KID-QC² - AI-supported Quantum Algorithm Development for Quantum Chemistry

In the KID-QC^2 project, a lighthouse project of Munich Quantum Valley, the Fraunhofer Institute for Integrated Circuits IIS and the University of Augsburg are working closely together to take the design and optimisation of quantum circuits for quantum chemical calculations to a new level. The main goal of this project is to use artificial intelligence (AI) to automate the development process of quantum circuits and increase their efficiency. The aim is to optimise the circuits for specific applications as well as for different hardware platforms.   

Particular attention is being paid to so-called "molecular quantum circuits", an innovative class of quantum circuits that have been specially designed for applications in quantum chemistry. These circuits are characterised by a complex and highly structured architecture that offers numerous possibilities for optimisation. The aim of KID-QC^2 is to investigate how these circuits can be improved and adapted to the requirements of different hardware environments using modern AI methods.

A central goal of the project is to optimise the Molecular Quantum Circuits in such a way that their expressivity and runtime are significantly improved. By using advanced AI methods, the structure of these circuits will be analysed and specifically adapted to achieve maximum performance. This is particularly important as quantum circuits in quantum chemistry are often very complex and require efficient utilisation of the available resources.

In addition, the project aims to make the molecular quantum circuits scalable. This means that the circuits should be applicable to larger and more complex quantum chemistry problems. Scalability is a decisive factor in expanding the possible applications of quantum computers in research and industry. Another important aspect of the project is to ensure that the optimisation strategies developed can be applied to different problem instances in quantum chemistry. This would mean that once a strategy has been developed, it is not only useful for a specific problem, but can be transferred to a wide range of applications.

In addition, the KID-QC^2 project places great emphasis on ensuring the compatibility of the Molecular Quantum Circuits with existing and future hardware platforms. The project takes into account the special requirements of Noisy Intermediate Scale Quantum (NISQ) devices, which are currently widely used in research. At the same time, it prepares the circuits for use on future, error-corrected quantum hardware generations. This future-proof design should ensure that the methods and circuits remain flexible and enable long-term usability.

The progress made as part of the KID-QC^2 project promises to significantly increase the performance and efficiency of quantum computers in quantum chemistry. At the same time, they open up new possibilities for industrial applications. The aim is to maximise the potential of quantum computers, even if only a limited number of logical qubits are available. The project is thus helping to promote the next generation of quantum chemical research and industrial innovations and pave the way for ground-breaking discoveries.

As consortium leader in the KID-QC² project, we contribute extensive expertise and research experience in the field of quantum computing technologies. Our focus is on the development and optimisation of quantum circuits that are specifically designed to meet the challenges of quantum chemistry.

We specialise in innovative approaches for the integration of artificial intelligence into the design process of quantum circuits. Through our expertise in mathematical optimisation and machine learning, we contribute to improving the efficiency and scalability of molecular quantum circuits.

In close co-operation with the other partners, we promote the exchange of knowledge and technologies to ensure that the solutions developed meet the requirements of a wide range of hardware platforms. Our goal is to significantly expand the practical application possibilities of quantum computers in research and industry.