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EigenOrbit's open-source eigenkit library addresses a critical fragmentation issue in quantum development by enabling algorithms to run across diverse simulators and hardware backends like IBM, IQM, and Amazon Braket without code rewrites. By decoupling algorithm logic from execution hardware, the tool lowers the barrier for researchers to efficiently benchmark performance and optimize costs across varying qubit counts and error rates. This abstraction layer is essential for scaling quantum software stacks as the ecosystem expands beyond a single vendor's proprietary SDKs.

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EigenOrbit Releases Open-Source eigenkit Quantum Computing Library

The Quantum InsiderOctober 14, 20263 min read

Insider Brief PRESS RELEASE — EigenOrbit has released eigenkit, a free open-source Python library for quantum computing. With eigenkit, a quantum algorithm is written once and runs on a simulator on an ordinary laptop or on real quantum computers from IBM, IQM and the vendors available through Amazon Braket. Moving from one machine to another […]

EigenOrbit has released eigenkit 1.0, a free, open-source Python library designed to run quantum algorithms across multiple simulators and quantum hardware platforms without rewriting the algorithm for each backend. The library supports tools including Qiskit, PennyLane, NVIDIA CUDA-Q and Amazon Braket, alongside hardware from IBM and IQM, and includes algorithms for quantum machine learning, optimization, chemistry and finance. Released under the…

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