

Over the course of 2021, Quantinuum’s customers and collaborators were the beneficiaries of a deliberate, strategic approach to quantum computing design. Namely, that it is possible to release a generation of quantum computers that can be quickly and systematically upgraded in parallel with commercial usage, allowing customers immediate access to the latest upgrades.
With the release of the System Model H1, Powered by Honeywell, in fall 2020, Quantinuum began a real-time demonstration of its design approach. The first System Model H1, referred to as the H1-1, launched in October 2020 with a measured quantum volume of 128. Quantum volume is a metric introduced by IBM to measure the overall capability and performance of a quantum computing system regardless of technology. (Calculating quantum volume requires running a series of complex random circuits and performing a statistical test on the results.)
During 2021, Quantinuum, under its trapped-ion hardware group, previously known as Honeywell Quantum Solutions, made multiple upgrades to the H1-1 achieving measured quantum volume records of 512 in March 2021 and the 1,024 in July 2021. During that same period, Quantinuum was quietly releasing its second H1 generation quantum computer to customers and collaborators, called the H1-2. The System Model H1-2 uses the same ion-trap architecture, control system design, integrated optics, and photonics as the H1-1.
“Our H1 generation of quantum computers are nearly identical copies, with the ongoing exception that at any given time one computer might have received upgrades prior to the other,” said Dr. Russ Stutz, Head of Commercial Products for the hardware team. “Our goal is to provide users with the highest performing hardware as they work on solving real world problems."
Upgrades to both H1 quantum computers over the course of 2021 included improved gate and measurement fidelities, reduced memory errors, faster circuit compilation, inclusion of real-time classical computing resources and quantum operations using 12 qubits, versus the 10 qubits available at initial release.
What has been remarkable about the approach, is the ability to deliver near-continuous capability upgrades while being consistent on performance.
“Our customers frequently comment about their ability to reliably get expected results, including when running deep circuits and using sophisticated features like mid-circuit measurement, qubit reuse and conditional logic,” said Dr. Brian Neyenhuis, Head of Commercial Operations for the hardware team.
Just this past week, H1-2 measured a Quantum Volume of 2,048 (211), setting a new bar on the highest quantum volume ever measured on a quantum computer. The performance of the H1 generation of quantum computers continues to achieve the 10X per year increase that was announced in March 2020.

The average single-qubit gate fidelity for this milestone was 99.996(2)%, the average two-qubit gate fidelity was 99.77(9)%, and state preparation and measurement (SPAM) fidelity was 99.61(2)%. We ran 2,000 randomly generated quantum volume circuits with 5 shots each, using standard optimization techniques to yield an average of 122 two-qubit gates per circuit.
The System Model H1-2 successfully passed the quantum volume 2,048 benchmark, returning heavy outputs 69.76% of the time, which is above the 2/3 threshold with 99.87% confidence.

The plot above shows the heavy outputs for Quantinuum’s tests of quantum volume and the dates when each test passed. All tests are above the 2/3 threshold to pass the respective quantum volume benchmark. Circles indicate heavy output averages and the violin plots show the histogram distributions. Data colored in blue show system performance results and red points correspond to modeled, noise-included simulation data. White markers are the lower two-sigma error bounds.

The plot above shows the individual heavy outputs for each quantum volume 2,048 circuit. The blue line is an average of heavy outputs and the orange line is the lower two-sigma error bar which crosses the 2/3 threshold after 818 circuits, which corresponds to passing.
This is the latest in a string of accomplishments for Quantinuum, which recently announced the completion of its combination between Honeywell Quantum Solutions and Cambridge Quantum Computing to form the largest stand-alone integrated quantum computing company in the world. This news also falls on the heels of the release of Quantinuum’s flagship product, Quantum Origin, the world’s first quantum-enhanced cryptographic key generation platform.
“We look forward to continued momentum in 2022 with expected advances in multiple application areas as well as further advances in the H-Series quantum computers”, said Tony Uttley, President and Chief Operating Officer of Quantinuum.
* The Honeywell trademark is used under license from Honeywell International Inc. Honeywell makes no representations or warranties with respect to this product or service.
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.
Quantinuum is focusing on redefining what’s possible in hybrid quantum–classical computing by integrating Quantinuum’s best-in-class systems with high-performance NVIDIA accelerated computing to create powerful new architectures that can solve the world’s most pressing challenges.
The launch of Helios, Powered by Honeywell, the world’s most accurate quantum computer, marks a major milestone in quantum computing. Helios is now available to all customers through the cloud or on-premise deployment, launched with a go-to-market offering that seamlessly pairs Helios with the NVIDIA Grace Blackwell platform, targeting specific end markets such as drug discovery, finance, materials science, and advanced AI research.
We are also working with NVIDIA to adopt NVIDIA NVQLink, an open system architecture, as a standard for advancing hybrid quantum-classical supercomputing. Using this technology with Quantinuum Guppy and the NVIDIA CUDA-Q platform, Quantinuum has implemented NVIDIA accelerated computing across Helios and future systems to perform real-time decoding for quantum error correction.
In an industry-first demonstration, an NVIDIA GPU-based decoder integrated in the Helios control engine improved the logical fidelity of quantum operations by more than 3% — a notable gain given Helios’ already exceptionally low error rate. These results demonstrate how integration with NVIDIA accelerated computing through NVQLink can directly enhance the accuracy and scalability of quantum computation.

This unique collaboration spans the full Quantinuum technology stack. Quantinuum’s next-generation software development environment allows users to interleave quantum and GPU-accelerated classical computations in a single workflow. Developers can build hybrid applications using tools such as NVIDIA CUDA-Q, NVIDIA CUDA-QX, and Quantinuum’s Guppy, to make advanced quantum programming accessible to a broad community of innovators.
The collaboration also reaches into applied research through the NVIDIA Accelerated Quantum Computing Research Center (NVAQC), where an NVIDIA GB200 NVL72 supercomputer can be paired with Quantinuum’s Helios to further drive hybrid quantum-GPU research, including the development of breakthrough quantum-enhanced AI applications.
A recent achievement illustrates this potential: The ADAPT-GQE framework, a transformer-based Generative Quantum AI (GenQAI) approach, uses a Generative AI model to efficiently synthesize circuits to prepare the ground state of a chemical system on a quantum computer. Developed by Quantinuum, NVIDIA, and a pharmaceutical industry leader—and leveraging NVIDIA CUDA-Q with GPU-accelerated methods—ADAPT-GQE achieved a 234x speed-up in generating training data for complex molecules. The team used the framework to explore imipramine, a molecule crucial to pharmaceutical development. The transformer was trained on imipramine conformers to synthesize ground state circuits at orders of magnitude faster than ADAPT-VQE, and the circuit produced by the transformer was run on Helios to prepare the ground state using InQuanto, Quantinuum's computational chemistry platform.
From collaborating on hardware and software integrations to GenQAI applications, the collaboration between Quantinuum and NVIDIA is building the bridge between classical and quantum computing and creating a future where AI becomes more expansive through quantum computing, and quantum computing becomes more powerful through AI.
By Dr. Noah Berthusen
The earliest works on quantum error correction showed that by combining many noisy physical qubits into a complex entangled state called a "logical qubit," this state could survive for arbitrarily long times. QEC researchers devote much effort to hunt for codes that function well as "quantum memories," as they are called. Many promising code families have been found, but this is only half of the story.
Being able to keep a qubit around for a long time is one thing, but to realize the theoretical advantages of quantum computing we need to run quantum circuits. And to make sure noise doesn't ruin our computation, these circuits need to be run on the logical qubits of our code. This is often much more challenging than performing gates on the physical qubits of our device, as these "logical gates" often require many physical operations in their implementation. What's more, it often is not immediately obvious which logical gates a code has, and so converting a physical circuit into a logical circuit can be rather difficult.
Some codes, like the famous surface code, are good quantum memories and also have easy logical gates. The drawback is that the ratio of physical qubits to logical qubits (the "encoding rate") is low, and so many physical qubits are required to implement large logical algorithms. High-rate codes that are good quantum memories have also been found, but computing on them is much more difficult. The holy grail of QEC, so to speak, would be a high-rate code that is a good quantum memory and also has easy logical gates. Here, we make progress on that front by developing a new code with those properties.
A recent work from Quantinuum QEC researchers introduced genon codes. The underlying construction method for these codes, called the "symplectic double cover," also provided a way to obtain logical gates that are well suited for Quantinuum's QCCD architecture. Namely, these "SWAP-transversal" gates are performed by applying single qubit operations and relabeling the physical qubits of the device. Thanks to the all-to-all connectivity facilitated through qubit movement on the QCCD architecture, this relabeling can be done in software essentially for free. Combined with extremely high fidelity (~1.2 x10-5) single-qubit operations, the resulting logical gates are similarly high fidelity.
Given the promise of these codes, we take them a step further in our new paper. We combine the symplectic double codes with the [[4,2,2]] Iceberg code using a procedure called "code concatenation". A concatenated code is a bit like nesting dolls, with an outer code containing codes within it---with these too potentially containing codes. More technically, in a concatenated code the logical qubits of one code act as the physical qubits of another code.
The new codes, which we call "concatenated symplectic double codes", were designed in such a way that they have many of these easily-implementable SWAP-transversal gates. Central to its construction, we show how the concatenation method allows us to "upgrade" logical gates in terms of their ease of implementation; this procedure may provide insights for constructing other codes with convenient logical gates. Notably, the SWAP-transversal gate set on this code is so powerful that only two additional operations (logical T and S) are necessary for universal computation. Furthermore, these codes have many logical qubits, and we also present numerical evidence to suggest that they are good quantum memories.
Concatenated symplectic double codes have one of the easiest logical computation schemes, and we didn’t have to sacrifice rate to achieve it. Looking forward in our roadmap, we are targeting hundreds of logical qubits at ~ 1x 10-8 logical error rate by 2029. These codes put us in a prime position to leverage the best characteristics of our hardware and create a device that can achieve real commercial advantage.
Every year, the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC) brings together the global supercomputing community to explore the technologies driving the future of computing.
Join Quantinuum at this year’s conference, taking place November 16th – 21st in St. Louis, Missouri, where we will showcase how our quantum hardware, software, and partnerships are helping define the next era of high-performance and quantum computing.
The Quantinuum team will be on-site at booth #4432 to showcase how we’re building the bridge between HPC and quantum.
On Tuesday and Wednesday, our quantum computing experts will host daily tutorials at our booth on Helios, our next-generation hardware platform, Nexus, our all-in-one quantum computing platform, and Hybrid Workflows, featuring the integration of NVIDIA CUDA-Q with Quantinuum Systems.
Join our team as they share insights on the opportunities and challenges of quantum integration within the HPC ecosystem:
Panel Session: The Quantum Era of HPC: Roadmaps, Challenges and Opportunities in Navigating the Integration Frontier
November 19th | 10:30 – 12:00pm CST
During this panel session, Kentaro Yamamoto from Quantinuum, will join experts from Lawrence Berkeley National Laboratory, IBM, QuEra, RIKEN, and Pawsey Supercomputing Research Centre to explore how quantum and classical systems are being brought together to accelerate scientific discovery and industrial innovation.
BoF Session: Bridging the Gap: Making Quantum-Classical Hybridization Work in HPC
November 19th | 5:15 – 6:45pm CST
Quantum-classical hybrid computing is moving from theory to reality, yet no clear roadmap exists for how best to integrate quantum processing units (QPUs) into established HPC environments. In this Birds of a Feather discussion, co-led by Quantinuum’s Grahame Vittorini and representatives from BCS, DOE, EPCC, Inria, ORNL NVIDIA, and RIKEN we hope to bring together a global community of HPC practitioners, system architects, quantum computing specialists and workflow researchers, including participants in the Workflow Community Initiative, to assess the state of hybrid integration and identify practical steps toward scalable, impactful deployment.