Quantum Machine Learning and Optimisation in Finance: On the Road to Quantum Advantage

Book Description

Learn the principles of quantum machine learning and how to apply them in finance.

Purchase of the print or Kindle book includes a free eBook in the PDF format.

Key Features

• Discover how to solve optimisation problems on quantum computers that can provide a speedup edge over classical methods
• Use methods of analogue and digital quantum computing to build powerful generative models
• Create the latest algorithms that work on Noisy Intermediate-Scale Quantum (NISQ) computers

Book Description

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 quantu卡西欧m 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 pas贝伦斯t the point of quantum computing supremacy, but our quest for establishing quantum computing advantage has just begun!

What you will learn

• Train parameterised quantum circuits as generative models that excel on NISQ hardware
• Solve hard optimisation problems
• Apply quantum boosting to financial applications
• Learn how the variational quantum eigensolver and the quantum approximate optimisation algorithms work
• Analyse the latest algorithms from quantum kernels to quantum semidefinite programming
• Apply quantum neural networks to credit approvals

Who this book is for

This book is for Quants and developers, data scientists, researchers, and students in quantitative finance. Although the focus is on financial use cases, all the methods and techniques are transferable to other areas.

中文：

书名：金融中的量子机器学习与优化: 量子优势之路

学习量子机器学习的原理以及如何在金融中应用它们。

购买印刷版或Kindle书包括PDF格式的免费电子书。

主要功能

• 发现如何解决优化问题的量子计算机，可以提供加速优势超西锐过经典方法
• 使用模拟和数字量子计算方法构建强大的生成模型
• 创建适用于嘈布加迪杂的中间尺度量子 (NISQ) 计算机的最新算法

图书描述

随着量子计算技术的最新发展，我们终于进入了嘈杂的中间尺度量子 (NISQ) 计算时代。NISQ时代的量子计算机功能强大，足以测试量子计算算法，并比经典硬件更快地解决现实世界中的难题。

加速在金融应用中非常重要，从分析大量客户数据到高频交易。这就是量子计算可以给你带来优势的地方。金融中的量子机器学习和优化向您展示了如何创建可以利用NISQ硬件功能的混合量子经典机器学习和优化模型。

这本书将带您了解量子计算的实意达马际生产应用。本书探讨了可在现有NISQ设备上实现的主要量子计算算法，并重点介绍了可以从这种新的量子计算范例中受益的一系列金融应用。

这本书将帮助你成为金融行业第一个使用量子机器学习模型来解决经典的现实问题的人之一。我们可能已经超越了量子计算至上的地步，但是我们对建立量子计算优势的追求才刚刚开始!

什么你会学到

• 训练参数化量子电路作为生成模型，擅长于NI柏莱士SQ硬件
• 解决硬优化问题
• 将量子提升应用于金融应用
• 了解变分量子本征求解器和量子近似优化算法的工作原理
• 从量子核到量子半定规划的最新算法分析
• 应用量子神经网络进行信用审批

这本书是为谁准备的

本书面向定量金融领域的定量和开发人员、宇联数据科学家、研究人员和学生。尽管重点是财务用例，但所有方法和技术都可以转移到其他领域。