Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Quantum Computing and its potential for industrial applications

Sabine Wölk

Published Jan 1, 2025• 0 citations
OpenAlex

Related papers

A Structured Survey of Quantum Computing for the Financial Industry

Franco D. Albareti, Thomas Ankenbrand, Denis Bieri +4 more

Quantum computers can solve specific problems that are not feasible on "classical" hardware. Harvesting the speed-up provided by quantum computers therefore has the potential to change any industry which uses computation, including finance. First quantum applications for the financial industry involving optimization, simulation, and machine learning problems have already been proposed and applied to use cases such as portfolio management, risk management, and pricing derivatives. This survey reviews platforms, algorithms, methodologies, and use cases of quantum computing for various applications in finance in a structured way. It is aimed at people working in the financial industry and serves to gain an overview of the current development and capabilities and understand the potential of quantum computing in the financial industry.

arXiv:2204.10026•Apr 21, 2022•7 citations

Analysis of quantum computing industrial developments and applications

Haiyi Zhang, Xiao Cui, WU Bingbing

Information and Communications Technology and Policy•Jul 15, 2020•0 citations

Quantum Computing Applications in Engineering: Current Status and Future Prospects

Syivesh Rukmanikanthan, Hayana Dullah, Yun Xin Teoh +1 more

Archives of Computational Methods in Engineering•May 28, 2026•1 citation

Practical Applications of Quantum Computing: An Interview with D-Wave Systems CEO Vern Brownell

Vern Brownell

Quantum computing (QC) is based in the fundamental laws of the universe. Although still in its infancy, this emerging field is showing great promise in benchmark tests on processing speed, and it holds great potential for the financial industry in computationally intensive applications. These include derivatives analysis, valuation of complex instruments and various forms of optimization. Vern Brownell, CEO of D-Wave Systems and an industry leader in the field of quantum computing, will be speaking at Global Derivatives in Budapest. In this pre-conference interview with Institutional Investor Journals, Brownell outlines the current uses for quantum computing and his vision for the role of quantum computers in the finance industry.

Practical Applications•May 6, 2016•0 citations

Quantum Computing: Applications and Future Trends

Siddharth Kote, Dnyaneshwar Kshirsagar, Raj B. Kulkarni +3 more

•Jan 1, 2023•2 citations

$$\mathrm{Q(AI)}^2$$: Quantum Artificial Intelligence for the Automotive Industry

Tobias Stollenwerk, Somtapa Bhattacharya, Michele Cattelan +15 more

The goal of the project \(\mathrm{Q(AI)}^2\) was to acquire a broader basis of quantum computing enhanced AI and optimization algorithms for potential applications in the automotive industry. In particular, we strove to assess the potential for quantum advantage for specific use cases from the automotive industry. For this, we developed quantum algorithmic solutions tailored both to the available hardware as well as to the industrial problems at hand. In addition, we ensured industrial relevance of the investigated applications by the constitution of the consortium, involving all three large German car manufactures VW, Mercedes-Benz and BMW as well as Bosch as a central component supplier. Forschungszentrum Jülich and the German Center for Artificial Intelligence (DFKI) provided the necessary expertise in AI and quantum computing methods.

Künstliche Intell.•Jul 17, 2024•0 citations
Quantum computers can solve specific problems that are not feasible on "classical" hardware. Harvesting the speed-up provided by quantum computers therefore has the potential to change any industry which uses computation, including finance. First quantum applications for the financial industry involving optimization, simulation, and machine learning problems have already been proposed and applied to use cases such as portfolio management, risk management, and pricing derivatives. This survey reviews platforms, algorithms, methodologies, and use cases of quantum computing for various applications in finance in a structured way. It is aimed at people working in the financial industry and serves to gain an overview of the current development and capabilities and understand the potential of quantum computing in the financial industry.
Quantum computing (QC) is based in the fundamental laws of the universe. Although still in its infancy, this emerging field is showing great promise in benchmark tests on processing speed, and it holds great potential for the financial industry in computationally intensive applications. These include derivatives analysis, valuation of complex instruments and various forms of optimization. Vern Brownell, CEO of D-Wave Systems and an industry leader in the field of quantum computing, will be speaking at Global Derivatives in Budapest. In this pre-conference interview with Institutional Investor Journals, Brownell outlines the current uses for quantum computing and his vision for the role of quantum computers in the finance industry.
Q(AI)2\mathrm{Q(AI)}^2Q(AI)2: Quantum Artificial Intelligence for the Automotive Industry
The goal of the project Q(AI)2\mathrm{Q(AI)}^2Q(AI)2 was to acquire a broader basis of quantum computing enhanced AI and optimization algorithms for potential applications in the automotive industry. In particular, we strove to assess the potential for quantum advantage for specific use cases from the automotive industry. For this, we developed quantum algorithmic solutions tailored both to the available hardware as well as to the industrial problems at hand. In addition, we ensured industrial relevance of the investigated applications by the constitution of the consortium, involving all three large German car manufactures VW, Mercedes-Benz and BMW as well as Bosch as a central component supplier. Forschungszentrum Jülich and the German Center for Artificial Intelligence (DFKI) provided the necessary expertise in AI and quantum computing methods.