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Quantum Machine Learning and Optimisation in Finance

You're reading from   Quantum Machine Learning and Optimisation in Finance Drive financial innovation with quantum-powered algorithms and optimisation strategies

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Product type Paperback
Published in Dec 2024
Publisher Packt
ISBN-13 9781836209614
Length 494 pages
Edition 2nd Edition
Languages
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Authors (2):
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Jacquier Antoine Jacquier Antoine
Author Profile Icon Jacquier Antoine
Jacquier Antoine
Alexei Kondratyev Alexei Kondratyev
Author Profile Icon Alexei Kondratyev
Alexei Kondratyev
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Toc

Table of Contents (21) Chapters Close

Preface 1. Chapter 1 The Principles of Quantum Mechanics 2. Part I Analog Quantum Computing – Quantum Annealing FREE CHAPTER
3. Chapter 2 Adiabatic Quantum Computing 4. Chapter 3 Quadratic Unconstrained Binary Optimisation 5. Chapter 4 Quantum Boosting 6. Chapter 5 Quantum Boltzmann Machine 7. Part II Gate Model Quantum Computing
8. Chapter 6 Qubits and Quantum Logic Gates 9. Chapter 7 Parameterised Quantum Circuits and Data Encoding 10. Chapter 8 Quantum Neural Network 11. Chapter 9 Quantum Circuit Born Machine 12. Chapter 10 Variational Quantum Eigensolver 13. Chapter 11 Quantum Approximate Optimisation Algorithm 14. Chapter 12 Quantum Kernels and Quantum Two-Sample Test 15. Chapter 13 The Power of Parameterised Quantum Circuits 16. Chapter 14 Advanced QML Models 17. Chapter 15 Beyond NISQ 18. Bibliography
19. Index 20. Other Books You Might Enjoy

Summary

In this chapter, we covered several important quantum algorithms that rely on the existence of a quantum computing hardware with characteristics that exceed the capabilities of currently available NISQ computers. However, the very presence of these algorithms and their potential to achieve quadratic or even exponential speedup provides strong motivation for the rapid development of quantum computers.

This chapter completes the book. Looking ahead, we see a bright future for quantum computing. In the update to their quantum computing development roadmap [154], IBM outlined an exciting vision with the goal of building quantum-centric supercomputers. This will incorporate quantum processors, classical processors, quantum communication networks, and classical networks. The most recent deliverables include 433-qubit Osprey processor (released in 2022) and 1,121-qubit Condor processor (released in 2023). The next step is the development of ways to link processors together into...

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