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The eigenkit library gives researchers one interface for running the same quantum algorithm on 12 simulators and hardware platforms, including IBM Heron and IQM Emerald. The reported result matters more than the tooling: the best processor for a given algorithm depends on how well its qubit topology matches the processor's physical connectivity, not just on hardware specs. Readers should treat the claims as early, since the article gives no benchmark figures, but backend portability is a practical concern for anyone comparing quantum hardware.
A single library now links quantum algorithms to IBM and IQM hardware

eigenkit is a new library simplifying the use of quantum algorithms on diverse hardware, currently supporting 12 providers.
A new library called eigenkit now links a single codebase to 12 different quantum simulators and actual quantum hardware platforms, including IBM Heron and IQM Emerald. Researchers at EigenOrbit Sàrl in Luxembourg developed the system to address the challenges of moving algorithms between diverse quantum computing environments and integrating them with standard scientific tools like NumPy, PyTorch and scikit-learn. Experiments reveal that the best processor for a given algorithm isn’t solely determined by hardware limitations, but also by the characteristics of the algorithm itself. This backend portability, the team reports, is important for both computational efficiency and quantum execution quality. This finding highlights the importance of software tools that facilitate algorithm portability across diverse quantum computing platforms, as a mismatched topology can substantially degrade execution quality. Experiments on IBM Heron and IQM Emerald…
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