aiqbench takeQuantum Computing

EigenOrbit's new open-source library enables writing quantum algorithms once while executing across diverse simulators and hardware backends like IBM, Amazon Braket, and Quandela. By integrating PyTorch and scikit-learn pipelines with built-in cost estimation tools, it lowers the barrier to multi-platform quantum development and benchmarking. This initiative directly addresses fragmentation in the ecosystem by standardizing access to both classical and quantum execution environments.

Source coveringQuantum Computing Report

What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

EigenOrbit Releases Open-Source eigenkit 1.0 for Multi-Backend Quantum Execution

Quantum Computing ReportOctober 14, 20261 min read

EigenOrbit has released eigenkit 1.0, an open-source Python library. It allows quantum algorithms to be written once and executed across multiple simulators and hardware backends without code modification. The library integrates with various classical simulators and QPU hardware access points, including machine learning and cost tools. The post EigenOrbit Releases Open-Source eigenkit 1.0 for Multi-Backend Quantum Execution appeared first on Quantum Computing Report.

Open-source quantum software initiative EigenOrbit has launched eigenkit 1.0, an Apache 2.0-licensed Python library designed to write quantum algorithms once and execute them…

Excerpt shown under the publisher's RSS terms · 23 words · full text and figures are on the publisher's site

Read at Quantum Computing Report ↗Ask about this article