Riverlane and NVIDIA Collaborate on AI-Based Quantum Decoder Calibration

15 October 2026. Riverlane and NVIDIA are collaborating on the use of AI and NVIDIA accelerated computing for quantum error correction (QEC), including how GPUs can make decoder calibration faster. A decoder is the part of a QEC system that interprets the signals produced by a quantum processor, works out which errors are most likely to have occurred and tells the system how to correct them.

Riverlane has developed an AI-based calibration loop that learns improved decoder settings directly from experimental data. As part of the collaboration, Riverlane uses NVIDIA H100 GPU to test how well different decoder settings perform. Using Riverlane's Local Clustering Decoder (LCD), adapted for high-throughput GPU processing, a training cycle on the surface code that previously took three minutes using a single-core CPU now takes just 2.8 seconds.

The H100 GPU can decode more than four million surface code syndromes per second, compared with around 59,000 per second on a single CPU core.

"Quantum error correction is the key technology that will enable useful quantum computers," Steve Brierley, founder and CEO of Riverlane, adds. Sam Stanwyck, Director of Quantum Product at NVIDIA, said: "Riverlane is using AI to help error correction keep pace with changing quantum hardware."

Riverlane will continue to investigate how NVIDIA accelerated computing can help make quantum error correction faster, more adaptive and more practical for utility-scale quantum computers.

Source: The Quantum Insider