Control electronics

Python-based data acquisition framework for physics experiments. Reduces setup time, encourages code sharing, and leverages modern software practices for efficient research.

Control quantum experiments with precise timing and low latency using a flexible, programmable system. Features Python-based programming, FPGA execution, and open hardware.

Access and deploy established error-robust quantum control protocols. Easily integrate techniques from the literature onto custom hardware, cloud platforms, or Fire Opal.

The Munich Quantum Toolkit (MQT) is a collection of software tools for quantum computing that explicitly utilizes this design automation expertise.

The Quantum Device Management Interface (QDMI) is one of the core components of the Munich Quantum Software Stack (MQSS)—a sophisticated software stack to connect end users to the wide range of possible quantum devices.

Run your hybrid classical-quantum algorithms on our hardware backends and experience new possibilities in hybrid quantum computing.

Develop cryogenic CMOS ASICs for quantum device control. Reduce hardware cost and eliminate wiring bottlenecks, enabling scalable next-generation quantum technologies.