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Financial Modeling Using Quantum Computing

You're reading from  Financial Modeling Using Quantum Computing

Product type Book
Published in May 2023
Publisher Packt
ISBN-13 9781804618424
Pages 292 pages
Edition 1st Edition
Languages
Authors (4):
Anshul Saxena Anshul Saxena
Profile icon Anshul Saxena
Javier Mancilla Javier Mancilla
Profile icon Javier Mancilla
Iraitz Montalban Iraitz Montalban
Profile icon Iraitz Montalban
Christophe Pere Christophe Pere
Profile icon Christophe Pere
View More author details

Table of Contents (16) Chapters

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

Further reading

Many providers are already shaping their offerings so that new as-a-service paradigms will emerge in the following years.

Oxford Quantum Circuits has already embraced the concept of Quantum Computing as a Service (QCaaS) (https://www.techradar.com/news/quantum-computing-as-a-service-is-going-mainstream), whereas other companies like QCentroid are targeting a wider audience by offering off-the-shelf solutions tailored to industry-specific applications through their Quantum-as-a-Service (QaaS) platform (https://marketplace.qcentroid.xyz/).

When thinking about cloud-accessible resources, one of the most interesting cases is the one posed by the variational quantum algorithm, where a constant interchange between classical and quantum resources must be sorted out. Given the queue times we have seen, we must be aware that any remote training of the ansatz will face important delays per iteration if we attempt to train on an actual device remotely.

Given the existing...

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