Quantum Machine Learning and Optimisation in Finance: On the Road to Quantum Advantage (Paperback)
暫譯: 金融中的量子機器學習與優化:邁向量子優勢之路 (平裝本)

Jacquier, Antoine, Kondratyev, Oleksiy

  • 出版商: Packt Publishing
  • 出版日期: 2022-10-31
  • 售價: $2,230
  • 貴賓價: 9.5$2,119
  • 語言: 英文
  • 頁數: 442
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1801813574
  • ISBN-13: 9781801813570
  • 相關分類: Machine Learning量子 Quantum
  • 立即出貨 (庫存=1)

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商品描述

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 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 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!

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.

商品描述(中文翻譯)

學習量子機器學習的原則以及如何將其應用於金融領域。

購買印刷版或 Kindle 版書籍可獲得免費的 PDF 格式電子書。

主要特色

- 探索如何在量子電腦上解決優化問題,這些問題能提供比傳統方法更快的速度優勢
- 使用類比和數位量子計算的方法來構建強大的生成模型
- 創建可在噪聲中等規模量子(NISQ)電腦上運行的最新算法

書籍描述

隨著量子計算技術的最新進展,我們終於來到了噪聲中等規模量子(NISQ)計算的時代。NISQ 時代的量子電腦足夠強大,可以測試量子計算算法並比傳統硬體更快地解決困難的現實問題。

在金融應用中,速度提升是非常重要的,範圍從分析大量客戶數據到高頻交易。這正是量子計算能為您提供優勢的地方。《金融中的量子機器學習與優化》向您展示如何創建混合量子-經典機器學習和優化模型,以利用 NISQ 硬體的力量。

本書將帶您了解量子計算的現實生產應用。書中探討了可在現有 NISQ 設備上實現的主要量子計算算法,並突顯了一系列可以從這種新量子計算範式中受益的金融應用。

本書將幫助您成為金融行業中首批使用量子機器學習模型來解決傳統上困難的現實問題的人之一。我們可能已經超越了量子計算優越性的時期,但我們建立量子計算優勢的探索才剛剛開始!

您將學到的內容

- 訓練參數化的量子電路作為在 NISQ 硬體上表現優異的生成模型
- 解決困難的優化問題
- 將量子增強應用於金融應用
- 學習變分量子特徵求解器和量子近似優化算法的工作原理
- 分析從量子核到量子半正定編程的最新算法
- 將量子神經網絡應用於信用批准

本書適合對象

本書適合量化分析師、開發人員、數據科學家、研究人員以及量化金融的學生。雖然重點在於金融用例,但所有方法和技術都可以轉移到其他領域。

目錄大綱

  1. The Principles of Quantum Mechanics
  2. Adiabatic Quantum Computing
  3. Quadratic Unconstrained Binary Optimisation
  4. Quantum Boosting
  5. Quantum Boltzmann Machine
  6. Qubits and Quantum Logic Gates
  7. Parameterised Quantum Circuits and Data Encoding
  8. Quantum Neural Network
  9. Quantum Circuit Born Machine
  10. Variational Quantum Eigensolver
  11. Quantum Approximate Optimisation Algorithm
  12. The Power of Parameterised Quantum Circuits
  13. Looking Ahead
  14. Bibliography

目錄大綱(中文翻譯)


  1. The Principles of Quantum Mechanics

  2. Adiabatic Quantum Computing

  3. Quadratic Unconstrained Binary Optimisation

  4. Quantum Boosting

  5. Quantum Boltzmann Machine

  6. Qubits and Quantum Logic Gates

  7. Parameterised Quantum Circuits and Data Encoding

  8. Quantum Neural Network

  9. Quantum Circuit Born Machine

  10. Variational Quantum Eigensolver

  11. Quantum Approximate Optimisation Algorithm

  12. The Power of Parameterised Quantum Circuits

  13. Looking Ahead

  14. Bibliography