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Stuttgart-Led FeedbacQ Wins €1.15m for Quantum Control
A three-year European project led by the University of Stuttgart will investigate whether control theory can help quantum computers tackle optimization problems and reduce errors. The six-partner team plans to develop algorithms and test it
Quantum.world Team · Written with AI · fact-checked ·
Most quantum algorithms return a result only after the computation ends. A new European project wants to test whether monitoring and adjusting a quantum computation while it runs can help solve optimization problems—and reduce errors. FeedbacQ, led by the University of Stuttgart, began with a partner meeting in Berlin on October 20.
Optimization problems involve finding the best choice among many alternatives. Examples include planning delivery routes to use less fuel and balancing electricity generation with consumption to keep a power grid stable. Many such problems can be solved with modern IT, but highly complex ones can push even high-performance computers to their limits. FeedbacQ will investigate whether quantum computers can help with this class of problems.
FeedbacQ puts feedback inside the computation
The project applies control theory, a field concerned with monitoring and steering dynamic systems, to quantum computing. Its researchers plan to develop methods that translate practical optimization problems into forms a quantum computer can process, devise algorithms and investigate ways to lower error rates. The University of Stuttgart announced the project on October 27.
Quantum computers use qubits rather than classical bits, which have a state of either 0 or 1. Qubits can hold different states at the same time; quantum algorithms use superposition and entanglement to amplify some computational paths and reduce others. A measurement at the end of a computation yields a concrete result. FeedbacQ will study whether control theory can help researchers monitor and influence that process before the final measurement.
Project coordinator Dr. Julian Berberich described the aim as intervening during a computation rather than relying only on its final measurement:
“We are working on mathematical methods that can be used to monitor quantum algorithms during the computation process and influence them in real time.”
Dr. Julian Berberich, project coordinator, University of Stuttgart
The university says the team will use continuous measurement and readjustment to pursue calculations that are more reliable, faster and less resource-intensive. Those are project goals, not reported performance results: the announcement describes planned research, not a demonstration of a quantum advantage.
Six institutions, three years and a Torino test
Alongside Stuttgart, the consortium includes Freie Universität Berlin, CentraleSupélec, École Nationale Supérieure de Techniques Avancées, the Politecnico di Torino and the University of Malta. Researchers in physics, mathematics, engineering and computer science will work across the disciplines, the university says.
The project runs for three years and will test its methods in real-world experiments on quantum computers. One planned test uses a gate-based device at the Politecnico di Torino. The researchers also intend to develop error-correction techniques based on feedback loops and continuous monitoring and control. The experiments are intended to validate the team’s results and demonstrate their practical significance.
€1.15 million from a competitive QuantERA call
QuantERA, a transnational funding network, is providing €1.15 million for FeedbacQ. The project was selected through QuantERA Call 2025, which drew 287 applications from 29 countries; 39 projects received funding, according to the University of Stuttgart.
The work targets two distinct challenges: how to express real-world optimization tasks for quantum processors, and how to control computations on hardware that remains prone to errors. The Torino experiments will give the partners a place to test their methods on a gate-based system; the announcement sets no performance target or timetable for results.