With 20 Qubits, the H1-1 Quantum Runs More Complex Algorithm
Our flagship quantum computer, System Model H1-1, is now running on 20 qubits
We sat down with Brian Neyenhuis, 夜色直播鈥檚 director of commercial operations to ask him about the 20-qubit upgrade, some of the technical details, and how this launch paves the way for scaling trapped-ion quantum computers in the future.
What are some of the key upgrades made to the H1-1 machine?
The biggest, or maybe the most notable, is that we expanded the number of fully connected qubits from 12 to 20. That is a significant increase and the most qubits we鈥檝e added to an existing machine. Last year, we added two fully connected qubits to the 10 qubits H1-1 already had. It was a major accomplishment at the time. Now, that seems easy compared to this upgrade because for us, it is not as simple as adding qubits.
To add eight more qubits and maintain all-to-all connectivity, we upgraded the optics that deliver the light used to control our qubits. Previously, we were only delivering the light needed to complete quantum gates to three different regions of the trap, which we call gate zones. Now we can address all five zones in our trap simultaneously. This enables us to complete more single-qubit or two-qubit gates in parallel, which means users can run complex algorithms without experiencing a slowdown.
How does this compare to previous hardware upgrades?
This one was significantly more involved than previous upgrades. Although we didn鈥檛 modify the trap at the heart of the computer or the vacuum chamber and cryostat that enclose it, we redesigned the entire optical delivery system. This was necessary so as not to deliver light to more regions of the trap, but also to improve stability.
Increasing the size and complexity of the machine without improving the stability would be a recipe for disaster. Because we were able to improve the stability, we were able to add more qubits without sacrificing performance or key features our users expect such as all-to-all connectivity, high single and two-qubit gate fidelities, and mid-circuit measurement.
Why is the increase in zones significant?
The gate zones are where all the interesting quantum stuff happens. More zones allow us to run more quantum operations in parallel, allowing for faster, more complex algorithms.
What's the connection between more zones and more qubits?
Having more gate zones allows us to use more qubits in an efficient way.
Because we can do all these operations in five different locations in parallel, it finally makes sense to put more qubits into the trap. We could have loaded more qubits into earlier versions of the system, but without additional gate zones, it doesn鈥檛 make a lot of sense. In fact, doing that would create a bottleneck with qubits waiting for their turn to do a two-qubit gate, which then slows down an algorithm. Now, we can do five quantum gates in parallel, which allows us to run more complex algorithms without sacrificing speed.
Twenty qubits are probably where this generation of traps ends. There is a possibility to add a handful more, but it feels like this is probably the most efficient number for these H1 Systems due to layout of the trap. But future generations, some of which are already trapping ions in the lab today, will use even more qubits and with the same or better efficiency.
What is the 鈥渋on dance鈥?
In the QCCD architecture, trapped ions are easy to move around. By applying the right set of voltages to the trap 鈥 a small, electrode-filled device that holds qubits in place 鈥 we can arbitrarily rearrange the chain of qubits so any qubit can pair with any other and perform a quantum gate. So, you can think of any algorithm as a set of steps where we shuffle all the qubits to pair them up for the next set of gates, move them into the gate zones, and then shuffle them again to set them up for the next set of gates. The ions 鈥渄ance鈥 across the trap moving from partner to partner to execute a quantum circuit.
Some circuits, like quantum volume circuits, are densely packed, meaning that every possible pair wants to do a gate at each step of the circuit. Other circuits are very loosely packed, meaning you can only do a few gates in parallel before moving on to the next slice because you need to reuse one of those qubits with a different partner.
Although this dance may sound complicated, it makes it very easy to program our quantum computer. A user sends us a time-ordered set of gates without having to think about the layout of the qubits, and our compiler figures out how to pair up the appropriate qubits to make it happen. You don't have to worry about which ones are next to each other because any pair of qubits is equal to all the others. And, at any step, we can completely rearrange this chain and put any two qubits next to each other.
It鈥檚 like a square dance where someone calls out directions to the dancers.
Anything else in the works for 夜色直播鈥檚 hardware this year?
We will continue to work with our customers to improve our system performance and their overall experience. One of the reasons we have a commercial system now is to allow our customers to program their algorithms on a real machine. They're dealing with all the constraints of real quantum hardware. They're pushing on their algorithms while we're pushing on the hardware, to get the fastest iterations.
As they learn new things about their algorithm, we learn what the most important things are to improve. And we work on those. We are learning a lot from our customers, and they are learning a lot by running on our hardware.
About 夜色直播
夜色直播,聽the world鈥檚 largest integrated quantum company, pioneers powerful quantum computers and advanced software solutions. 夜色直播鈥檚 technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With over 500 employees, including 370+ scientists and engineers, 夜色直播 leads the quantum computing revolution across continents.聽
Quantum computing companies are poised to exceed $1 billion in revenues by the close of 2025, to McKinsey & Company, underscoring how today鈥檚 quantum computers are already delivering customer value in their current phase of development.
This figure is projected to reach upwards of $37 billion by 2030, rising in parallel with escalating demand, as well as with the scale of the machines and the complexity of problem sets of which they will be able to address. 聽
Several systems on the market today are fault-tolerant by design, meaning they are capable of suppressing error-causing noise to yield reliable calculations. However, the full potential of quantum computing to tackle problems of true industrial relevance, in areas like medicine, energy, and finance, remains contingent on an architecture that supports a fully fault-tolerant universal gate set with repeatable error correction鈥攁 capability that, until now, has eluded the industry. 聽
夜色直播 is the first鈥攁nd only鈥攃ompany to achieve this critical technical breakthrough, universally recognized as the essential precursor to scalable, industrial-scale quantum computing. This milestone provides us with the most de-risked development roadmap in the industry and positions us to fulfill our promise to deliver our universal, fully fault-tolerant quantum computer, Apollo, by 2029.
In this regard, 夜色直播 is the first company to step from the so-called 鈥淣ISQ鈥 (noisy intermediate-scale quantum) era towards utility-scale quantum computers.
Unpacking our achievement: first, a 鈥榝ull鈥 primer
A quantum computer uses operations called gates to process information in ways that even today鈥檚 fastest supercomputers cannot. The industry typically refers to two types of gates for quantum computers:
- Clifford gates, which can be easily simulated by classical computers, and are relatively easy to implement; and
- Non-Clifford gates, which are usually harder to implement, but are required to enable true quantum computation (when combined with their siblings).
A system that can run both gates is classified as and has the machinery to tackle the widest range of problems. Without non-Clifford gates, a quantum computer is non-universal and restricted to smaller, easier sets of tasks - and it can always be simulated by classical computers. This is like painting with a full palette of primary colors, versus only having one or two to work with. Simply put, a quantum computer that cannot implement 鈥榥on-Clifford鈥 gates is not really a quantum computer.
A fault-tolerant, or error-corrected, quantum computer detects and corrects its own errors (or faults) to produce reliable results. 夜色直播 has the best and brightest scientists dedicated to keeping our systems鈥 error rates the lowest in the world.
For a quantum computer to be fully fault-tolerant, every operation must be error-resilient, across Clifford gates and non-Clifford gates, and thus, performing 鈥渁 full gate set鈥 with error correction. While some groups have performed fully fault-tolerant gate sets in academic settings, these demonstrations were done with only a few qubits and 鈥攖oo high for any practical use.
Today, we have published that establishes 夜色直播 as the first company to develop a complete solution for a universal fully fault-tolerant quantum computer with repeatable error correction, and error rates low enough for real-world applications.
This is where the magic happens
The describes how scientists at 夜色直播 used our System Model H1-1 to perfect magic state production, a crucial technique for achieving a fully fault-tolerant universal gate set. In doing so, they set a record magic state infidelity (7x10-5), 10x better than any .
Our simulations show that our system could reach a magic state infidelity of 10^-10, or about one error per 10 billion operations, on a larger-scale computer with our current physical error rate. We anticipate reaching 10^-14, or about one error per 100 trillion operations, as we continue to advance our hardware. This means that our roadmap is now derisked.
Setting a record magic state infidelity was just the beginning. The paper also presents the first break-even two-qubit non-Clifford gate, demonstrating a logical error rate below the physical one. In doing so, the team set another record for two-qubit non-Clifford gate infidelity (2x10-4, almost 10x better than our physical error rate). Putting everything together, the team ran the first circuit that used a fully fault-tolerant universal gate set, a critical moment for our industry.
Flipping the switch
In the , co-authored with researchers at the University of California at Davis, we demonstrated an important technique for universal fault-tolerance called 鈥渃ode switching鈥.
Code switching describes switching between different error correcting codes. The team then used the technique to demonstrate the key ingredients for universal computation, this time using a code where we鈥檝e previously demonstrated full error correction and the other ingredients for universality.
In the process, the team set a new record for magic states in a distance-3 error correcting code, over 10x better than with error correction. Notably, this process only cost 28 qubits . This completes, for the first time, the ingredient list for a universal gate setin a system that also has real-time and repeatable QEC.
Fully equipped for fault-tolerance
Innovations like those described in these two papers can reduce estimates for qubit requirements by an order of magnitude, or more, bringing powerful quantum applications within reach far sooner.
With all of the required pieces now, finally, in place, we are 鈥榝ully鈥 equipped to become the first company to perform universal fully fault-tolerant computing鈥攋ust in time for the arrival of Helios, our next generation system launching this year, and what is very likely to remain as the most powerful quantum computer on the market until the launch of its successor, Sol, arriving in 2027.
If we are to create 鈥榥ext-gen鈥 AI that takes full advantage of the power of quantum computers, we need to start with quantum native transformers. Today we announce yet again that 夜色直播 continues to lead by demonstrating concrete progress 鈥 advancing from theoretical models to real quantum deployment.
The future of AI won't be built on yesterday鈥檚 tech. If we're serious about creating next-generation AI that unlocks the full promise of quantum computing, then we must build quantum-native models鈥攄esigned for quantum, from the ground up.
Around this time last year, we introduced Quixer, a state-of-the-art quantum-native transformer. Today, we鈥檙e thrilled to announce a major milestone: one year on, Quixer is now running natively on quantum hardware.
Why this matters: Quantum AI, born native
This marks a turning point for the industry: realizing quantum-native AI opens a world of possibilities.
Classical transformers revolutionized AI. They power everything from ChatGPT to real-time translation, computer vision, drug discovery, and algorithmic trading. Now, Quixer sets the stage for a similar leap 鈥 but for quantum-native computation. Because quantum computers differ fundamentally from classical computers, we expect a whole new host of valuable applications to emerge. 聽
Achieving that future requires models that are efficient, scalable, and actually run on today鈥檚 quantum hardware.
That鈥檚 what we鈥檝e built.
What makes Quixer different?
Until Quixer, quantum transformers were the result of a brute force 鈥渃opy-paste鈥 approach: taking the math from a classical model and putting it onto a quantum circuit. However, this approach does not account for the considerable differences between quantum and classical architectures, leading to substantial resource requirements.
Quixer is different: it鈥檚 not a translation 鈥 it's an innovation.
With Quixer, our team introduced an explicitly quantum transformer, built from the ground up using quantum algorithmic primitives. Because Quixer is tailored for quantum circuits, it's more resource efficient than most competing approaches.
As quantum computing advances toward fault tolerance, Quixer is built to scale with it.
What鈥檚 next for Quixer?
We鈥檝e already deployed Quixer on real-world data: genomic sequence analysis, a high-impact classification task in biotech. We're happy to report that its performance is already approaching that of classical models, even in this first implementation.
This is just the beginning.
Looking ahead, we鈥檒l explore using Quixer anywhere classical transformers have proven to be useful; such as language modeling, image classification, quantum chemistry, and beyond. More excitingly, we expect use cases to emerge that are quantum-specific, impossible on classical hardware.
This milestone isn鈥檛 just about one model. It鈥檚 a signal that the quantum AI era has begun, and that 夜色直播 is leading the charge with real results, not empty hype.
Stay tuned. The revolution is only getting started.
Our team is participating in (ISC 2025) from June 10-13 in Hamburg, Germany!
As quantum computing accelerates, so does the urgency to integrate its capabilities into today鈥檚 high-performance computing (HPC) and AI environments. At ISC 2025, meet the 夜色直播 team to learn how the highest performing quantum systems on the market, combined with advanced software and powerful collaborations, are helping organizations take the next step in their compute strategy.
夜色直播 is leading the industry across every major vector: performance, hybrid integration, scientific innovation, global collaboration and ease of access.
- Our industry-leading quantum computer holds the record for performance with a Quantum Volume of 2虏鲁 = 8,388,608 and the highest fidelity on a commercially available QPU available to our users every time they access our systems.
- Our systems have been validated by a #1 ranking against competitors in a recent benchmarking study by J眉lich Research Centre.
- We鈥檝e laid out a clear roadmap to reach universal, fully fault-tolerant quantum computing by the end of the decade and will launch our next-generation system, Helios, later this year.
- We are advancing real-world hybrid compute with partners such as RIKEN, NVIDIA, SoftBank, STFC Hartree Center and are pioneering applications such as our own GenQAI framework.
Exhibit Hall
From June 10鈥13, in Hamburg, Germany, visit us at Booth B40 in the Exhibition Hall or attend one of our technical talks to explore how our quantum technologies are pushing the boundaries of what鈥檚 possible across HPC.
Presentations & Demos
Throughout ISC, our team will present on the most important topics in HPC and quantum computing integration鈥攆rom near-term hybrid use cases to hardware innovations and future roadmaps.
Multicore World Networking Event
- 鈥Monday, June 9 | 7:00pm 鈥 9:00 PM at Hofbr盲u Wirtshaus Esplanade
鈥In partnership with Multicore World, join us for a 夜色直播-sponsored Happy Hour to explore the present and future of quantum computing with 夜色直播 CCO, Dr. Nash Palaniswamy, and network with our team.
H1 x CUDA-Q Demonstration
- 鈥All Week at Booth B40
鈥We鈥檙e showcasing a live demonstration of NVIDIA鈥檚 CUDA-Q platform running on 夜色直播鈥檚 industry-leading quantum hardware. This new integration paves the way for hybrid compute solutions in optimization, AI, and chemistry.
鈥Register for a demo
HPC Solutions Forum
- 鈥Wednesday, June 11 | 2:20 鈥 2:40 PM
鈥鈥淓nabling Scientific Discovery with Generative Quantum AI鈥 鈥 Presented by Maud Einhorn, Technical Account Executive at 夜色直播, discover how hybrid quantum-classical workflows are powering novel use cases in scientific discovery.
See You There!
Whether you're exploring hybrid solutions today or planning for large-scale quantum deployment tomorrow, ISC 2025 is the place to begin the conversation.
We look forward to seeing you in Hamburg!