Quantum computing applications
Quantum computing is described as a disruptive technology for numerous applications in industrial contexts or in academic research. Thus, it is expected that optimization problems can be solved more efficiently by using quantum computing, that quantum-based machine learning is superior to classical AI, and that quantum mechanical systems can be simulated more precisely.
In order to realize these advantages, considerable further development is still required not only in the hardware and software area, but also on the algorithm side. For this reason, scientists of the Munich Quantum Valley are working on the development of prototypical algorithms for potential applications of future quantum computers in the industrial sector (e.g. logistics or automotive) and in other research fields (e.g. medicine).
At the same time, it will be worked out whether quantum computers with a considerable level of noise, which are already available today or will soon be available, could be used for certain applications, or whether error-corrected quantum computers should rather be used in the future.
Related projects and activities
Application-driven Benchmarking of Quantum Computers (Bench-QC)
The MQV lighthouse project Bench-QC is a cooperation between industrial and research partners of different expertise. They aim to develop and implement a universal framework to allow a quantitative comparison of entire solution approaches of industrial problems using quantum computing as the practical usability of quantum computing hardware in industrial applications strongly depends on the combination of case application, used algorithm, mathematical problem formulation and given hardware parameters.
Quantum Algorithms for Application, Cloud & Industry (QACI)
Applications investigated within the Quantum Algorithms for Application, Cloud & Industry (QACI) consortium are ranging from optimization tasks in commercial applications, simulation of quantum systems for chemical, pharmaceutical or battery research to quantum machine learning for fraud detection. Use-cases are identified together with industry partners from different fields such as Infineon, DATEV, Airbus, BMW, or Roche, taking part as associated partners in MQV-associated project proposals.
Links
Quantum-enabling services and tools for industrial applications (QuaST)
Solutions based on quantum computing (QC) can make a significant contribution to the advancement of industrial optimization problems, saving time and money. However, QC-supported solutions are not yet available for mainstream industrial users. This is not only due to the limits of quantum computing hardware, but also because in-depth knowledge of physics and computer science is required in order to program today’s quantum computers. There is a general lack of low-threshold access to QC-supported solutions for end users. This is something that the project entitled QuaST – quantum-enabling services and tools for industrial applications – intends to change.