Quantinuum hits 99.9995% logical fidelity on Helios, partly ahead of Sol targets

【Article Title】 Quantinuum hits 99.9995% logical fidelity on Helios, partly ahead of Sol targets 【Article Body】 AI TRANSLATION This article is an AI-generated translation of the original Japanese article. For the authoritative version, please refer to the original. Read the original Japanese article → (https://quantumindex.jp/quantinuum-helios-logical-fidelity-999995/) Quantinuum announced that it executed quantum error correctionquantum error correction量子誤り訂正 / Quantum Error Correction / QECA technique that distributes information across multiple physical qubits and detects and corrects errors without directly disturbing the quantum state.QI NoteSimply implementing it does not automatically provide practical fault tolerance. What matters is whether the logical error rate is improved relative to the physical error rate. using the color code on its trapped‑ion quantum computer Helios and achieved a logical fidelity of 99.9995%. While the company reduced its error rate to one‑tenth of the result reported in September 2026, large‑scale logical computations and reproducibility in commercial environments have not yet been demonstrated. ✍️ Quantum Index Analysis We explain the technical and business significance behind the announcement and the evaluation points that may not be apparent from numbers or headlines alone. Read our exclusive analysis ↓ Summary of the announcement In the experiment, Quantinuum used the color code on Helios and recorded a logical fidelity equivalent to five errors per one million operations (99.9995%). According to the company, this error rate is one‑tenth of the result it achieved in September 2026 and one‑hundredth of the best published value reported by Google Quantum AI for a different superconducting system. In experiments with increased code distance, residual logical errors decreased by a factor of 1/12 at each step, showing exponential suppression of errors. The company’s error‑correction architecture integrates an AI decoder, all‑to‑all qubitqubitQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important. connectivity, high‑fidelity physical operations, hardware‑level error mitigation, and real‑time decoding. Earlier on the same Helios system, experiments using the Helix code were performed in September 2026. While the Helix code used ten physical qubitsphysical qubitsPhysical Qubit / Physical QubitIndividual qubits that are physically created and manipulated on a quantum processor. They are also used to form logical qubits.QI NoteA large number of physical qubits does not by itself indicate practical computational capability. Error rates, connectivity, and the number of physical qubits required per logical qubit are also important. per logical qubitlogical qubitLogical Qubit / Logical QubitA unit of information treated as a single qubit protected from errors by using multiple physical qubits and quantum error correction.QI NoteSimply having “created a logical qubit” does not necessarily mean fault-tolerant quantum computing (FTQC) has been achieved. One should verify logical error rates, operational/gate performance, and scalability., the color code used up to 37 physical qubits per logical qubit in this experiment and achieved a lower logical error rate. This demonstrates the ability to switch codes on the same hardware to balance accuracy and resource requirements. Quantinuum says the performance falls within the target range for Apollo, a general fault‑tolerant quantum computer planned for delivery by 2029. However, the delivery date, system scalability, and required physical qubit counts are forward‑looking projections and this single result does not guarantee realization. Key points • Using Helios and the color code, Quantinuum recorded a logical fidelity of 99.9995%, equivalent to five errors per one million operations. • Quantinuum reports the error rate is ten times lower than its September 2026 record. • Increasing code distance reduced residual logical errors by a factor of 1/12 at each step. • On the same hardware, Quantinuum tested the Helix code (physically efficient) and the color code (lower logical errors) to tune the balance between qubit efficiency and error rate. • Quantinuum says the result falls within Apollo’s target range, but performance at scale and in commercial use remains unproven. Technical and business significance The observed exponential decrease in logical errors with increasing code distance is a technical milestone showing that quantum error correction can indeed suppress physical qubit errors. Being able to use different error‑correction codes on the same hardware makes it easier to choose designs according to accuracy, speed, or required physical qubit counts. From a business perspective, the result supports the Apollo development roadmap, but claims that fault tolerance can be achieved with fewer qubits or that practical computations are now within reach are not yet demonstrated. Points to watch The next focus is whether the same level of error suppression can be maintained for larger numbers of logical qubits and longer computations. It will also be important to see how switching between Helix and color codes affects the physical‑qubit requirements and processing efficiency for real workloads. For Apollo, assessment criteria include the integration status of hardware, error correction, and software, and whether Quantinuum can present concrete evidence supporting the 2029 delivery plan and commercial performance. ✍️ Quantum Index Analysis This result can be viewed as a significant step toward practical quantum error correctionquantum error correction量子誤り訂正 / Quantum Error Correction / QECA technique that distributes information across multiple physical qubits and detects and corrects errors without directly disturbing the quantum state.QI NoteSimply implementing it does not automatically provide practical fault tolerance. What matters is whether the logical error rate is improved relative to the physical error rate.. Beyond the headline figure of 99.9995% logical fidelity, the fact that logical error rates dropped by about a factor of 12 each time code distance was increased is particularly important. In quantum error correction, adding qubitsqubitsQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important. to suppress errors can itself introduce new control errors. This experiment showed that adding physical qubitsphysical qubitsPhysical Qubit / Physical QubitIndividual qubits that are physically created and manipulated on a quantum processor. They are also used to form logical qubits.QI NoteA large number of physical qubits does not by itself indicate practical computational capability. Error rates, connectivity, and the number of physical qubits required per logical qubit are also important. to strengthen error correction actually yielded a large improvement in reliability. Also notable is that this result partially preempts performance targets set for future hardware generations. Quantinuum plans Sol for 2027 with a target of roughly 100 logical qubitslogical qubitsLogical Qubit / Logical QubitA unit of information treated as a single qubit protected from errors by using multiple physical qubits and quantum error correction.QI NoteSimply having “created a logical qubit” does not necessarily mean fault-tolerant quantum computing (FTQC) has been achieved. One should verify logical error rates, operational/gate performance, and scalability. and 99.999% logical fidelity, and Apollo for 2029 with a target of several hundred logical qubits and up to 99.99999999% logical fidelity. The 99.9995% achieved on Helios, while obtained under limited experimental conditions, numerically exceeds the logical fidelity target set for the next‑generation Sol. Quantinuum hardware development roadmap GenerationSystemRelease / plannedQubit countKey features / targets1st generationH1202020 physical qubitsHigh‑fidelity gates, all‑to‑all connectivity2nd generationH2202356 physical qubitsRace‑track architecture, demonstration of error correction3rd generationHelios202598 physical qubitsAdopts Ba⁺ ions; demonstrated 99.9995% logical fidelity4th generationSolPlanned 2027~100 logical qubits (target)Target: 99.999% logical fidelity5th generationApolloPlanned 2029Several hundred logical qubits (target)Up to 99.99999999% logical fidelity; general fault‑tolerant computing ※ The H1 and H2 qubit counts are after expansion. Sol and Apollo figures are future development targets, and physical qubit counts and logical qubit counts are not directly comparable. Another important achievement is that the same Helios hardware was used with different quantum error correction codes to improve performance. The Helix code tested in September 2026 used ten physical qubits per logical qubit, whereas the color code in this experiment used up to 37 physical qubits per logical qubit and achieved a lower logical error rate. This is not merely a performance increase: it suggests the possibility of selecting or combining error‑correction schemes to meet differing demands for qubit efficiency, accuracy, and processing speed. The fact that performance can be raised by improving error‑correction techniques without changing the underlying hardware is also significant. However, these results alone do not mean Sol’s full performance targets have been met. Simultaneously running about 100 logical qubits and stably executing long quantum circuits have not yet been demonstrated. The comparison that Quantinuum’s error rate is 1/100 of Google Quantum AI’s superconducting system also requires consideration of differences in measurement targets and execution conditions. Trapped‑ion systems tend to have relatively slow gate speeds, so low logical error rates do not automatically translate into shorter wall‑clock computation times. This achievement is not just a future projection but an experimental result obtained on commercially available hardware. Strengthening error correction substantially improved reliability, and different codes can be used to optimize performance—this has major significance. The next focus is whether this high logical fidelity can be extended to many logical qubits and connected to Apollo in 2029. NETWORKSee the industry network around Quantinuum → (/qi-network/) Related articles • Who will control the classical side of quantum computers? The quantum computing infrastructure race from NVIDIA and AMD (https://en.quantumindex.jp/quantum-classical-infrastructure-nvidia-amd/) • IonQ processes error correction on a single CPU — verification for 408 logical qubits claimed, but actual hardware not yet available (https://en.quantumindex.jp/ionq-real-time-quantum-error-decoder-single-cpu/) • QuEra survey: evaluation metrics shift from qubit counts to QEC and logical performance — a trend shared with IBM (https://en.quantumindex.jp/quera-quantum-readiness-survey-fault-tolerance-2026/) Source Read the original announcement (https://www.quantinuum.com/press-releases/quantinuum-breaks-error-correction-world-record-by-10x-validating-its-leading-path-to-fault-tolerant-quantum-computing-by-2029) If you found this article useful, please consider sharing it. ──────────────────── 【AI Evaluation Request】 Evaluate the following article critically, not based on the quality of its writing, but on its **original informational value as a specialist publication**. Do not give a high rating to summaries, paraphrases, explanations of technical terms, or generic observations such as "this will be worth watching" or "the timeline remains uncertain" if they could easily be produced by a general-purpose generative AI, even if they are well written. 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Quantinuum announced that it executed quantum error correctionquantum error correction量子誤り訂正 / Quantum Error Correction / QECA technique that distributes information across multiple physical qubits and detects and corrects errors without directly disturbing the quantum state.QI NoteSimply implementing it does not automatically provide practical fault tolerance. What matters is whether the logical error rate is improved relative to the physical error rate. using the color code on its trapped‑ion quantum computer Helios and achieved a logical fidelity of 99.9995%. While the company reduced its error rate to one‑tenth of the result reported in September 2026, large‑scale logical computations and reproducibility in commercial environments have not yet been demonstrated.

Summary of the announcement

In the experiment, Quantinuum used the color code on Helios and recorded a logical fidelity equivalent to five errors per one million operations (99.9995%). According to the company, this error rate is one‑tenth of the result it achieved in September 2026 and one‑hundredth of the best published value reported by Google Quantum AI for a different superconducting system. In experiments with increased code distance, residual logical errors decreased by a factor of 1/12 at each step, showing exponential suppression of errors. The company’s error‑correction architecture integrates an AI decoder, all‑to‑all qubitqubitQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important. connectivity, high‑fidelity physical operations, hardware‑level error mitigation, and real‑time decoding. Earlier on the same Helios system, experiments using the Helix code were performed in September 2026. While the Helix code used ten physical qubitsphysical qubitsPhysical Qubit / Physical QubitIndividual qubits that are physically created and manipulated on a quantum processor. They are also used to form logical qubits.QI NoteA large number of physical qubits does not by itself indicate practical computational capability. Error rates, connectivity, and the number of physical qubits required per logical qubit are also important. per logical qubitlogical qubitLogical Qubit / Logical QubitA unit of information treated as a single qubit protected from errors by using multiple physical qubits and quantum error correction.QI NoteSimply having “created a logical qubit” does not necessarily mean fault-tolerant quantum computing (FTQC) has been achieved. One should verify logical error rates, operational/gate performance, and scalability., the color code used up to 37 physical qubits per logical qubit in this experiment and achieved a lower logical error rate. This demonstrates the ability to switch codes on the same hardware to balance accuracy and resource requirements. Quantinuum says the performance falls within the target range for Apollo, a general fault‑tolerant quantum computer planned for delivery by 2029. However, the delivery date, system scalability, and required physical qubit counts are forward‑looking projections and this single result does not guarantee realization.

Key points

• Using Helios and the color code, Quantinuum recorded a logical fidelity of 99.9995%, equivalent to five errors per one million operations.
• Quantinuum reports the error rate is ten times lower than its September 2026 record.
• Increasing code distance reduced residual logical errors by a factor of 1/12 at each step.
• On the same hardware, Quantinuum tested the Helix code (physically efficient) and the color code (lower logical errors) to tune the balance between qubit efficiency and error rate.
• Quantinuum says the result falls within Apollo’s target range, but performance at scale and in commercial use remains unproven.

Technical and business significance

The observed exponential decrease in logical errors with increasing code distance is a technical milestone showing that quantum error correction can indeed suppress physical qubit errors. Being able to use different error‑correction codes on the same hardware makes it easier to choose designs according to accuracy, speed, or required physical qubit counts. From a business perspective, the result supports the Apollo development roadmap, but claims that fault tolerance can be achieved with fewer qubits or that practical computations are now within reach are not yet demonstrated.

Points to watch

The next focus is whether the same level of error suppression can be maintained for larger numbers of logical qubits and longer computations. It will also be important to see how switching between Helix and color codes affects the physical‑qubit requirements and processing efficiency for real workloads. For Apollo, assessment criteria include the integration status of hardware, error correction, and software, and whether Quantinuum can present concrete evidence supporting the 2029 delivery plan and commercial performance.

✍️ Quantum Index Analysis

This result can be viewed as a significant step toward practical quantum error correctionquantum error correction量子誤り訂正 / Quantum Error Correction / QECA technique that distributes information across multiple physical qubits and detects and corrects errors without directly disturbing the quantum state.QI NoteSimply implementing it does not automatically provide practical fault tolerance. What matters is whether the logical error rate is improved relative to the physical error rate.. Beyond the headline figure of 99.9995% logical fidelity, the fact that logical error rates dropped by about a factor of 12 each time code distance was increased is particularly important. In quantum error correction, adding qubitsqubitsQubit / Quantum Bit / QubitThe basic unit of information in a quantum computer. It can represent not only 0 or 1 but also a quantum state that is a superposition of them.QI NoteHaving more qubits does not necessarily mean higher performance. Error rates, connectivity, coherence time, and the number of logical qubits are also important. to suppress errors can itself introduce new control errors. This experiment showed that adding physical qubitsphysical qubitsPhysical Qubit / Physical QubitIndividual qubits that are physically created and manipulated on a quantum processor. They are also used to form logical qubits.QI NoteA large number of physical qubits does not by itself indicate practical computational capability. Error rates, connectivity, and the number of physical qubits required per logical qubit are also important. to strengthen error correction actually yielded a large improvement in reliability.

Also notable is that this result partially preempts performance targets set for future hardware generations. Quantinuum plans Sol for 2027 with a target of roughly 100 logical qubitslogical qubitsLogical Qubit / Logical QubitA unit of information treated as a single qubit protected from errors by using multiple physical qubits and quantum error correction.QI NoteSimply having “created a logical qubit” does not necessarily mean fault-tolerant quantum computing (FTQC) has been achieved. One should verify logical error rates, operational/gate performance, and scalability. and 99.999% logical fidelity, and Apollo for 2029 with a target of several hundred logical qubits and up to 99.99999999% logical fidelity. The 99.9995% achieved on Helios, while obtained under limited experimental conditions, numerically exceeds the logical fidelity target set for the next‑generation Sol.

Quantinuum hardware development roadmap

Generation	System	Release / planned	Qubit count	Key features / targets
1st generation	H1	2020	20 physical qubits	High‑fidelity gates, all‑to‑all connectivity
2nd generation	H2	2023	56 physical qubits	Race‑track architecture, demonstration of error correction
3rd generation	Helios	2025	98 physical qubits	Adopts Ba⁺ ions; demonstrated 99.9995% logical fidelity
4th generation	Sol	Planned 2027	~100 logical qubits (target)	Target: 99.999% logical fidelity
5th generation	Apollo	Planned 2029	Several hundred logical qubits (target)	Up to 99.99999999% logical fidelity; general fault‑tolerant computing

※ The H1 and H2 qubit counts are after expansion. Sol and Apollo figures are future development targets, and physical qubit counts and logical qubit counts are not directly comparable.

Another important achievement is that the same Helios hardware was used with different quantum error correction codes to improve performance. The Helix code tested in September 2026 used ten physical qubits per logical qubit, whereas the color code in this experiment used up to 37 physical qubits per logical qubit and achieved a lower logical error rate. This is not merely a performance increase: it suggests the possibility of selecting or combining error‑correction schemes to meet differing demands for qubit efficiency, accuracy, and processing speed. The fact that performance can be raised by improving error‑correction techniques without changing the underlying hardware is also significant.

However, these results alone do not mean Sol’s full performance targets have been met. Simultaneously running about 100 logical qubits and stably executing long quantum circuits have not yet been demonstrated. The comparison that Quantinuum’s error rate is 1/100 of Google Quantum AI’s superconducting system also requires consideration of differences in measurement targets and execution conditions. Trapped‑ion systems tend to have relatively slow gate speeds, so low logical error rates do not automatically translate into shorter wall‑clock computation times.

This achievement is not just a future projection but an experimental result obtained on commercially available hardware. Strengthening error correction substantially improved reliability, and different codes can be used to optimize performance—this has major significance. The next focus is whether this high logical fidelity can be extended to many logical qubits and connected to Apollo in 2029.

NETWORKSee the industry network around Quantinuum →

Related articles

• Who will control the classical side of quantum computers? The quantum computing infrastructure race from NVIDIA and AMD
• IonQ processes error correction on a single CPU — verification for 408 logical qubits claimed, but actual hardware not yet available
• QuEra survey: evaluation metrics shift from qubit counts to QEC and logical performance — a trend shared with IBM

Source

Read the original announcement