aiqbench takeQuantum Computing

Aqarios is pioneering a strategy to treat quantum noise as a computational resource rather than an error, enabling machine learning tasks on today's imperfect hardware. This approach directly addresses the immediate utility of current quantum devices while aligning with regulatory demands for explainable AI under the EU AI Act. By benchmarking these quantum neural computing methods against classical approaches, the project aims to deliver practical industry applications without waiting for fully error-corrected systems.

Sources coveringQuantum Zeitgeist, SiliconANGLE, Inside Quantum Technology, IQMP

Aqarios Quantum Technologies tests quantum machine learning methods on today’s hardware.

Quantum ZeitgeistNovember 5, 20263 min read

The QuantERA project IgnisQNC asks whether the noise in today’s quantum computers can be put to work for machine learning. Aqarios is responsible for testing new AI methods, designed for current hardware, on real quantum hardware via Luna over the next three years, from autumn 2026 to autumn 2029.

Aqarios Quantum Technologies will actively harness quantum noise, typically viewed as a hindrance, as a resource for machine learning within the three-year IgnisQNC project. Funded by the European QuantERA programme, the initiative running from autumn 2026 to autumn 2029 focuses on developing AI methods for current, noisy quantum hardware. The project, titled “Harnessing Quantum Uncertainty: Trustworthy…

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