Technical perspective: By the end of the decade, we will deliver universal, fully fault-tolerant quantum computing

September 17, 2024

By Dr. Harry Buhrman, Chief Scientist for Algorithms and Innovation, and Dr. Chris Langer, Fellow

This week, we confirm what has been implied by the rapid pace of our recent technical progress as we reveal a major acceleration in our hardware road map. By the end of the decade, our accelerated hardware roadmap will deliver a fully fault-tolerant and universal quantum computer capable of executing millions of operations on hundreds of logical qubits. 

The next major milestone on our accelerated roadmap is Quantinuum Helios™, Powered by Honeywell, a device that will definitively push beyond classical capabilities in 2025. That sets us on a path to our fifth-generation system, Quantinuum Apollo™, a machine that delivers scientific advantage and a commercial tipping point this decade.

What is Apollo?

We are committed to continually advancing the capabilities of our hardware over prior generations, and Apollo makes good on that promise. It will offer:

  • thousands of physical qubits
  • physical error rates less than 10-4
  • All of our most competitive features: all-to-all connectivity, low crosstalk, mid-circuit measurement and qubit re-use
  • Conditional logic
  • Real-time classical co-compute
  • Physical variable angle 1 qubit and 2 qubit gates
  • Hundreds of logical qubits
  • Logical error rates better than 10-6 with analysis based on recent literature estimating as low as 10-10

By leveraging our all-to-all connectivity and low error rates, we expect to enjoy significant efficiency gains in terms of fault-tolerance, including single-shot error correction (which saves time) and high-rate and high-distance Quantum Error Correction (QEC) codes (which mean more logical qubits, with stronger error correction capabilities, can be made from a smaller number of physical qubits). 

Studies of several efficient QEC codes already suggest we can enjoy logical error rates much lower than our target 10-6 – we may even be able to reach 10-10, which enables exploration of even more complex problems of both industrial and scientific interest.

Error correcting code exploration is only just beginning – we anticipate discoveries of even more efficient codes. As new codes are developed, Apollo will be able to accommodate them, thanks to our flexible high-fidelity architecture. The bottom line is that Apollo promises fault-tolerant quantum advantage sooner, with fewer resources.

Like all our computers, Apollo is based on the quantum charged coupled device (QCCD) architecture. Here, each qubit’s information is stored in the atomic states of a single ion. Laser beams are applied to the qubits to perform operations such as gates, initialization, and measurement. The lasers are applied to individual qubits or co-located qubit pairs in dedicated operation zones. Qubits are held in place using electromagnetic fields generated by our ion trap chip. We move the qubits around in space by dynamically changing the voltages applied to the chip. Through an alternating sequence of qubit rearrangements via movement followed by quantum operations, arbitrary circuits with arbitrary connectivity can be executed.

The ion trap chip in Apollo will host a 2D array of trapping locations. It will be fabricated using standard CMOS processing technology and controlled using standard CMOS electronics. The 2D grid architecture enables fast and scalable qubit rearrangement and quantum operations – a critical competitive advantage. The Apollo architecture is scalable to the significantly larger systems we plan to deliver in the next decade.

What is Apollo good for?

Apollo’s scaling of very stable physical qubits and native high-fidelity gates, together with our advanced error correcting and fault tolerant techniques will establish a quantum computer that can perform tasks that do not run (efficiently) on any classical computer. We already had a first glimpse of this in our recent work sampling the output of random quantum circuits on H2, where we performed 100x better than competitors who performed the same task while using 30,000x less power than a classical supercomputer. But with Apollo we will travel into uncharted territory.

The flexibility to use either thousands of qubits for shorter computations (up to 10k gates) or hundreds of qubits for longer computations (from 1 million to 1 billion gates) make Apollo a versatile machine with unprecedented quantum computational power. We expect the first application areas will be in scientific discovery; particularly the simulation of quantum systems. While this may sound academic, this is how all new material discovery begins and its value should not be understated. This era will lead to discoveries in materials science, high-temperature superconductivity, complex magnetic systems, phase transitions, and high energy physics, among other things.

In general, Apollo will advance the field of physics to new heights while we start to see the first glimmers of distinct progress in chemistry and biology. For some of these applications, users will employ Apollo in a mode where it offers thousands of qubits for relatively short computations; e.g. exploring the magnetism of materials. At other times, users may want to employ significantly longer computations for applications like chemistry or topological data analysis. 

But there is more on the horizon. Carefully crafted AI models that interact seamlessly with Apollo will be able to squeeze all the “quantum juice” out and generate data that was hitherto unavailable to mankind. We anticipate using this data to further the field of AI itself, as it can be used as training data. 

The era of scientific (quantum) discovery and exploration will inevitably lead to commercial value. Apollo will be the centerpiece of this commercial tipping point where use-cases will build on the value of scientific discovery and support highly innovative commercially viable products. 

Very interestingly, we will uncover applications that we are currently unaware of. As is always the case with disruptive new technology, Apollo will run currently unknown use-cases and applications that will make perfect sense once we see them. We are eager to co-develop these with our customers in our unique co-creation program.

How do we get there?

Today, System Model H2 is our most advanced commercial quantum computer, providing 56 physical qubits with physical two-qubit gate errors less than 10-3. System Model H2, like all our systems, is based on the QCCD architecture.

Starting from where we are today, our roadmap progresses through two additional machines prior to Apollo. The Quantinuum Helios™ system, which we are releasing in 2025, will offer around 100 physical qubits with two-qubit gate errors less than 5x10-4. In addition to expanded qubit count and better errors, Helios makes two departures from H2. First, Helios will use 137Ba+ qubits in contrast to the 171Yb+ qubits used in our H1 and H2 systems. This change enables lower two-qubit gate errors and less complex laser systems with lower cost. Second, for the first time in a commercial system, Helios will use junction-based qubit routing. The result will be a “twice-as-good" system: Helios will offer roughly 2x more qubits with 2x lower two-qubit gate errors while operating more than 2x faster than our 56-qubit H2 system.

After Helios we will introduce Quantinuum Sol™, our first commercially available 2D-grid-based quantum computer. Sol will offer hundreds of physical qubits with two-qubit gate errors less than 2x10-4, operating approximately 2x faster than Helios. Sol being a fully 2D-grid architecture is the scalability launching point for the significant size increase planned for Apollo.

Opportunity for early value creation discovery in Helios and Sol

Thanks to Sol’s low error rates, users will be able to execute circuits with up to 10,000 quantum operations. The usefulness of Helios and Sol may be extended with a combination of quantum error detection (QED) and quantum error mitigation (QEM). For example, the [[k+2, k, 2]] iceberg code is a light-weight QED code that encodes k+2 physical qubits into k logical qubits and only uses an additional 2 ancilla qubits. This low-overhead code is well-suited for Helios and Sol because it offers the non-Clifford variable angle entangling ZZ-gate directly without the overhead of magic state distillation. The errors Iceberg fails to detect are already ~10x lower than our physical errors, and by applying a modest run-time overhead to discard detected failures, the effective error in the computation can be further reduced. Combining QED with QEM, a ~10x reduction in the effective error may be possible while maintaining run-time overhead at modest levels and below that of full-blown QEC.

Why accelerate our roadmap now?

Our new roadmap is an acceleration over what we were previously planning. The benefits of this are obvious: Apollo brings the commercial tipping point sooner than we previously thought possible. This acceleration is made possible by a set of recent breakthroughs.

First, we solved the “wiring problem”: we demonstrated that trap chip control is scalable using our novel center-to-left-right (C2LR) protocol and broadcasting shared control signals to multiple electrodes. This demonstration of qubit rearrangement in a 2D geometry marks the most advanced ion trap built, containing approximately 40 junctions. This trap was deployed to 3 different testbeds in 2 different cities and operated with 2 different collections of dual-ion-species, and all 3 cases were a success. These demonstrations showed that the footprint of the most complex parts of the trap control stay constant as the number of qubits scales up. This gives us the confidence that Sol, with approximately 100 junctions, will be a success.

Second, we continue to reduce our two-qubit physical gate errors. Today, H1 and H2 have two-qubit gate errors less than 1x10-3 across all pairs of qubits. This is the best in the industry and is a key ingredient in our record >2 million quantum volume. Our systems are the most benchmarked in the industry, and we stand by our data - making it all publicly available. Recently, we observed an 8x10-4 two-qubit gate error in our Helios development test stand in 137Ba+, and we’ve seen even better error rates in other testbeds. We are well on the path to meeting the 5x10-4 spec in Helios next year.

Third, the all-to-all connectivity offered by our systems enables highly efficient QEC codes. In Microsoft’s recent demonstration, our H2 system with 56 physical qubits was used to generate 12 logical qubits at distance 4. This work demonstrated several experiments, including repeated rounds of error correction where the error in the final result was ~10x lower than the physical circuit baseline.

In conclusion, through a combination of advances in hardware readiness and QEC, we have line-of-sight to Apollo by the end of the decade, a fully fault-tolerant quantum advantaged machine. This will be a commercial tipping point: ushering in an era of scientific discovery in physics, materials, chemistry, and more. Along the way, users will have the opportunity to discover new enabling use cases through quantum error detection and mitigation in Helios and Sol.

Quantinuum has the best quantum computers today and is on the path to offering fault-tolerant useful quantum computation by the end of the decade.

About Quantinuum

Quantinuum, the world’s largest integrated quantum company, pioneers powerful quantum computers and advanced software solutions. Quantinuum’s technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With over 500 employees, including 370+ scientists and engineers, Quantinuum leads the quantum computing revolution across continents. 

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November 5, 2025
Helios Delivers Quantum Advantage with Real-World Impact

Quantinuum’s real world experiment, on the world’s most powerful quantum computer, is the largest of its kind— so large that no amount of classical computing could match it

Figure 1. Real image (not an artist’s depiction) of 98 single atoms (atomic ions) used for computation inside Quantinuum’s Helios quantum computer. The atomic ions are cooled to a fraction of a degree above absolute zero, so that their quantum state can be carefully controlled and manipulated to perform calculations that are very difficult, if not impossible, for classical supercomputers. 

In 1911, a student working under famed physicist Heike Kamerlingh Onnes made a discovery that would rewire our understanding of electricity. The student was studying the electrical resistance of wires, a seemingly simple question that held secrets destined to surprise the world. 

Kamerlingh Onnes had recently succeeded in liquefying helium, a feat so impressive it earned him the Nobel Prize in Physics two years later. With this breakthrough, scientists could now immerse other materials in a cold bath of liquid Helium, cooling things to unprecedented temperatures and observing their behavior.

Many theories existed about what would happen to a wire at such low temperatures. Lord Kelvin predicted that electrons would freeze in place, making the resistance infinite and stopping the conduction of electricity. Others expected resistance to decrease linearly with temperature—a hypothesis that led to thermometer designs still in use today.

When the student cooled a mercury wire to 3.6 degrees above absolute zero, he found something remarkable: the electrical resistivity suddenly vanished.

Onnes quickly devised an ingenious experiment: as a diligent researcher, he knew that he needed to validate these surprising findings. He took a closed loop of wire, set a current running through it, and watched as it flowed endlessly without fading—a type of perpetual motion that seemed to defy everything we know about physics. And so, superconductivity was born. 

More than a century later, all known superconductors still require extreme conditions like brutal cold or high pressure. If we could instead design a material that superconducts at room temperature, and under normal conditions, our world would be profoundly reshaped.  “Room temperature superconductivity”, as it is generally called, would enable a raft of technological breakthroughs from affordable MRI machines to nearly lossless power grids.

Designing such a material means answering many open questions, and scientists are pursuing diverse strategies to find answers. One promising approach is light-induced superconductivity. In one astonishing study, researchers at the Max Planck Institute in Hamburg used light to entice a material that normally superconducts at roughly -180 °C to superconduct at room temperature - but only for a few picoseconds. This effect raised new questions: how does light achieve something that scientists have been grappling with for decades? What is the microscopic mechanism behind this phenomenon? Could understanding it unlock practical room-temperature superconductors?

Nature’s language is mathematics and mathematics is the language of the world’s most powerful quantum computer, Helios

Physics is a surprisingly profound field when you stop to think about it. At its core lies the idea that nature speaks the language of mathematics—and that by discovering the right equations, we can reveal her secrets. As bold as that sounds, history has proven it true time and again. Whenever we peek behind the veil; mathematics is there.

To understand a phenomena like superconductivity, physicists first need a mathematical model, or a set of equations that describe how it works. With the right model, they can predict and even design new superconductors that operate under more practical conditions. This is a key frontier in the search for room temperature superconductors, one of science’s holy grails.

Since the discovery of superconductivity, a lot of work has gone into finding this right model – one that can act as a sort of ‘Rosetta stone’ for harnessing this phenomenon. One of the best bets for describing high temperature superconductors like the one in the Hamburg study is called the “non-equilibrium Fermi-Hubbard” model, which describes how electrons interact and move in a crystal. 

A surprising element of models that describe superconductivity is the prediction that electrons ‘pair up’ when the material becomes superconducting, dancing around in a waltz, two at a time. These pairs are referred to as “cooper pairs” after the famous physicist Leon Cooper. Now, scientists studying superconductors look for “pairing correlations”, a key signature of superconductivity.

Even armed with the Fermi-Hubbard model, light-induced superconductivity has been very difficult to study. The world’s most powerful supercomputers can only handle very small versions, limiting their utility. Even quantum platforms, like analog simulators, limit researchers to observing ‘average’ quantities and obscuring the microscopic details that are crucial for unravelling this mystery.

Light-induced superconductivity has proved challenging to study with quantum computers as well, as doing so requires low error rates, many qubits, and extreme flexibility to measure the fickle symptoms of superconductivity.

That was, until now: Quantinuum’s Helios is one of the first machines in the world able to handle the complexity of the non-equilibrium Fermi-Hibbard model at scales previously out of reach. 

Hopping across the lattice and connecting the dots

Before Helios, we were limited to small explorations of this model, stalling research on this critical frontier. Now, with Helios, we have a quantum computer uniquely suited for this problem. With a novel fermionic encoding and using up to 90 qubits (72 system qubits plus 18 ancilla), Helios can simulate the dynamics of a 6×6 lattice — a system so large that its full quantum state spans over 2^72 dimensions.

Figure 2. The Helios chip, which generates tiny electromagnetic fields to trap single atomic ions hovering above the chip to be used for computation.

Using Helios to study a system like this offers researchers a sort of “qubit-based laboratory.” Capable of handling complex quantum mechanical effects better than classical computers, Helios allows researchers to thoroughly explore phenomena like this without wasting expensive laboratory time and materials, or spending lots of money and energy running it on a supercomputer. 

Our qubit-based laboratory is a dream come true for several reasons. First, it allows arbitrary state preparation – preparing states far from equilibrium, a challenging task for classical computers. Second, it allows for meaningfully long ‘dynamical simulation’ – seeing how the state evolves in time as entanglement spreads and complexity increases. This is notoriously difficult for classical computers, in part due to their difficulty with handling distinctly quantum phenomena like entanglement. Finally, it allows for flexible measurements and experimental parameters – you can measure any observable, including critical “off-diagonal” observables that carry the signature of superconductivity, and simulate any system, such as those with laser pulses or electric fields. 

This last point is the most significant. While analog quantum simulators, like cold atom systems, can take snapshots of atom positions or measure densities, they struggle with off-diagonal observables—the very ones that signal the formation of Cooper pairs in superconductors.

Breaking new ground: a light-induced pairing

In our work, we've simulated three different regimes of the Fermi-Hubbard model and successfully measured non-zero superconducting pairing correlations — a first for any quantum computing platform.

We began by preparing a low-energy state of the model at half-filling — a standard benchmark for testing quantum simulations. Then, using simulated laser pulses or electric fields, we perturbed the system and observed how it responded.

After these perturbations, we measured a notable increase in the so-called “eta” pairing correlations, a mathematical signature of superconducting behavior. These results prove that our computers can help us understand light-induced superconductivity, such as the results from the Max Planck researchers. However, unlike those physical experiments, Helios offers a new level of control and insight. By tuning every aspect of the simulation — from pulse shape, to field strength, to lattice geometry — researchers can explore scenarios that are completely inaccessible to real materials or analog simulators.

Looking to a future where superconductors permeate our lives

Why does any of this matter? If we could predict which materials will become superconducting — and at what temperature, field, or current — it would transform how we search for new superconductors. Instead of trial-and-error in the lab, scientists could design and test new materials digitally first, saving huge amounts of time and money.

In the long run, Helios and its successors will become essential tools for materials science — not just confirming theories but generating new ones. And perhaps, one day, they’ll help us crack the code behind room-temperature superconductors.

Until then, the quantum revolution continues, one entangled pair at a time.

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November 5, 2025
Introducing Helios: The Most Accurate Quantum Computer in the World
A large room with a large rectangular objectAI-generated content may be incorrect.
Figure 1: A rendering of the Quantinuum Helios system deployed at a customer site. 

We’re pleased to introduce Helios, a technological marvel redefining the possible. 

Building on its predecessor H2, which has already breached quantum advantage, Helios nearly doubles the qubit count and surpasses H2’s industry-leading fidelity, pushing further into the quantum advantage regime than any system before it. With unprecedented capability across its full stack, Helios is the most powerful quantum computer in the world. 

“Helios is a true marvel—a seamless fusion of hardware and software, creating a platform for discovery unlike any other.”- Dr. Rajeeb Hazra, CEO 

Helios’ groundbreaking design and advanced software stack bring quantum programming closer than ever to the ease and flexibility of classical computing—positioning Helios to accelerate commercial adoption. Even before its public debut, Helios had already demonstrated its capabilities as the world’s first enterprise-grade quantum computer. During a two-month early access program, select partners including SoftBank Corp. and JPMorgan Chase conducted commercially relevant research. We also leveraged Helios to perform large-scale simulations in high-temperature superconductivity and quantum magnetism—both with clear pathways to real-world industry applications.

Helios is now available to all customers through our cloud service and on-premise offering, including an option to integrate with NVIDIA GB200 for applications targeting specific end markets.     

A Stellar Quantum Computer 
“You would need to harvest every star in the universe to power a classical machine that could do the same calculations we did with Helios."
- Dr. Anthony Ransford, Helios Lead Architect
Figure 2: Random Circuit Sampling (RCS) results on Helios. Running the same calculation classically in the same amount of time would require the power of all the stars in the visible universe.

As we detailed in a benchmarking paper, Helios sets a new standard for quantum computing performance with the highest fidelity ever released to the market. It features 98 fully connected physical qubits with single-qubit gate fidelity of 99.9975% and two-qubit gate fidelity of 99.921% across all qubit pairs—making it the most accurate commercial quantum computer in the world.  

Our fidelity shines in system-level benchmarks, such as Random Circuit Sampling (RCS), famously used by Google to demonstrate quantum supremacy when it performed an RCS task that would take a classical computer “10 septillion years” to replicate. Now, RCS serves as both a benchmark and the minimum standard for serious competitors in the market. Frequently missed in this conversation, however, is the importance of fidelity, or accuracy. That's why, when benchmarking Helios using RCS, we report the fidelity achieved by Helios on circuits of varying complexity (with complexity quantified by power requirements for classical simulation).

Our results show a classical supercomputer would require more power than the Sun—or, in fact, the combined power of all stars in the visible universe—to complete the same task in the same amount of time. In contrast, Helios achieved it using roughly the power of a single data center rack. 

Like its predecessors, H1 and H2, Helios is designed to improve fidelity and overall system performance over time while sustaining competitive leadership through the launch of its successor.

Qubits at a Crossroads
Figure 3: The Helios chip, which generates tiny electromagnetic fields to trap single atomic ions hovering above the chip, which are then used for computation. The Helios chip contains the world’s first commercial ion junction – enabling a huge jump in architectural design and opening the door to true scaling.
"When I first saw the rotatable ion storage ring with a junction and gating legs sketched on a napkin, I loved the idea for its simplicity and efficiency. Seeing it finally realized after all of the team’s hard work has been truly incredible." 
- Dr. John Gaebler, Fellow and Chief Scientist, Quantinuum

The Helios ion trap uses tiny currents to generate electromagnetic fields that hold single atomic ions (qubits) hovering above the trap for computation. We introduced a first-of-its-kind “junction”, which acts like a traffic intersection for qubits, enabling efficient routing and improved reliability. This is not only the first commercial implementation of this engineering triumph but it also allows our QCCD (Quantum Charged Coupled Device) architecture to scale, with future systems featuring hundreds of junctions arranged like a city street grid.   

Illustration:The Helios QPU. Ions rotate through the ring storage to the cache and logic zones for gating. Image adapted from benchmarking paper.

Whereas predecessor systems routed qubits using “physical swaps,” requiring sequential sorting, cooling, and gating that prevented parallel operations, the Helios QPU instead resembles a classical architecture with dedicated memory, cache, and computational zones. Like a spinning hard drive, the Helios QPU rotates qubits through ring storage (memory), passes them through the junction into the cache, moves them to logic zones for gating, and moves them to the leg storage while the next batch is processed. Sorting can now be done in parallel with cooling operations, resulting in a processor that is faster and less error prone.  This parallelism will become a hallmark of Quantinuum’s future generations, enabling faster operating speeds.

Animation: This triumph of engineering demonstrates exquisite control over some of nature’s smallest particles in a way the world has never seen; one colleague likened the ions to a “little marching band.”

Quantinuum’s QCCD provides full all-to-all connectivity, giving the Helios QPU significant advantages over “fixed qubit” architectures, such as those used in superconducting systems. Its ability to physically move qubits around and entangle any qubit with any other qubit enables algorithms and error-correcting codes that are functionally impossible for fixed qubit architectures. 

A blue dot pattern on a black backgroundAI-generated content may be incorrect.
Image: Real image of 98 single Barium atoms (atomic ions) used for computation inside Quantinuum’s Helios quantum computer.

We made another “tiny” but significant change: we switched our qubits from ytterbium to barium. Whereas ytterbium largely relied on ultraviolet lasers that are expensive and hard on other components, barium can be manipulated with lasers in the visible part of the spectrum, where mature industrial technology exists, providing a more affordable, reliable and scalable commercial solution.

Barium also naturally allows the quantum computer to detect and remove a certain type of error, known as leakage, at the atomic level. By addressing this error directly, programmers can enhance the performance of their computation.

Delivered on Time – in Real Time

As announced earlier this year, Helios launched with a completely new stack equipped with a new software environment that makes quantum programming feel as intuitive as classical development. 

Our new stack also features a real-time engine that massively improves our capability. With a real-time control system, we are evolving from static, pre-planned circuits to dynamic quantum programs that respond to results on the fly. We can now, for the first time on a quantum computer, interleave GPU-accelerated classical and quantum computations in a single program. 

Our real-time engine also means we have dynamic transport – routing qubits as the moment demands reduces time to solution and diminishes the impact of memory errors.  

Programmers can now use our new quantum programming language, Guppy, to write dynamic circuits that were previously impossible. By combining Guppy with our real-time engine, developers can leverage arbitrary control flow driven by quantum measurements, as well as full classical computation—including loops, higher-order functions, early exits, and dynamic qubit allocation. Far from being mere conveniences, these capabilities are essential stepping stones toward achieving fault-tolerant quantum computing at scale—putting us decisively ahead of the competition.

Fully compatible with industry standards like QIR and tools such as NVIDIA CUDA-Q, Helios bridges classical and quantum computing more seamlessly than ever, making hybrid quantum-classical development simple, natural, and accessible, and establishing Helios as the most programmable, general-purpose quantum computer ever built.  

The Most Logical Path to Fault Tolerance

While everyone else is promising fault-tolerance, we’re delivering it. We are the only company to demonstrate a fully universal fault-tolerant gate set, we’ve demonstrated more codes than anyone else, and our logical fidelities are the best in class.

Now, with 98 physical qubits, we’ve been able to make 94 logical qubits, fully entangled in one of the largest GHZ states ever recorded. We did this with better than break-even fidelity, meaning they outperform physical qubits running the same algorithm. Built on our Iceberg code, published last year in Nature Physics, these logical qubits achieve the industry’s highest encoding efficiency, needing only two ancilla qubits per code block, or roughly a 1:1 physical-to-logical qubit ratio.

With 50 error-detected logical qubits, Helios achieved better than break-even performance, running the largest encoded simulation of quantum magnetism to date—an exceptional example of how users can leverage efficient encodings. This range and flexibility let users tailor the encoding rate to their application: fewer logical qubits deliver higher fidelity for less complex tasks, while larger sets enable more complex simulations.

Helios also produced 48 fully error-corrected logical qubits at a remarkable 2:1 encoding rate, a ratio thought impossible just a few years ago. This super high encoding rate stands in stark contrast to other notable demonstrations from industry peers. For example, the demonstration linked in the previous sentence would need a whopping 4800 qubits to make 48 logical qubits. Our 2:1 encoding rate was achieved through a clever technique called code concatenation, a breakthrough that supports single-shot error correction, transversal logic, and full parallelization—all at 99.99% state preparation and measurement fidelity. 

To extend this performance at scale, all future Quantinuum systems—starting with Helios—will integrate real-time decoding using NVIDIA Grace Hopper GPUs, treating decoding as a dynamic computational process rather than a static lookup. Errors can be corrected as computations run without slowing the logical clock rate. Combined with Guppy, NVIDIA CUDA-Q, and NVQLink, this infrastructure forms the foundation for fault-tolerant, real-time quantum computation, delivering immediate quantum advantage in the near term and a clear path to scalable error-corrected computing. 

We remain the only company to perform a fully universal fault-tolerant gate set, with more error-correcting codes and higher logical fidelities than any other company.

Helios is ready to drive practical, commercial quantum applications across industries. Its unprecedented fidelity, scalability, and programmability give users the tools to tackle problems that were previously out of reach. This is just the beginning, and we look forward to seeing what users and companies will achieve with it. 

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October 30, 2025
Scalable Quantum Error Detection

Typically, Quantum Error Detection (QED) is viewed as a short-term solution—a non-scalable, stop-gap until full fault tolerance is achieved at scale.

That’s just changed, thanks to a serendipitous discovery made by our team. Now, QED can be used in a much wider context than previously thought. Our team made this discovery while studying the contact process, which describes things like how diseases spread or how water permeates porous materials. In particular, our team was studying the quantum contact process (QCP), a problem they had tackled before, which helps physicists understand things like phase transitions. In the process (pun intended), they came across what senior advanced physicist, Eli Chertkov, described as “a surprising result.”

While examining the problem, the team realized that they could convert detected errors due to noisy hardware into random resets, a key part of the QCP, thus avoiding the exponentially costly overhead of post-selection normally expected in QED.

To understand this better, the team developed a new protocol in which the encoded, or logical, quantum circuit adapts to the noise generated by the quantum computer. They quickly realized that this method could be used to explore other classes of random circuits similar to the ones they were already studying.

The team put it all together on System Model H2 to run a complex simulation, and were surprised to find that they were able to achieve near break-even results, where the logically encoded circuit performed as well as its physical analog, thanks to their clever application of QED.  Ultimately, this new protocol will allow QED codes to be used in a scalable way, saving considerable computational resources compared to full quantum error correction (QEC).

Researchers at the crossroads of quantum information, quantum simulation, and many-body physics will take interest in this protocol and use it as a springboard for inventing new use cases for QED.

Stay tuned for more, our team always has new tricks up their sleeves.

Learn mode about System Model H2 with this video:

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