Quantum X Labs’ Decoder Delivers Lowest Logical Error Rates by integrating NVIDIA CUDA-Q QEC in Comparison to Other Decoders
Streaming tests showed approximately 6% and 9% lower observed logical error rates than PyMatching at the two tested code distances.
Sentiment and the balance of points
Rhea-AI Sentiment reads the wording of the document, how positive or negative its language is on a 1 to 5 scale. The balance of points shown with the takes weighs what the document actually discloses, so the two can disagree, for example when a trial that missed its main goal is described in upbeat language.
Rhea-AI Summary
Quantum X Labs (QXL) has deployed its quantum error-correction decoder on NVIDIA CUDA-Q and reported fewer errors in hardware-data benchmarks.
A decoder interprets error measurements to determine corrections. On Google's public quantum hardware data, QXL recorded 12.7% fewer logical errors than PyMatching at code distance 3 and 12.1% fewer at distance 5. Performance was comparable to BP+OSD. In a separate 25-round streaming evaluation, observed logical error rates were approximately 6% and 9% lower than PyMatching at those respective distances.
QXL plans to test the decoder in a real-time error-correction pipeline using an NVIDIA NVQLink connection. It is also discussing potential integration with quantum control-system providers; live operation alongside quantum hardware remains a goal.
Positive
- Minor pointCUDA-Q deployment completes a milestone integrating QXL's decoder with NVIDIA's quantum computing software platform.
- Minor pointLogical errors were 12.7% lower at distance 3 and 12.1% lower at distance 5 versus PyMatching.
- Minor pointBP+OSD comparison showed about 2% fewer errors at distance 3 and 1.5% fewer at distance 5.
- Minor pointSimulation results beat standard matching across all 108 code-size and noise-level settings tested.
- Minor pointStreaming error rates were approximately 6% lower at distance 3 and 9% lower at distance 5 versus PyMatching.
3 minor points
- Minor pointStreaming evaluation also outperformed the CUDA-Q QEC sliding-window baseline and performed comparably to BP+OSD.
- Minor point. Forward-looking: it has not happened yet and may not happen.Real-time pipeline testing is planned on a system using an NVIDIA NVQLink connection.
- Minor pointPotential platform integration is under discussion with quantum control-system providers.
Negative
- None.
Key Figures
- Logical errors vs. PyMatching
- 12.7% fewer
- Google public hardware data, distance 3
- Logical errors vs. PyMatching
- 12.1% fewer
- Google public hardware data, distance 5
- Logical errors vs. BP+OSD
- about 2% fewer
- Google public hardware data, distance 3
- Logical errors vs. BP+OSD
- 1.5% fewer
- Google public hardware data, distance 5
- Streaming logical error rate vs. PyMatching
- approximately 6% lower
- Held-out Google hardware data, distance 3
- Streaming logical error rate vs. PyMatching
- 9% lower
- Held-out Google hardware data, distance 5
- Simulation settings
- 108
- Decoder beat standard matching across tested code-size and noise-level settings
- Held-out runs
- 10,000
- Google public hardware data benchmark
Previous AI Reports
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Reported improved decoder performance on Google’s public surface-code dataset using NVIDIA CUDA-Q.
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Reported selected simulated-regime outperformance versus a classical decoder using CUDA-Q QEC.
24h Move is the share-price change in the day after each event; other market factors may also have contributed.
Key Terms
quantum error-correction technical
surface-code technical
logical error rates technical
superconducting quantum processor technical
AI-generated analysis. How Rhea-AI works. Not financial advice.
QXL's decoder leverages CUDA-Q QEC to manage to cutt logical errors by 12–
TEL AVIV, Israel, Oct. 21, 2026 (GLOBE NEWSWIRE) -- Quantum X Labs Inc. (NASDAQ: QXL) (“Quantum X Labs”, “QXL” or the “Company”), 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–
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
“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
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.
About Quantum X Labs Inc.
Quantum X Labs Inc. and its subsidiaries are focused on quantum technology, digital advertising and computing and enterprise artificial intelligence (AI) solutions. Quantum X Labs Ltd. is focused on developing and promoting quantum algorithms for the transportation, drug discovery and security segments as well as developing quantum- based GPS replacement and quantum atom accuracy solutions. Gix Media develops a variety of technological software solutions, which perform automation, optimization and monetization of internet campaigns, for the purposes of acquiring and routing internet user traffic to its customers. Metagramm is a developer of grammatical error correction software and offers tools for writing and reviewing, grammar, spelling, punctuation and style features, as well as translation and multilingual dictionaries, using artificial intelligence and machine learning technology.
For more information about Quantum X Labs, visit https://quantumxlabs.xyz/
Forward-Looking Statements
This press release contains forward-looking statements within the meaning of the “safe harbor” provisions of the Private Securities Litigation Reform Act of 1995 and other Federal securities laws. Forward-looking statements contained in this press release include, but are not limited to, statements regarding Quantum X Labs’ and its subsidiaries’ strategic and business plans, technology, relationships, objectives and expectations for its business, growth, the impact of trends on and interest in its business, intellectual property, products and its future results, operations and financial performance and condition and may be identified by the use of words such as “may,” “seek,” “will,” “consider,” “likely,” “assume,” “estimate,” “expect,” “anticipate,” “intend,” “believe,” “do not believe,” “aim,” “predict,” “plan,” “project,” “continue,” “potential,” “guidance,” “objective,” “outlook,” “trends,” “future,” “could,” “would,” “should,” “target,” “on track” or their negatives or variations, and similar terminology and words of similar import, generally involve future or forward-looking statements. For example, the Company is using forward-looking statements when it discusses the potential benefits and capabilities of its quantum error correction technology; the potential integration, adoption and use of its decoder with NVIDIA CUDA-Q QEC, NVIDIA NVQLink, quantum control systems and other quantum computing platforms and hardware; potential integration of its decoder directly into quantum control-system providers’ platforms; its plans to advance its decoder toward accelerated and real-time operation alongside quantum hardware; and the development and potential applications of its broader adaptive quantum error correction platform. Forward-looking statements are not historical facts, and are based upon management’s current expectations, beliefs and projections, many of which, by their nature, are inherently uncertain. Such expectations, beliefs and projections are expressed in good faith. However, there can be no assurance that management’s expectations, beliefs and projections will be achieved, and actual results may differ materially from what is expressed in or indicated by the forward-looking statements. Forward-looking statements are subject to risks and uncertainties that could cause actual performance or results to differ materially from those expressed in the forward-looking statements. For a more detailed description of the risks and uncertainties affecting the Company, reference is made to the Company’s reports filed from time to time with the Securities and Exchange Commission (“SEC”), including, but not limited to, the risks detailed in the Company’s most recent Annual Report on Form 10-K and in subsequent filings with the SEC. Forward-looking statements speak only as of the date the statements are made. The Company assumes no obligation to update forward-looking statements to reflect actual results, subsequent events or circumstances, changes in assumptions or changes in other factors affecting forward-looking information except to the extent required by applicable securities laws. If the Company does update one or more forward-looking statements, no inference should be drawn that the Company will make additional updates with respect thereto or with respect to other forward-looking statements. References and links to websites have been provided as a convenience, and the information contained on such websites is not incorporated by reference into this press release. Quantum X Labs is not responsible for the content of third-party websites.
Investor Relations Contacts:
Michal Efraty
Investor Relations
michal@efraty.com
FAQ
AI-generated questions and answers. How Rhea-AI works. Not financial advice.
How did Quantum X Labs' decoder compare with PyMatching on Google's quantum hardware data?
QXL's decoder made 12.7% fewer logical errors at distance 3 and 12.1% fewer at distance 5 than PyMatching in the standard benchmark. In the separate 25-round streaming evaluation, observed logical error rates were approximately 6% and 9% lower at those respective distances.
How did Quantum X Labs test its CUDA-Q decoder?
The standard benchmark used 10,000 held-out runs of five error-correction rounds from Google's public surface-code dataset, recorded on its superconducting quantum processor. Testing covered code distances 3 and 5. Every decoder used the same CUDA-Q QEC interface and the same data.
How does Quantum X Labs expect hardware teams to access its CUDA-Q decoder?
QXL expects teams building on NVIDIA's quantum platform to be able to select its decoder alongside existing CUDA-Q decoders without a separate workflow. That expectation rests on the decoder's integration with the CUDA-Q QEC library.