NVIDIA has launched the Ising family of open-source AI models to accelerate practical quantum computers by tackling key challenges in processor calibration and error correction.
The models deliver performance of up to 2.5x faster quantum error-correction decoding and 3x higher accuracy compared to the industry-standard pyMatching tool.
They are named after the Ising model, a foundational mathematical framework in statistical mechanics developed by Ernst Ising in 1925.
“With Ising, AI becomes the control plane — the operating system of quantum machines — transforming fragile qubits to scalable and reliable quantum-GPU systems,” said Jensen Huang, Founder and CEO of NVIDIA.
Early adopters include leading labs such as Fermi National Accelerator Laboratory, Harvard’s John A Paulson School of Engineering, IQM Quantum Computers, and the UK National Physical Laboratory.
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