically 3.9.1 Arithmetic 3.9.2 Conjugation 3.9.3 Units 3.9.4 Polynomials and roots 3.10 Summary 4 Planes and Circles and Spheres, Oh My 4.1 Functions 4.2 The real plane 4.2.1 Moving to two dimensions 4.2.2 Distance and length 4.2.3 Geometric figures in the real plane 4.2.4 Exponentials and logarithms 4.3 Trigonometry 4.3.1 The fundamental functions 4.3.2 The inverse functions 4.3.3 Additional identities 4.4 From Cartesian to polar coordinates 4.5 The complex "plane" 4.6 Real three dimensions 4.7 Summary 5 Dimensions 6 What Do You Mean "Probably"? II Quantum Computing 7 One Qubit 8 Two Qubits, Three 9 Wirina Up the Circuits 10 From Circuits to Algorithms 11 Getting Physical 12 Questions about the Future Afterword Appendices A Quick Reference B Symbols C Notices D Production Notes Other Books You May Enjoy Index
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學(xué)習(xí)量子比特(影印版)(英文版) 作者簡介

羅伯特·S.薩托 has been a technical leader and executive in the IT industry for over 30 years. More than two decades of that have been spent in IBM Research in New York. During his time there, he worked on or led efforts in symbolic mathematical computation, optimization, AI, blockchain, and quantum computing. He is the co-author of several research papers and the book Axiom: The Scientific Computation System with the late Richard D. Jenks. He also was an executive on the software side of the business in areas including emerging industry standards, software on Linux, mobile, and open source. He's a theoretical mathematician by training, has a Ph.D. from Princeton University, and an undergraduate degree from Harvard College. He started coding when he was 15 and has used most of the programming languages that have come along.

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