QXL has completed two meaningful development steps. First, the Company executed its Deep Quantum Error Correction (DQEC) workflow on an NVIDIA GPU in an AWS environment and benchmarked its transformer-based QECCT decoder against the classical Minimum-Weight Perfect Matching (MWPM) decoder across controlled toric-code noise configurations. QECCT outperformed MWPM in selected simulated regimes.

QXL also tested synthetic surface-code configurations modeled on Google’s public surface-code geometry and experiment structure, spanning multiple code distances. Across these scenarios, the QECCT decoder showed stable logical and bit error rates under varying physical error conditions.

These results are intended as an initial step in validating the approach within controlled simulation environments. Future work is expected to focus on extending these evaluations to publicly available experimental datasets and continuing to refine data pipelines and decoder workflows compatible with CUDA-Q QEC frameworks.