(as of Nov 14,2022 23:35:53 UTC – Details)
From the Publisher
How can quantum computing transform the finance industry?
Quantum computation is more general than classical computation. Quantum computers can simulate classical computers; that is, they can perform all operations that are possible on classical computers. At the same time, the classical simulation of a quantum computer would immediately run into classical memory limits. This shows the enormous potential advantage of quantum computers over their classical counterparts. Some problems, such as in optimisation and machine learning algorithms, have already proved to be solvable with quadratic or even exponential quantum speedup. The field of quantitative finance, built on such methodologies and full of such classically hard problems, is thus an obvious playground of applications for quantum technologies. It is also hoped that new, powerful computers will give rise to new applications and services that we cannot envisage yet.
What applications do you cover in the book?
The book focuses on two main applications: optimisation and quantum machine learning. In some cases, classically hard combinatorial optimisation problems, such as discrete portfolio optimisation, can be solved efficiently on quantum computers. You’ll get a thorough overview of Parameterised Quantum Circuits (PQCs) – a quantum analogue to artificial neural networks, which can be trained as either discriminative or generative machine learning models. The book highlights their potential larger expressive power compared to their classical counterparts, along with showing you how to build a credit scoring model using a Quantum Neural Network trained as a classifier and how to generate synthetic market data with the help of the Quantum Circuit Born Machine. Furthermore, you’ll explore quantum algorithms such as the Variational Quantum Eigensolver and the Quantum Approximate Optimisation Algorithm in the context of NP-hard combinatorial optimisation problems.
Publisher : Packt Publishing (October 31, 2022)
Language : English
Paperback : 442 pages
ISBN-10 : 1801813574
ISBN-13 : 978-1801813570
Item Weight : 1.67 pounds
Dimensions : 7.5 x 1 x 9.25 inches