TEL AVIV, Israel, October 21, 2026 -- Quantum X Labs Inc. a quantum technology company developing advanced solutions across quantum computing, quantum error correction, quantum software, cybersecurity and quantum sensing, today announced a key milestone: its quantum error-correction (QEC) decoder is now deployed and running on NVIDIA CUDA-Q, the open platform for hybrid quantum-classical supercomputing. Leveraging the CUDA-Q QEC library, the decoder made 12–13% fewer logical errors than the platform's standard matching decoder (PyMatching) on Google's publicly released quantum hardware data.

Quantum computers are inherently prone to errors, and a decoder is the classical software that interprets error-correction measurements and determines how those errors should be corrected as the machine operates. Improved decoding may enable more reliable, logical operation from the same physical hardware.

Because the QXL decoder integrates with CUDA-Q QEC, QXL expects that quantum hardware teams building on the NVIDIA quantum platform will be able to select it alongside existing CUDA-Q decoders without requiring a separate workflow. QXL believe the integration represents an important step in its transition from decoder research and offline benchmarking toward accelerated and real time quantum error correction.

QXL tested the decoder on Google's public surface-code dataset, recorded on Google's superconducting quantum processor. The test used 10,000 held-out runs of five error-correction rounds at two code sizes (distance 3 and distance 5). Every decoder was run through the same CUDA-Q QEC interface on the same data, so the comparison is like-for-like.

The QXL decoder made 12.7% fewer logical errors than PyMatching at distance 3 and 12.1% fewer at distance 5. It was on par with BP+OSD, with about 2% fewer errors at distance 3 and 1.5% fewer at distance 5. In simulation, the decoder beat standard matching in all 108 code-size and noise-level settings tested.

“This milestone demonstrates that QXL’s decoder technology can operate within a leading quantum computing software environment and deliver encouraging results on real experimental data,” said Prof. Nir Sharon, Chief Scientist of Quantum X Labs. “It is an important step toward accelerated and adaptable decoding that can ultimately operate alongside quantum control systems.”

QXL has also turned the decoder into a streaming version that follows the real-time decoding interface in CUDA-Q QEC: it receives error data round by round as the quantum computer runs and returns corrections continuously.

In a separate 25-round streaming evaluation on held-out shots from the same Google public hardware dataset, the QXL streaming decoder achieved lower observed logical error rates than the CUDA-Q QEC sliding-window baseline and full-experiment PyMatching and performed comparably to BP+OSD. Compared with PyMatching, its observed logical error rate was approximately 6% lower at distance 3 and 9% lower at distance 5.

QXL plans, as a next step, to run the decoder in a real-time QEC pipeline on a system utilizing an NVIDIA NVQLink connection, with the goal of moving it closer to live operation alongside quantum hardware. QXL is also working with quantum control-system providers regarding potential integration of the decoder directly into their platforms.

The decoder tested with CUDA-Q QEC is one implementation within QXL’s broader adaptive quantum error correction platform. The Company’s roadmap is designed to support multiple decoder architectures, error correcting codes and quantum hardware technologies, allowing decoding solutions to be adapted to the requirements of different quantum systems.