Programming Language

As demand for quantum computers rises, so does the need for powerful, user-friendly tools for programming them. Many quantum algorithms are hybrid, meaning they have components that are computed on classical computers as well as quantum components that require a quantum computer. Even if quantum computers were significantly more advanced, it would still make sense to run primarily the sub-algorithms that benefit from quantum computing on quantum computers, rather than the entire applications.

With “Qrisp,” Fraunhofer researchers at Fraunhofer FOKUS have created a high-level programming language for writing and compiling quantum algorithms. Its structured programming model enables developers to write efficient and scalable quantum algorithms.

One of the medium-term goals ahead of us is the integration of gate-based quantum computing and adiabatic quantum computing into the classical landscape of computing architectures. Therefore, connecting quantum computers to classical hardware is very important and must be taken into account in the design of algorithms and the integration of quantum computers.

With this in mind, we are seeking platforms, frameworks, and high-level programming languages (including machine-independent ones) for such algorithms and workflows. Ideally, these new languages and frameworks should be embedded in existing programming languages and platforms (e.g., Python, Java, C/C++ …) so that the wide range of existing software libraries can be used to control the various types of hardware.

Furthermore, this kind of integration also enables the use of existing libraries for mathematical optimization, machine learning, AI explainability, and other cutting-edge research findings from recent years.