While gate speed is a common industry benchmark, Helios contends that total “wall-clock time to a result worth acting on” is the most important metric, arguing that “moving slower in the right direction is still progress.” The company’s approach centers on fidelity, encompassing gate, measurement and memory errors, because theoretical work suggests computations become efficiently approximated on classical computers when fidelity falls between 1 and 3. Helios believes a complete understanding of error profiles is essential for scalable error correction and ultimately, a dependable result.
Fidelity as Foundation for Scalable Quantum Computation
Helios contends that achieving a usable level of fidelity is paramount, even if it means accepting slower gate speeds, because the accumulation of errors, not simply their rate, dictates the feasibility of complex calculations. A system with lower error rates can ultimately deliver results faster by minimizing the overhead required for error correction, a point illustrated by the company’s own color-code experiments demonstrating performance below the 10⁻³ threshold.
This approach acknowledges that faster gates do not necessarily translate to faster solutions if the underlying quantum information is quickly corrupted by errors. The company asserts that a system’s ability to sustain reliable computation is the true measure of its performance. Helios’ Quantum Universal Operations Performance System (QUOPS) aims to quantify this capability, tracking computational reach and speed with a score, Q, that measures the size of a circuit a system can successfully execute.
Helios defines “fidelity” comprehensively, encompassing gate, measurement and memory errors, alongside leakage, crosstalk, correlations, and drift. This broad definition reflects an understanding that error profiles are complex and interconnected, extending beyond simple gate error rates. The company’s approach to error correction uses the principle that many physical qubits and operations can be used to create protected logical operations with error rates significantly below 10⁻⁴. This allows for scaling up error correction to meet the demands of increasingly complex applications, pushing the logical error rate down to levels required for reliable computation.
The company’s strategy is rooted in the belief that high fidelity enables smaller error correction codes and reduces overall overhead, potentially transforming slower physical gates into faster logical gates, Helios says. This focus on fidelity, rather than speed alone, positions Helios as a proponent of a long-term, sustainable approach to quantum computing, where reliable computation is prioritized over raw processing power.
Error Rate Thresholds Enable Quantum Error Correction
Achieving a logical memory failure rate of just 5 × 10⁻⁶ per correction cycle represents a critical step toward scalable quantum error correction, as recently demonstrated by Helios using code distances 3, 5, and 7. This performance, achieved with physical two-qubit gate error rates around 10⁻³, indicates that the physical qubits are already reliable enough for error correction to begin scaling, a finding detailed in recent experiments.
The team observed approximately twelvefold error suppression for each increase of two in code distance across the tested sizes, validating the principle that increased protection reduces logical error rates when physical error rates are sufficiently low. The threshold for effective error correction is not a fixed point, but rather a dynamic relationship between physical error rates and the overhead introduced by the correction process itself.
Below this threshold, the benefits of increased protection outweigh the potential for new faults, allowing for longer and more reliable computations. Experiments, including those conducted by Helios, are designed to demonstrate operation below the threshold of specific codes like the color code or surface code, confirming the viability of these approaches, according to the company. A faster processor, while desirable, cannot circumvent the need for this underlying fidelity; speed alone does not reduce the number of faults that must be corrected.
Protected two-qubit Clifford operations also showed significant improvement, with roughly ninefold suppression from distance 3 to 5, further illustrating the effectiveness of the error correction strategy. Helios’ experiments highlight that the goal is not simply to reduce the error per operation, but to lower the overall logical error rate to a level suitable for the intended application.
For the team’s 10,000-operation example, an error rate of 10⁻³ per operation resulted in an average of ten faults, a number that quantum error correction can effectively mitigate. “First make the computation reliable; then make it faster,” emphasizes the prioritization of stability over speed in the pursuit of scalable quantum computation. The ability to improve both stored information and logical operations through stronger protection is central to the scaling question.
This means that high physical fidelity enables longer, reliable computations, rather than simply delivering a cleaner component benchmark. The team’s findings build on work by others, including N. Berthusen et al., who demonstrated a compact fault-tolerant architecture for trapped ions, and A. These results, alongside studies such as “Improved quantum processor logical error rates via correction and detection,” published by A. Paetznick et al., collectively demonstrate the growing maturity of quantum error correction techniques.
Helios Demonstrates Computational Reach via QUOPS Benchmarking
Successfully executing benchmark circuits exceeding the size achieved by Willow and IBM’s Boston systems in initial cross-platform testing using the newly developed Quantum Universal Operations Performance System, or QUOPS, were Helios’ H2-1 and Helios-1 processors. While the superconducting systems and IBM demonstrated higher effective operation rates, they were limited to smaller circuits, highlighting a trade-off between speed and scale. A system with slower physical gates can still arrive first if it incurs lower overheads. It may even be the only system that arrives at all, because noise overwhelms the faster system’s computation.
The team’s findings indicate that error mitigation, while enabling larger circuits, introduces significant overhead, reducing effective processing rates by factors of thousands, and that faster physical gates do not automatically translate to faster results, the company says. “We need to know how much reliable computation a system can sustain and how quickly it delivers it,” explains the team, emphasizing the importance of sustained performance over raw speed.
This suppression of errors improved with increasing code distance, demonstrating approximately twelvefold improvement for every two-unit increase in distance. The team’s success with magic-state preparation, an essential component for universal fault-tolerant computation, further supports the viability of their approach, Helios reports. In 2025, they demonstrated high-fidelity logical magic states, and a complementary approach using magic-state cultivation on superconducting hardware was recently published by Willow team in Science on October 15. “Researchers demonstrate quantum advantage through trusted quantum computation,” the team notes, acknowledging the broader progress in the field.
The QUOPS study also estimated the computational resources required to tackle complex problems like factoring RSA-2048 or calculating FeMoco’s ground-state energy, finding that these tasks demand roughly 100,000 times the computational reach currently demonstrated by existing physical-qubit processors. While the 98-qubit Helios system already supports circuits beyond the reach of classical simulation methods, the team acknowledges that translating this capability into practical industrial advantage requires further advancements. The findings emphasise that achieving a reliable result requires not just low error rates, but a comprehensive understanding and mitigation of all error sources, from gate imperfections to measurement errors and beyond.
NISQ Computing’s Limited Path to Industrial Advantage
While error mitigation techniques can temporarily extend the capabilities of NISQ systems, their scalability is constrained; at fixed error rates, general-purpose mitigation faces exponentially increasing sampling costs as circuit complexity grows. This limitation, outlined in research published in Nature Physics, highlights the necessity of transitioning toward fault-tolerant architectures for sustained progress. The team’s work, however, focuses on the interplay between reliability and speed. “A 98-qubit trapped-ion quantum computer with all-to-all connectivity,” allows for exploration of complex algorithms, but the ultimate goal is to reduce both the time and total cost of solving useful problems.
Industrial advantage requires more than just outperforming classical algorithms on isolated tasks. It demands solving practically relevant problems faster or at lower cost, while maintaining comparable accuracy and accounting for the entire workflow. According to Helios, the improvement must also withstand advancements in classical algorithms. While some advantage claims have emerged, they continue to face classical challenge and validation, as reported in the IBM Quantum Computing Blog.
The company’s below-threshold results mark a transition toward the fault-tolerant era, where faster logical operations and parallel execution become increasingly important as physical operations move further below the error threshold. The team’s focus is on accelerating transport, cooling, measurement, compilation, and parallel execution alongside continued fidelity improvements, recognizing that quantum computing is entering a new phase where the terms of the race are fundamentally changing.
Speed Alone Fails to Deliver Reliable Results
Helios contends that sustained, reliable computation demands a focus on fidelity above all else, rather than simply building faster gates. While superconducting systems often prioritize gate speed, the company’s recent experiments demonstrate that a slower, more accurate approach can yield more meaningful results, particularly as computations scale, the company’s account states. Theoretical work highlights this point, establishing a critical threshold where sufficiently noisy quantum computations can be efficiently approximated on classical computers, specifically within the range of 1-3.
This suggests a fundamental limit to quantum advantage if error rates are not adequately addressed. Helios’ approach centers on ensuring that quantum information remains coherent long enough to complete a computation, even if that means operating at a slower pace.
A growing body of research supports the idea that error correction, while adding overhead, is essential for unlocking the potential of quantum computers, but only if the underlying physical operations are already sufficiently reliable. The company’s October 2026 color-code results provide evidence of this principle in action. Operating below the color-code threshold, Helios demonstrated that increasing the code distance suppressed logical memory errors exponentially, and improved protected two-qubit Clifford operations, the company claims.
“Superconducting pairing correlations on a trapped-ion quantum computer,” was a key component of this success. This isn’t merely a matter of achieving lower error rates; it’s about building a system where stronger protection translates to longer, reliable computations. David Hayes explains that magic-state preparation and logical error correction measure different aspects of progress, highlighting the need for a complete view of system performance.
The challenge now lies in integrating these advancements, error correction, magic-state resources and real-time control, into extended, dependable computations. Decoding in the recent color-code benchmarks was performed offline, representing a significant hurdle to overcome for practical applications. The team’s work, alongside studies such as “Computing with many encoded logical qubits beyond break-even,” demonstrates a commitment to pushing the boundaries of what’s possible with quantum error correction. The goal isn’t simply to achieve faster gate speeds, but to create a system capable of delivering reliable results at scale.
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