Dancing with Qubits From Qubits to Algorithms, Embark on the Quantum Computing Journey Shaping Our Future
Dancing with Qubits, Second Edition, is a comprehensive quantum computing textbook that starts with an overview of why quantum computing is so different from classical computing and describes several industry use cases where it can have a major impact. A full description of classical computing and t...
| Autor principal: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing, Limited
2024.
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| Edición: | 2nd ed |
| Colección: | Expert insight.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009810645006719 |
Tabla de Contenidos:
- Intro
- Copyright
- Contributors
- Contents
- Preface
- I Foundations
- 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
- 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?
- 2.9 Summary
- 3 More Numbers Than You Can Imagine
- 3.1 Natural numbers
- 3.2 Whole numbers
- 3.3 Integers
- 3.4 Rational numbers
- 3.5 Real numbers
- 3.6 Structure
- 3.7 Modular arithmetic
- 3.8 Doubling down
- 3.9 Complex numbers, algebraically
- 3.10 Summary
- 4 Planes and Circles and Spheres, Oh My
- 4.1 Functions
- 4.2 The real plane
- 4.3 Trigonometry
- 4.4 From Cartesian to polar coordinates
- 4.5 The complex ``plane''
- 4.6 Real three dimensions
- 4.7 Summary
- 5 Dimensions
- 5.1 R2 and C1
- 5.2 Vector spaces
- 5.3 Linear maps
- 5.4 Matrices
- 5.5 Matrix algebra
- 5.6 The determinant and trace
- 5.7 Length and preserving it
- 5.8 Unitary transformations
- 5.9 Change of basis
- 5.10 Eigenvectors and eigenvalues
- 5.11 Direct sums
- 5.12 Homomorphisms
- 5.13 Systems of linear equations
- 5.14 Summary
- 6 What Do You Mean ``Probably''?
- 6.1 Being discrete
- 6.2 More formally
- 6.3 Wrong again?
- 6.4 Probability and error detection
- 6.5 Randomness
- 6.6 Expectation
- 6.7 Hellinger distance
- 6.8 Markov and Chebyshev go to the casino
- 6.9 Summary
- II Quantum Computing
- 7 One Qubit
- 7.1 Introducing quantum bits
- 7.2 Bras and kets
- 7.3 The complex math and physics of a single qubit.
- 7.4 A nonlinear projection
- 7.5 The Bloch sphere
- 7.6 Professor Hadamard, meet Professor Pauli
- 7.7 Gates and unitary matrices
- 7.8 Summary
- 8 Two Qubits, Three
- 8.1 Tensor products
- 8.2 Entanglement
- 8.3 Multi-qubit gates
- 8.4 The cat
- 8.5 Summary
- 9 Wiring Up the Circuits
- 9.1 So many gates
- 9.2 From gates to circuits
- 9.3 Building blocks and universality
- 9.4 Arithmetic
- 9.5 Welcome to Delphi
- 9.6 Amplitude amplification and interference
- 9.7 Searching with Grover
- 9.8 The Deutsch-Jozsa algorithm
- 9.9 The Bernstein-Vazirani algorithm
- 9.10 Simon's algorithm
- 9.11 Summary
- 10 From Circuits to Algorithms
- 10.1 Quantum Fourier Transform
- 10.2 Factoring
- 10.3 How hard can that be, again?
- 10.4 Phase kickback
- 10.5 Eigenvalue and phase estimation
- 10.6 Order and period finding
- 10.7 Shor's factoring algorithm
- 10.8 Summary
- 11 Getting Physical
- 11.1 That's not logical
- 11.2 What does it take to be a qubit?
- 11.3 Quantum cores and interconnects
- 11.4 Decoherence
- 11.5 Error correction for physical qubits
- 11.6 Quantum benchmarks
- 11.7 The software stack and access
- 11.8 Simulation
- 11.9 Light and photons
- 11.10 Summary
- III Advanced Topics
- 12 Considering NISQ Algorithms
- 12.1 Cost functions and optimization
- 12.2 Heuristics
- 12.3 Hermitian matrices again
- 12.4 Expectation and the variational principle
- 12.5 Time evolution
- 12.6 Parameterized circuits
- 12.7 The Hamiltonian
- 12.8 Quantum approximate optimization algorithm (QAOA)
- 12.9 Is NISQ worth it?
- 12.10 Summary
- 13 Introduction to Quantum Machine Learning
- 13.1 What is machine learning?
- 13.2 Methods for encoding data
- 13.3 Quantum neural networks
- 13.4 Quantum kernels for SVMs
- 13.5 Other quantum machine learning research areas
- 13.6 Summary
- 14 Questions about the Future.
- 14.1 Ecosystem and community
- 14.2 Applications and strategy
- 14.3 Computing system access
- 14.4 Software
- 14.5 Hardware
- 14.6 Education
- 14.7 Workforce
- 14.8 Summary
- Afterword
- Appendices
- A Quick Reference
- A.1 One qubit kets
- A.2 Two qubit kets
- A.3 Pauli gates and matrices
- A.4 Pauli strings of length 2
- A.5 Greek letters
- B Notices
- B.1 Photos, images, and diagrams
- B.2 Marks
- B.3 Creative Commons Attribution-NoDerivs 2.0 Generic
- B.4 Creative Commons Attribution-ShareAlike 2.0 Germany
- B.5 Creative Commons Attribution 3.0 Unported
- B.6 Creative Commons Attribution-ShareAlike 3.0 Unported
- B.7 Los Alamos National Laboratory
- B.8 Python 3 license
- C Production Notes
- C.1 How this book was built
- C.2 Citing this book
- C.3 Python version
- C.4 LaTeX environment
- Other Books You May Enjoy
- References
- Index
- Share your thoughts
- Download a free PDF copy of this book
- Other Books You May Enjoy
- Index
- Blank Page.
