A Practical Guide to Quantum Machine Learning and Quantum Optimization Hands-On Approach to Modern Quantum Algorithms
This book also shows you how to train quantum machine learning models, such as quantum support vector machines, quantum neural networks, and quantum generative adversarial networks. The book takes a straightforward path to help you learn about quantum algorithms, illustrating them with code that...
| Main Authors: | , |
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| Other Authors: | |
| Format: | eBook |
| Language: | English |
| Published: |
Birmingham
Packt Publishing, Limited
2023
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| Edition: | 1st edition |
| Subjects: | |
| Online Access: | |
| Collection: | O'Reilly - Collection details see MPG.ReNa |
Table of Contents:
- Running constrained problems on quantum annealers
- Solving optimization problems on quantum annealers with Leap
- The Leap annealers
- Embeddings and annealer topologies
- Controlling annealing parameters
- The importance of coupling strengths
- Classical and hybrid samplers
- Classical solvers
- Hybrid solvers
- Summary
- Chapter 5: QAOA: Quantum Approximate Optimization Algorithm
- From adiabatic computing to QAOA
- Discretizing adiabatic quantum computing
- QAOA: The algorithm
- Circuits for QAOA
- Estimating the energy
- QUBO and HOBO
- Using QAOA with Qiskit
- Cover
- Title Page
- Copyright and Credits
- Foreword
- Acknowledgements
- Table of Contents
- Preface
- Part 1: I, for One, Welcome our New Quantum Overlords
- Chapter 1: Foundations of Quantum Computing
- Quantum computing: the big picture
- The basics of the quantum circuit model
- Working with one qubit and the Bloch sphere
- What is a qubit?
- Dirac notation and inner products
- One-qubit quantum gates
- The Bloch sphere and rotations
- Hello, quantum world!
- Working with two qubits and entanglement
- Two-qubit states
- Two-qubit gates: tensor products
- The CNOT gate
- Entanglement
- The no-cloning theorem
- Controlled gates
- Hello, entangled world!
- Working with multiple qubits and universality
- Multi-qubit systems
- Multi-qubit gates
- Universal gates in quantum computing
- Summary
- Chapter 2: The Tools of the Trade in Quantum Computing
- Tools for quantum computing: a non-exhaustive overview
- A non-exhaustive survey of frameworks and platforms
- Qiskit, PennyLane, and Ocean
- Working with Qiskit
- An overview of the Qiskit framework
- Using Qiskit Terra to build quantum circuits
- Initializing circuits
- Quantum gates
- Measurements
- Using Qiskit Aer to simulate quantum circuits
- Let's get real: using IBM Quantum
- Working with PennyLane
- Circuit engineering 101
- PennyLane's interoperability
- Love is in the Aer
- Connecting to IBMQ
- Summary
- Part 2: When Time is Gold: Tools for Quantum Optimization
- Chapter 3: Working with Quadratic Unconstrained Binary Optimization Problems
- The Max-Cut problem and the Ising model
- Graphs and cuts
- Formulating the problem
- The Ising model
- Enter quantum: formulating optimization problems the quantum way
- From classical variables to qubits
- Computing expectation values with Qiskit
- Moving from Ising to QUBO and back
- Combinatorial optimization problems with the QUBO model
- Binary linear programming
- The Knapsack problem
- Graph coloring
- The Traveling Salesperson Problem
- Other problems and other formulations
- Summary
- Chapter 4: Adiabatic Quantum Computing and Quantum Annealing
- Adiabatic quantum computing
- Quantum annealing
- Using Ocean to formulate and transform optimization problems
- Constrained quadratic models in Ocean
- Solving constrained quadratic models with dimod