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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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Table of Contents (21) Chapters Close

Preface 1. Chapter 1 The Principles of Quantum Mechanics FREE CHAPTER 2. Part I Analog Quantum Computing – Quantum Annealing
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

6.5 Entanglement

The key aspect of quantum computing is entanglement, which allows for quantum states to encode more information than the sum of their individual components. We explain this in detail here and provide examples for two-qubit systems.

6.5.1 Quantum entanglement and why it matters

An n-qubit system can exist in any superposition of the 2n basis states:

 n 2∑ −1 ci |i⟩ = c0 |00...00⟩ + c1 |00...01⟩+ ...+ c2n−1 |11 ...11⟩, i=0

with

2n∑−1 |ci|2 = 1. i=0

If such a state can be represented as a tensor product of individual qubit states, then the qubit states are not entangled. For example, it is easy to check that

--1- 4 √2-(√ -- √ -- √ -- √ -- ) 3 |000⟩+ |001⟩ + 3 |010⟩+ 3 |011⟩ + 3 |100⟩+ |101⟩+ 3 |110⟩+ 3 |111⟩
= ( ) √1--|0⟩+ √1-|1⟩ 2 2( √ -- ) 1-|0⟩ + --3 |1⟩ 2 2( √ -- ) --3 |0⟩ + 1-|1⟩ 2 2, (6.5.1)

so that the quantum state is not entangled (only in superposition). An entangled state cannot be represented as a tensor product of individual qubit states.

For example, the two-qubit state

√1-|00⟩+ 1√--|11⟩ 2 2

does not allow a tensor product decomposition. Namely, for any a,b,c,d such that |a|2 + |b|2 = |c|2 + |d|2 = 1, we have

-1- -1- √2-|00⟩+ √2--|11⟩ ⁄= (a |0⟩ + b |1⟩)⊗ (c |0⟩+ d |1⟩).

We notice that we need 2n probability amplitudes to describe...

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