IonQ, a College Park, Maryland-based quantum computing company, has announced the successful testing of what it describes as the industry’s first end-to-end real-time quantum error correction decoder capable of running on a single standard CPU. In technical benchmarks involving up to 408 simulated logical qubits and more than 31.5 million quantum operations, the technology introduced as little as 0.02% additional execution time, addressing a major computational challenge in the development of fault-tolerant quantum computers.
The development represents an important milestone in IonQ’s efforts to build larger and more reliable quantum computing systems. By enabling error correction to operate continuously on conventional computing hardware, the company aims to reduce the processing overhead associated with scaling quantum computers.
Quantum error correction is essential to developing practical quantum computers because the physical qubits used to perform calculations are highly sensitive to environmental noise and other disturbances.
These disturbances can introduce errors that compromise the accuracy of quantum computations. As quantum systems become larger and perform more operations, identifying and addressing those errors becomes increasingly complex.
A significant challenge involves the conventional computers responsible for processing error information. These systems must analyze information generated by the quantum computer and determine the corrections needed to preserve the computation.
If the classical error decoder cannot process information quickly enough, it creates a bottleneck that can force the quantum system to pause while waiting for error-processing results.
IonQ’s newly demonstrated technology is designed to eliminate this delay by allowing a single commercially available CPU to process error information continuously in the background.
The company evaluated its proprietary dual-decoder architecture in research published on arXiv, using complex benchmark circuits representing quantum computing workloads.
The tests simulated up to 408 logical qubits distributed across 88 memory blocks and magic factories. The benchmark circuits involved more than 31.5 million individual quantum operations, representing what IonQ describes as the MegaQuOp scale.
Logical qubits are units of quantum information protected through quantum error correction, typically requiring multiple physical qubits. Magic factories are specialized components used to produce resource states needed for certain fault-tolerant quantum operations.
The benchmarks were designed to evaluate whether IonQ’s decoder could process the error information associated with increasingly large and complex quantum computations without introducing substantial delays.
Under standard operational noise assumptions, the decoder introduced as little as 0.02% stretch time, meaning that the additional processing required for error correction had almost no effect on overall execution time in the evaluated circuits.
The results were obtained through simulated benchmark circuits rather than an experimental demonstration involving a physical processor with 408 operational logical qubits.
Nevertheless, the findings provide evidence that conventional computing hardware could support real-time error decoding for substantially larger quantum systems without requiring a corresponding increase in classical processing resources.
The development supports IonQ’s proprietary Walking Cat architecture, which is designed to enable scalable fault-tolerant quantum computing.
According to IonQ, the research demonstrates that classical error-decoding hardware does not necessarily need to scale exponentially as quantum systems increase in logical qubit count or computational complexity.
Reducing this processing overhead could help address the infrastructure costs and technical challenges associated with developing commercially viable quantum computers.
The company is incorporating the technology into its broader roadmap as it progresses beyond 256 physical qubits toward industrial-scale quantum platforms controlling thousands of qubits.
IonQ’s research and development activities extend across quantum computing, networking, sensing, and security. Its newest generation of quantum computers, Superion, is part of its strategy to deliver increasingly capable quantum computing systems for enterprise and research applications.
The company has worked with organizations including Amazon Web Services, AstraZeneca, and NVIDIA on quantum computing applications and infrastructure.
Potential applications for its technology include drug discovery, materials science, financial modeling, logistics, cybersecurity, and defense, although realizing the full potential of these applications will depend on further improvements in quantum hardware, error correction, and overall system reliability.
In 2025, IonQ reported achieving 99.99% two-qubit gate fidelity, a measurement of the accuracy of quantum operations. The latest decoder demonstration addresses a separate challenge: processing the error information necessary to maintain reliable computations as quantum systems grow.
Together, these developments form part of IonQ’s effort to build fault-tolerant quantum computers capable of performing increasingly complex calculations while maintaining practical requirements for execution time, cost, and energy consumption.
KEY QUOTES:
“Successfully validating real-time decoding across hundreds of logical qubits and over millions of logical operations is an important milestone. Moreover, the fact that our decoder runs on a single CPU provides a practical path to commercial-scale fault-tolerant quantum computing.”
Nicolas Delfosse, Paper Co-Author and Quantum Research Lead at IonQ
“IonQ is enabling cost-effective quantum system scaling through direct verification of each component. Empirical evidence like this supports our vision for fault tolerance where time-to-solution, cost-to-solution, and energy-to-solution are always our North Star.”
John Gamble, Vice President at IonQ Architecture
