Passer à la navigation principale Passer à la recherche Passer au contenu principal

Quantum Computing for Finance: State-of-the-Art and Future Prospects

  • Daniel J. Egger
  • , Claudio Gambella
  • , Jakub Marecek
  • , Scott McFaddin
  • , Martin Mevissen
  • , Rudy Raymond
  • , Andrea Simonetto
  • , Stefan Woerner
  • , Elena Yndurain
  • S.
  • IBM Research Ireland
  • IBM Watson Research Center
  • MIT Computer Science & Artificial Intelligence Laboratory
  • Tokyo Research Laboratory
  • International Business Machines

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

Résumé

This article outlines our point of view regarding the applicability, state-of-the-art, and potential of quantum computing for problems in finance. We provide an introduction to quantum computing as well as a survey on problem classes in finance that are computationally challenging classically and for which quantum computing algorithms are promising. In the main part, we describe in detail quantum algorithms for specific applications arising in financial services, such as those involving simulation, optimization, and machine learning problems. In addition, we include demonstrations of quantum algorithms on IBM Quantum back-ends and discuss the potential benefits of quantum algorithms for problems in financial services. We conclude with a summary of technical challenges and future prospects.

langue originaleAnglais
Numéro d'article3101724
journalIEEE Transactions on Quantum Engineering
Volume1
Les DOIs
étatPublié - 1 janv. 2020
Modification externeOui

Empreinte digitale

Examiner les sujets de recherche de « Quantum Computing for Finance: State-of-the-Art and Future Prospects ». Ensemble, ils forment une empreinte digitale unique.

Contient cette citation