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Programming Quantum Computers. Essential Algorithms and Code Samples - Helion

Programming Quantum Computers. Essential Algorithms and Code Samples
ebook
Autor: Eric R. Johnston, Nic Harrigan, Mercedes Gimeno-Segovia
ISBN: 978-14-920-3963-1
stron: 336, Format: ebook
Data wydania: 2019-07-03
Księgarnia: Helion

Cena książki: 211,65 zł (poprzednio: 246,10 zł)
Oszczędzasz: 14% (-34,45 zł)

Dodaj do koszyka Programming Quantum Computers. Essential Algorithms and Code Samples

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.

Dodaj do koszyka Programming Quantum Computers. Essential Algorithms and Code Samples

 

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Dodaj do koszyka Programming Quantum Computers. Essential Algorithms and Code Samples

Spis treści

Programming Quantum Computers. Essential Algorithms and Code Samples eBook -- spis treści

  • Preface
    • How This Book Is Structured
    • Conventions Used in This Book
    • Using Code Examples
    • OReilly Online Learning
    • How to Contact Us
    • Acknowledgments
  • 1. Introduction
    • Required Background
    • What Is a QPU?
    • A Hands-on Approach
      • A QCEngine Primer
        • Running code
        • Debugging code
    • Native QPU Instructions
      • Simulator Limitations
      • Hardware Limitations
    • QPU Versus GPU: Some Common Characteristics
  • I. Programming for a QPU
  • 2. One Qubit
    • A Quick Look at a Physical Qubit
    • Introducing Circle Notation
      • Circle Size
      • Circle Rotation
    • The First Few QPU Operations
      • QPU Instruction: NOT
      • QPU Instruction: HAD
      • QPU Instruction: READ
      • QPU Instruction: WRITE
      • Hands-on: A Perfectly Random Bit
      • QPU Instruction: PHASE()
      • QPU Instructions: ROTX() and ROTY()
    • COPY: The Missing Operation
    • Combining QPU Operations
      • QPU Instruction: ROOT-of-NOT
    • Hands-on: Quantum Spy Hunter
    • Conclusion
  • 3. Multiple Qubits
    • Circle Notation for Multi-Qubit Registers
    • Drawing a Multi-Qubit Register
    • Single-Qubit Operations in Multi-Qubit Registers
      • Reading a Qubit in a Multi-Qubit Register
    • Visualizing Larger Numbers of Qubits
    • QPU Instruction: CNOT
    • Hands-on: Using Bell Pairs for Shared Randomness
    • QPU Instructions: CPHASE and CZ
      • QPU Trick: Phase Kickback
    • QPU Instruction: CCNOT (Toffoli)
    • QPU Instructions: SWAP and CSWAP
      • The Swap Test
    • Constructing Any Conditional Operation
    • Hands-on: Remote-Controlled Randomness
    • Conclusion
  • 4. Quantum Teleportation
    • Hands-on: Lets Teleport Something
    • Program Walkthrough
      • Step 1: Create an Entangled Pair
      • Step 2: Prepare the Payload
      • Step 3.1: Link the Payload to the Entangled Pair
      • Step 3.2: Put the Payload into a Superposition
      • Step 3.3: READ Both of Alices Qubits
      • Step 4: Receive and Transform
      • Step 5: Verify the Result
    • Interpreting the Results
    • How Is Teleportation Actually Used?
    • Fun with Famous Teleporter Accidents
  • II. QPU Primitives
  • 5. Quantum Arithmetic and Logic
    • Strangely Different
    • Arithmetic on a QPU
      • Hands-on: Building Increment and Decrement Operators
    • Adding Two Quantum Integers
    • Negative Integers
    • Hands-on: More Complicated Math
    • Getting Really Quantum
      • Quantum-Conditional Execution
      • Phase-Encoded Results
    • Reversibility and Scratch Qubits
    • Uncomputing
    • Mapping Boolean Logic to QPU Operations
      • Basic Quantum Logic
    • Conclusion
  • 6. Amplitude Amplification
    • Hands-on: Converting Between Phase and Magnitude
    • The Amplitude Amplification Iteration
    • More Iterations?
    • Multiple Flipped Entries
    • Using Amplitude Amplification
      • AA and QFT as Sum Estimation
      • Speeding Up Conventional Algorithms with AA
    • Inside the QPU
      • The Intuition
    • Conclusion
  • 7. QFT: Quantum Fourier Transform
    • Hidden Patterns
    • The QFT, DFT, and FFT
    • Frequencies in a QPU Register
    • The DFT
      • Real and Complex DFT Inputs
      • DFT Everything
    • Using the QFT
      • The QFT Is Fast
        • Signal processing with the QFT
        • Preparing superpositions with the inverse QFT
    • Inside the QPU
      • The Intuition
      • Operation by Operation
        • Rotating each circles phase by a multiple of its value
        • Conditionally rotating by the angle n/2N × 360°
    • Conclusion
  • 8. Quantum Phase Estimation
    • Learning About QPU Operations
    • Eigenphases Teach Us Something Useful
    • What Phase Estimation Does
    • How to Use Phase Estimation
      • Inputs
      • Outputs
    • The Fine Print
      • Choosing the Size of the Output Register
      • Complexity
      • Conditional Operations
    • Phase Estimation in Practice
    • Inside the QPU
      • The Intuition
      • Operation by Operation
    • Conclusion
  • III. QPU Applications
  • 9. Real Data
    • Noninteger Data
    • QRAM
    • Vector Encodings
      • Limitations of Amplitude Encoding
        • Caveat 1: Beware of quantum outputs
        • Caveat 2: The requirement for normalized vectors
      • Amplitude Encoding and Circle Notation
    • Matrix Encodings
      • How Can a QPU Operation Represent a Matrix?
      • Quantum Simulation
        • The basic idea
        • How it works
        • Reconstruction
        • Deconstructing H
        • The cost of quantum simulation
  • 10. Quantum Search
    • Phase Logic
      • Building Elementary Phase-Logic Operations
      • Building Complex Phase-Logic Statements
    • Solving Logic Puzzles
      • Of Kittens and Tigers
    • General Recipe for Solving Boolean Satisfiability Problems
      • Hands-on: A Satisfiable 3-SAT Problem
      • Hands-on: An Unsatisfiable 3-SAT Problem
    • Speeding Up Conventional Algorithms
  • 11. Quantum Supersampling
    • What Can a QPU Do for Computer Graphics?
    • Conventional Supersampling
    • Hands-on: Computing Phase-Encoded Images
      • A QPU Pixel Shader
      • Using PHASE to Draw
      • Drawing Curves
    • Sampling Phase-Encoded Images
    • A More Interesting Image
    • Supersampling
    • QSS Versus Conventional Monte Carlo Sampling
      • How QSS Works
        • The QSS lookup table
        • Confidence maps
    • Adding Color
    • Conclusion
  • 12. Shors Factoring Algorithm
    • Hands-on: Using Shor on a QPU
    • What Shors Algorithm Does
      • Do We Need a QPU at All?
      • The Quantum Approach
    • Step by Step: Factoring the Number 15
      • Step 1: Initialize QPU Registers
      • Step 2: Expand into Quantum Superposition
      • Step 3: Conditional Multiply-by-2
      • Step 4: Conditional Multipy-by-4
      • Step 5: Quantum Fourier Transform
      • Step 6: Read the Quantum Result
      • Step 7: Digital Logic
      • Step 8: Check the Result
    • The Fine Print
      • Computing the Modulus
      • Time Versus Space
      • Coprimes Other Than 2
  • 13. Quantum Machine Learning
    • Solving Systems of Linear Equations
      • Describing and Solving Systems of Linear Equations
      • Solving Linear Equations with a QPU
        • What HHL does
          • Inputs
          • Outputs
          • Speed and fine print
        • Inside the box
          • 1. Quantum simulation, QRAM, and phase estimation
          • 2. Invert values
          • 3. Move inverted values into amplitudes
          • 4. Amplitude amplification
          • 5. Uncompute
    • Quantum Principle Component Analysis
      • Conventional Principal Component Analysis
      • PCA with a QPU
        • Representing a covariance matrix in a QPU register
        • Fixing problem 1
        • Fixing problem 2
        • The output
        • Performance
    • Quantum Support Vector Machines
      • Conventional Support Vector Machines
        • SVM generalizations
      • SVM with a QPU
        • Using a QPU to train a quantum SVM
          • Concern 1: Is F suitable for HHL?
          • Concern 2: How can we act F1 on [ 0 , y ] ?
          • Concern 3: How do we classify data?
    • Other Machine Learning Applications
  • IV. Outlook
  • 14. Staying on Top: A Guide to the Literature
    • From Circle Notation to Complex Vectors
    • Some Subtleties and Notes on Terminology
    • Measurement Basis
    • Gate Decompositions and Compilation
    • Gate Teleportation
    • QPU Hall of Fame
    • The Race: Quantum Versus Conventional Computers
    • A Note on Oracle-Based Algorithms
      • Deutsch-Jozsa
      • Bernstein-Vazirani
      • Simon
    • Quantum Programming Languages
    • The Promise of Quantum Simulation
    • Error Correction and NISQ Devices
    • Where Next?
      • Books
      • Lecture Notes
      • Online Resources
  • Index

Dodaj do koszyka Programming Quantum Computers. Essential Algorithms and Code Samples

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