C12, Thales Test QuantumTrack for Real-Time Radar Tracking

C12 and Thales have announced the development of QuantumTrack, a hybrid quantum-classical method designed for real-time tracking of multiple radar targets. The two French companies, C12 specializing in carbon nanotube spin-qubit processors and Thales in defense and aerospace, received the 2026 Quantum Effects Award in the Quantum Computing Hardware category.

QuantumTrack’s Capabilities, According to C12 and Thales

The partners benchmarked QuantumTrack using C12’s Callisto emulator, which models a processor with up to 20 qubits, including errors and decoherence. The companies claim that QuantumTrack achieved the same time-to-solution as the best classical solver and operated approximately 100 times faster than competing quantum annealers on the emulator. A LinkedIn post by Frédéric Barbaresco, acknowledging contributions from both firms, describes this work as a simulation of quantum annealing on a semiconducting cQED device for a Multiple Hypothesis Tracking benchmark.

Key details provided by the companies include:

• Partners: C12 Quantum Electronics and Thales, with Thales acting as the system integrator.
• Function: Selecting mutually compatible hypotheses within Multiple Hypothesis Tracking.
• Hardware Modeled: Up to 20 qubits on the Callisto emulator.
• Estimated End-to-End Runtime: Approximately 50 milliseconds, utilizing an identified active qubit reset protocol.
• Stage: Technology Readiness Level (TRL) 5, with a TRL 6 demonstration on a physical processor planned.
• Event: Presented at the Quantum Effects trade fair in Stuttgart on October 6.

C12 CEO Pierre Desjardins stated that the next step involves demonstrating these results on the company’s own chip.

QuantumTrack’s Place in Quantum Technology

QuantumTrack addresses a quantum computing workload focused on an optimization problem within radar processing; it is neither quantum sensing nor post-quantum cryptography. This distinction is important, as quantum sensing involves separate technologies like atomic clocks and Rydberg spectrum sensing, and companies such as Infleqtion develop qubit systems for different applications. In this case, the radar hardware remains classical, while the quantum processor handles a computationally intensive step.

Tracking numerous moving objects simultaneously is an NP-hard problem. With increasing drone traffic and saturation attacks on defense radars, classical solvers often prune candidate trajectories to meet real-time requirements, potentially discarding paths that are later proven correct. C12 states that its spin qubits in carbon nanotubes, coupled to a microwave resonator, can be tuned to function as a native annealer, which the partners use to solve subproblems and integrate the results.

While the award and the emulator benchmark are verified, the demonstration on a physical chip has not yet occurred. This aspect is crucial for interpreting the speed figures. Interest in quantum technology continues to grow across various sectors, from academic centers like the Virginia Quantum Hub to open-source initiatives such as Fujitsu’s quantum application package.