Book Image

Quantum Machine Learning and Optimisation in Finance

By : Antoine Jacquier, Oleksiy Kondratyev
Book Image

Quantum Machine Learning and Optimisation in Finance

By: Antoine Jacquier, Oleksiy Kondratyev

Overview of this book

With recent advances in quantum computing technology, we finally reached the era of Noisy Intermediate-Scale Quantum (NISQ) computing. NISQ-era quantum computers are powerful enough to test quantum computing algorithms and solve hard real-world problems faster than classical hardware. Speedup is so important in financial applications, ranging from analysing huge amounts of customer data to high frequency trading. This is where quantum computing can give you the edge. Quantum Machine Learning and Optimisation in Finance shows you how to create hybrid quantum-classical machine learning and optimisation models that can harness the power of NISQ hardware. This book will take you through the real-world productive applications of quantum computing. The book explores the main quantum computing algorithms implementable on existing NISQ devices and highlights a range of financial applications that can benefit from this new quantum computing paradigm. This book will help you be one of the first in the finance industry to use quantum machine learning models to solve classically hard real-world problems. We may have moved past the point of quantum computing supremacy, but our quest for establishing quantum computing advantage has just begun!
Table of Contents (4 chapters)

13
Looking Ahead

The first generation of quantum algorithms appeared in the 1990s when quantum computers existed only as a concept. On the one hand, the absence of actual quantum hardware was a huge disadvantage since it made direct experiments impossible; on the other hand, it stimulated theoretical research not inhibited by the limitations and constraints of the imperfect early quantum computers. Researchers focused on devising algorithms that would achieve quadratic or even exponential speedup, assuming that powerful, error-free quantum computers would be available one day. It was the time when Shor’s prime factorisation algorithm  [265] and Grover’s search algorithm  [117] were discovered. Incidentally, as the book was about to be released, Peter Shor was named one of the four recipients of the 2022 Breakthrough Prize in Fundamental Physics (along with C. H. Bennett, G. Brassard, and D. Deutsch) for their foundational work in quantum information....