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Quantum Computing Experimentation with Amazon Braket

You're reading from   Quantum Computing Experimentation with Amazon Braket Explore Amazon Braket quantum computing to solve combinatorial optimization problems

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Product type Paperback
Published in Jul 2022
Publisher Packt
ISBN-13 9781800565265
Length 420 pages
Edition 1st Edition
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Author (1):
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Alex Khan Alex Khan
Author Profile Icon Alex Khan
Alex Khan
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Table of Contents (19) Chapters Close

Preface 1. Introduction
2. Section 1: Getting Started with Amazon Braket FREE CHAPTER
3. Chapter 1: Setting Up Amazon Braket 4. Chapter 2: Braket Devices Explained 5. Chapter 3: User Setup, Tasks, and Understanding Device Costs 6. Chapter 4: Writing Your First Amazon Braket Code Sample 7. Section 2: Building Blocks for Real-World Use Cases
8. Chapter 5: Using a Quantum Annealer – Developing a QUBO Function and Applying Constraints 9. Chapter 6: Using Gate-Based Quantum Computers – Qubits and Quantum Circuits 10. Chapter 7: Using Gate Quantum Computers – Basic Quantum Algorithms 11. Chapter 8: Using Hybrid Algorithms – Optimization Using Gate-Based Quantum Computers 12. Chapter 9: Running QAOA on Simulators and Amazon Braket Devices 13. Section 3: Real-World Use Cases
14. Chapter 10: Amazon Braket Hybrid Jobs, PennyLane, and other Braket Features 15. Chapter 11: Single-Objective Optimization Use Case 16. Chapter 12: Multi-Objective Optimization Use Case 17. Other Books You May Enjoy Appendix: Knapsack BQM Derivation

Summary

In this chapter, we solved the knapsack problem, which represents a very simple real-world problem, on various Amazon Braket devices and suggested a process for developing and solving similar problems. Many real-world problems can be mapped to one of many types of knapsack problem formulations and the more elaborate bin packing problems formulations. The 0/1 knapsack formulation, with its binary item variable, single objective, and single integer weight constraint, is a good foundational problem to evaluate how to build a QUBO formulation. This in itself is a mathematically intensive process and requires various device and hardware-specific parameter fine-tuning to ensure the formulation will give the desired results. We tested our formulation classically and then ensured our QUBO formulation gave the best result. Next, we evaluated the QUBO formulation development on various Amazon Braket devices. We also reviewed a suggested step-by-step framework for solving such problems...

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