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Financial Modeling Using Quantum Computing

You're reading from   Financial Modeling Using Quantum Computing Design and manage quantum machine learning solutions for financial analysis and decision making

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Product type Paperback
Published in May 2023
Publisher Packt
ISBN-13 9781804618424
Length 292 pages
Edition 1st Edition
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Authors (4):
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Iraitz Montalban Iraitz Montalban
Author Profile Icon Iraitz Montalban
Iraitz Montalban
Anshul Saxena Anshul Saxena
Author Profile Icon Anshul Saxena
Anshul Saxena
Javier Mancilla Javier Mancilla
Author Profile Icon Javier Mancilla
Javier Mancilla
Christophe Pere Christophe Pere
Author Profile Icon Christophe Pere
Christophe Pere
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Toc

Table of Contents (16) Chapters Close

Preface 1. Part 1: Basic Applications of Quantum Computing in Finance
2. Chapter 1: Quantum Computing Paradigm FREE CHAPTER 3. Chapter 2: Quantum Machine Learning Algorithms and Their Ecosystem 4. Chapter 3: Quantum Finance Landscape 5. Part 2: Advanced Applications of Quantum Computing in Finance
6. Chapter 4: Derivative Valuation 7. Chapter 5: Portfolio Management 8. Chapter 6: Credit Risk Analytics 9. Chapter 7: Implementation in Quantum Clouds 10. Part 3: Upcoming Quantum Scenario
11. Chapter 8: Simulators and HPC’s Role in the NISQ Era 12. Chapter 9: NISQ Quantum Hardware Roadmap 13. Chapter 10: Business Implementation 14. Index 15. Other Books You May Enjoy

Circuit knitting

Circuit knitting was proposed recently (Piveteau and Sutter 2022), given the complexity of providing larger chips without introducing large amounts of errors. Instead of aiming for larger, fully quantum chips, you could think of distributed resource systems where these instances are classically connected.

This type of architecture has been exploited in the field of distributed GPU computing (Gu et al. 2019), distributed computing for big data (Zaharia et al. 2012), and even edge computation (Shi 2016). However, it does not entail a paradigm shift from classical to quantum as all these resources work, let’s say, at the same physical level.

The main difference between those approaches and circuit knitting is the need to split a quantum circuit that would classically communicate with other parts of the circuit. Assuming there is a group of gates that could minimize the cut between two groups of more densely connected operations, you could split the circuit...

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