Quantum Computing Report

Gothenburg and Chalmers Researchers Develop Modular Graph Neural Decoder for Surface Code Memory and Lattice Surgery

Researchers from the University of Gothenburg and Chalmers University of Technology have developed a modular neural decoder for surface code quantum error correction (QEC). This decoder demonstrates superior performance compared to traditional methods and is capable of adapting across different hardware architectures, noise profiles, and multi-patch logical operations. Its efficient design, inspired by the renormalization group, allows for training on a single commercial GPU and offers portabili

By Quantum Computing Report

1 min read
Gothenburg and Chalmers Researchers Develop Modular Graph Neural Decoder for Surface Code Memory and Lattice Surgery
AI-generated illustration

Got news to share with the events industry?

Submit a press release or story tip and reach thousands of event professionals.

Get in touch→

More in Quantum Tech & Cryptography

Related Insights