Book Image

Financial Modeling Using Quantum Computing

By : Anshul Saxena, Javier Mancilla, Iraitz Montalban, Christophe Pere
5 (1)
Book Image

Financial Modeling Using Quantum Computing

5 (1)
By: Anshul Saxena, Javier Mancilla, Iraitz Montalban, Christophe Pere

Overview of this book

Quantum computing has the potential to revolutionize the computing paradigm. By integrating quantum algorithms with artificial intelligence and machine learning, we can harness the power of qubits to deliver comprehensive and optimized solutions for intricate financial problems. This book offers step-by-step guidance on using various quantum algorithm frameworks within a Python environment, enabling you to tackle business challenges in finance. With the use of contrasting solutions from well-known Python libraries with quantum algorithms, you’ll discover the advantages of the quantum approach. Focusing on clarity, the authors expertly present complex quantum algorithms in a straightforward, yet comprehensive way. Throughout the book, you'll become adept at working with simple programs illustrating quantum computing principles. Gradually, you'll progress to more sophisticated programs and algorithms that harness the full power of quantum computing. By the end of this book, you’ll be able to design, implement and run your own quantum computing programs to turbocharge your financial modelling.
Table of Contents (16 chapters)
1
Part 1: Basic Applications of Quantum Computing in Finance
5
Part 2: Advanced Applications of Quantum Computing in Finance
10
Part 3: Upcoming Quantum Scenario

Local simulation of noise models

First, we must distinguish between the three naming conventions we will use during this chapter and the following ones. Previously, we talked about how quantum algorithms can be run on a classical device before being sent to a real quantum device, but there are some different ways in which this classical execution can be done. Problems such as the ones we have posed have been around for a while, and classical computing has evolved in many different ways to bring solutions to the technology at hand during this time. As we will see, this may also bring some challenges related to the specifics of the different classical setups we will cover. Mimicking quantum mechanical evolution is a non-trivial task; that was how quantum computing was proposed as a potential solution.

Simulators are the classical means of processing information in the way an ideal quantum computer would do so. Recall that quantum information theory is not a new task brought about...