Insider Brief
- QC Design launched Gauge, a tool within its Plaquette platform to determine optimal fault-tolerance thresholds for quantum error correction codes.
- Gauge uses automated simulations and a fast Monte Carlo engine to evaluate how codes and noise models impact achievable error-correction performance.
- The tool helps teams benchmark theoretical limits and refine design choices for scalable fault-tolerant quantum computing systems.
PRESS RELEASE — Today QC Design announced the launch of Gauge, an extension of its Plaquette platform that determines the optimal fault-tolerance threshold for a given quantum error correction code and noise model.
Gauge computes the best achievable error-correction threshold across all decoding strategies by mapping the decoding problem onto a statistical mechanical system. Powered by a Markov-chain Monte Carlo engine that is 100 times faster than those reported in the literature, Gauge fully automates simulation of how different QEC codes and hardware imperfections affect the maximum attainable threshold. This allows teams to separate the impact of the error-correction code from that of the decoder, providing a clearer view of the design choices most likely to achieve fault tolerance.
Dr. Ish Dhand, co-founder and CEO of QC Design, said:
“Gauge represents a major step forward in how quantum computing teams evaluate their cutting edge architectures for fault-tolerance. By establishing the theoretical limits of error correction, we enable teams to focus their efforts on the approaches most likely to achieve scalable fault-tolerant quantum computing, whether it is developing better decoders for existing codes or devising new codes altogether.”
QC Design has put Gauge in the hands of leading quantum computing companies, including PsiQuantum, who have leveraged the tool to understand the optimal thresholds and determine if additional performance could be unlocked through further decoder development.
Gauge expands Plaquette’s role in the fault-tolerant quantum computing stack. Plaquette already helps hardware teams simulate and optimize architectures under realistic noise. By adding Gauge, those same teams can now establish the theoretical ceiling for error-correction performance, providing a clear view of both the benchmark they should aim for and the architectural choices that can help them get there.
