


ĢƵ President and COO Tony Uttley announced three major accomplishments during his keynote address at the IEEE Quantum Week event in Colorado last week.
The three milestones, representing actionable acceleration for the quantum computing eco-system, are: (i) new arbitrary angle gate capabilities on the H-series hardware, (ii) another QV record for the System Model H1 hardware, and (iii) over 500,000 downloads of ĢƵ’s open-sourced , a world-leading quantum software development kit (SDK).
The announcements were made during Uttley’s keynote address titled, “A Measured Approach to Quantum Computing.”
These advancements are the latest examples of the company’s continued demonstration of its leadership in the quantum computing community.
“ĢƵ is accelerating quantum computing’s impact to the world,” Uttley said. “We are making significant progress with both our hardware and software, in addition to building a community of developers who are using our TKET SDK.”
This latest quantum volume measurement of 8192 is particularly noteworthy and is the second time this year ĢƵ has published a new QV record on their trapped-ion quantum computing platform, the System Model H1, Powered by Honeywell.

A key to achieving this latest record is the new capability of directly implementing arbitrary angle two-qubit gates. For many quantum circuits, this new way of doing a two-qubit gate allows for more efficient circuit construction and leads to higher fidelity results.
Dr. Brian Neyenhuis, Director of Commercial Operations at ĢƵ, said, “This new capability allows for several user advantages. In many cases, this includes shorter interactions with the qubits, which lowers the error rate. This allows our customers to run long computations with less noise.”
These arbitrary angle gates build on the overall design strength of the trapped-ion architecture of the H1, Neyenhuis said.
“With the quantum-charged coupled device (QCCD) architecture, interactions between qubits are very simple and can be limited to a small number of qubits which means we can precisely control the interaction and don’t have to worry about additional crosstalk,” he said.
This new gate design represents a third method for ĢƵ to improve the efficiency of the H1 generation, said Dr. Jenni Strabley, Senior Director of Offering Management at ĢƵ.
“ĢƵ’s goal is to accelerate quantum computing. We know we have to make the hardware better and we have to make the algorithms smarter, and we’re doing that,” she said. “Now we can also implement the algorithms more efficiently on our H1 with this new gate design.”
Currently, researchers can do single qubit gates – rotations on a single qubit – or a fully entangling two-qubit gate. It’s possible to build any quantum operation out of just those building blocks.
With arbitrary angle gates, instead of just having a two-qubit gate that's fully entangling, scientists can use a two-qubit gate that is partially entangling.
“There are many algorithms where you want to evolve the quantum state of the system one tiny step at a time. Previously, if you wanted a tiny bit of entanglement for some small time step, you had to entangle it all the way, rotate it a little bit, and then unentangle it almost all the way back,” Neyenhuis said. “Now we can just add this tiny little bit of entanglement natively and then go to the next step of the algorithm.”
There are other algorithms where this arbitrary angle two-qubit gate is the natural building block, according to Neyenhuis. One example is the quantum Fourier transform. Using arbitrary angle two-qubit gates cuts the number of two-qubit gates (and the overall error) in half, drastically improving the fidelity of the circuit. Researchers can use this new gate design to run harder problems that resulted in catastrophic errors in previous experiments.
“By going to an arbitrary angle gate, in addition to cutting the number of two-qubit gates in half, the error we get per gate is lower because it scales with the amplitude of that gate,” Neyenhuis said.
This is a powerful new capability, particularly for noisy intermediate-scale quantum algorithms. Another demonstration from the ĢƵ team was to use arbitrary angle two-qubit gates to study non-equilibrium phase transitions, the technical details of which are .
“For the algorithms that we are going to want to run in this NISQ regime that we're in right now, this is a more efficient way to run your algorithm,” Neyenhuis said. “There are lots of different circuits you would want to run where this arbitrary angle gate gives you a fairly significant increase in the fidelity of your overall circuit.This capability also allows for a speed up in the circuit execution by removing unneeded gates, which ultimately reduces the time of executing a job on our machines.”
Researchers working with machine learning algorithms, variational algorithms, and time evolution algorithms would see the most benefit from these new gates. This advancement is particularly relevant for simulating the dynamics of other quantum systems.
“This just gave us a big win in fidelity because we can run the sort of interaction you're after natively, rather than constructing it out of some other Lego blocks,” Neyenhuis said.
Quantum volume tests require running arbitrary circuits. At each slice of the quantum volume circuit, the qubits are randomly paired up and a complex two-qubit operation is performed. This SU(4) gate can be constructed more efficiently using the arbitrary angle two-qubit gate, lowering the error at each step of the algorithm.

The H1-1’s quantum volume of 8192 is due in part to the implementation of arbitrary angle gates and the continued reduction in error rates.ĢƵ’s last quantum volume increase was in April when the System Model H1-2 doubled its performance to become the first commercial quantum computer to pass Quantum Volume 4096.
This new increase is the seventh time in two years that ĢƵ’s H-Series hardware has set an industry record for measured quantum volume as it continues to achieve its goal of 10X annual improvement.
Quantum volume, a benchmark introduced by IBM in 2019, is a way to measure the performance of a quantum computer using randomized circuits, and is a frequently used metric across the industry.
ĢƵ has also achieved another milestone: over 500,000 downloads of .
TKET is an advanced software development kit for writing and running programs on gate-based quantum computers. TKET enables developers to optimize their quantum algorithms, reducing the computational resources required, which is important in the NISQ era.
TKET is open source and accessible through the PyTKET Python package. The SDK also integrates with major quantum software platforms including Qiskit, Cirq and Q#. has been available as an open source language for almost a year.
This universal availability and TKET’s portability across many quantum processors are critical for building a community of developers who can write quantum algorithms. The number of downloads includes many companies and academic institutions which account for multiple users.
ĢƵ CEO Ilyas Khan said, “Whilst we do not have the exact number of users of TKET, it is clear that we are growing towards a million people around the world who have taken advantage of a critical tool that integrates across multiple platforms and makes those platforms perform better. We continue to be thrilled by the way that TKET helps democratize as well as accelerate innovation in quantum computing.”
Arbitrary angle two-qubit gates and other recent ĢƵ advances are all built into TKET.
“TKET is an evolving platform and continues to take advantage of these new hardware capabilities,” said Dr. Ross Duncan, ĢƵ’s Head of Quantum Software. “We’re excited to put these new capabilities into the hands of the rapidly increasing number of TKET users around the world.”
The average single-qubit gate fidelity for this milestone was 99.9959(5)%, the average two-qubit gate fidelity was 99.71(3)% with fully connected qubits, and state preparation and measurement fidelity was 99.72(1)%. The ĢƵ team ran 220 circuits with 90 shots each, using standard QV optimization techniques to yield an average of 175.2 arbitrary angle two-qubit gates per circuit.
The System Model H1-1 successfully passed the quantum volume 8192 benchmark, outputting heavy outcomes 69.33% of the time, with a 95% confidence interval lower bound of 68.38% which is above the 2/3 threshold.
ĢƵ, the world’s largest integrated quantum company, pioneers powerful quantum computers and advanced software solutions. ĢƵ’s technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With over 500 employees, including 370+ scientists and engineers, ĢƵ leads the quantum computing revolution across continents.
Quantum computing is all about putting the exotic properties of physics to work. Qubits can exist in two states at once, like the famous cat that is both alive and dead. Qubits can also be entangled, where the state of one will instantaneously affect the state of another - even when they have no way to “talk” to each other. Qubits can even be teleported, moving a quantum state from one place to another without physically moving it through space.
These features give quantum computing its power. But the ‘spooky’ nature of quantum computing doesn’t stop there: our quantum computers are potent enough to make exotic states of matter out of our qubits, and to perform calculations that would warp the mind of more traditional thinkers.
In a recent paper published in Nature, researchers at ĢƵ teamed up with Caltech, the University of Chicago, and Harvard to create a rare ‘topologically ordered’ state of matter from our qubits.
When the qubits become ‘topologically ordered’, they become more than individual particles, now ‘related’ to each other in a specific way. This is like how hydrogen and oxygen act as individual gas particles alone, but you can put them together in a certain way so that they become water, a liquid, and an entirely different creature.
When the qubits become topologically ordered, the quantum information that they carried individually gets spread out over the whole system, which acts as a sort of protection from noise. This is like how a net makes a stronger barrier than a bunch of un-knotted ropes.
Once the researchers had topologically ordered qubits, they used the exotic particles that resulted (called non-Abelian anyons) to compute, performing error-protected gates and measurements.
To perform gates, the researchers 'braided' the anyons, which is like changing the shape of the “net”. This is something like the children’s game ‘cats cradle’. Through a sequence of changes to the “net”, the quantum computer can perform full calculations, one day helping scientists to understand the secrets hidden in the world around us.
Why go to such trouble? Well, for the love of discovery of course - but the team had an additional, specific motivation. One of the biggest challenges in building practical quantum computers is protecting them from errors while still being able to perform every operation needed for computation (this is referred to as universality).
This work takes a fresh approach to this challenge. Unlike traditional quantum error correction, the special properties of topological matter enable a universal set of fault tolerant gates without relying on expensive magic state distillation.
Quantum error correction is essential for large-scale quantum computing. While it protects fragile quantum information from noise by turning delicate physical qubits into robust logical qubits, it also introduces a significant constraint: not every quantum gate can be performed directly on logical qubits.
For decades, the standard solution has been to supplement error-corrected operations with magic states. These specially prepared quantum resources enable universal computation but can come at a steep cost - in many estimates of future fault-tolerant quantum computers, magic state preparation dominates both the physical qubit count and the runtime of useful algorithms.
Reducing this overhead has therefore become an important goal in quantum computing. This new approach may significantly reduce the cost by enabling the ‘topological preparation’ of magic states, eliding expensive protocols like distillation. If universal computation can be performed without large-scale magic state distillation, quantum computers could require significantly fewer physical qubits and spend much less time generating computational resources before running useful algorithms.
While there is still considerable work ahead to understand the practical implementation and scalability of these ideas, this result expands the landscape of what's possible in quantum fault tolerance.
Of course, this impressive demonstration describes just one approach we are taking to fault tolerance at scale. We will continue to push forward with topological computing alongside more traditional approaches to quantum error correction, as well as exploring everything we can imagine in between. We are looking at a number of ways to reduce the resource cost of magic states in particular, and are making strides in multiple dimensions. With machines that are both flexible and accurate enough to do it all, who can resist?
Fault-tolerant quantum computing is the threshold the industry must cross before quantum computers can solve the hardest, highest-value problems with confidence. To be commercially useful at scale, the question is not simply who can build more qubits. It is who can build reliable, efficient, scalable systems that reduce technical risk and accelerate the path to commercial usefulness.
ĢƵ is progressing on that path.
Last year, in partnership with Microsoft, we published a breakthrough in logical computing, demonstrating logical qubits that outperformed their physical counterparts by a factor of 800. We are proud to announce that this work is now being published in Nature, one of the most highly regarded scientific journals in the world.
This work highlights our leading fidelities, as shown in Table 1:

Since then, we’ve accelerated our efforts to reach large-scale fault tolerance and advanced what we believe to be the core building blocks of fault-tolerant quantum computing, from logical-qubit teleportation and multiple error-correction breakthroughs to one of the first meaningful computations using logical qubits. Importantly, these results were achieved on commercial ĢƵ hardware, demonstrating not just scientific progress, but a practical and efficient path toward scalable, customer-ready fault tolerance.
Since the work with Microsoft, we achieved a milestone years ahead of schedule, demonstrating high-fidelity teleportation of a logical qubit, which was published in one of the world’s most prestigious journals. Later, we beat our own record in this crucial fault tolerance milestone, thanks to continued improvements to our System Model H2’s fidelity.
Then, a series of results demonstrating more error-correcting milestones (and codes):
Recently, we topped ourselves yet again by performing one of the first meaningful computations with logical qubits – exploring key questions in materials and magnetism, using . This result also includes a leading “encoding rate” squeezing 48 logical qubits out of just 98 physical qubits, emphasizing how our architecture helps to support large scale fault tolerance without enormous resource costs.
It is worth noting that all these results were achieved on our commercial hardware, not on one-off laboratory test-stands – reflecting the performance that we are able to deliver to our customers.
We also did crucial theoretical work, exploring that can reduce resource requirements, time to solution, and shorten the timeline to large scale fault tolerance.
We believe the commercial implication is clear: ĢƵ is reducing the uncertainty around the path to fault-tolerant quantum computing. Our architecture, hardware fidelity, full-stack control, and error-correction progress are converging into a practical roadmap for systems that can support valuable scientific and commercial workloads.
For those evaluating when quantum computing will become strategically relevant, we believe the signal is also increasingly clear: the fault-tolerant era is no longer a distant concept. It is becoming an engineering reality, and ĢƵ is leading the way.
Progress in quantum computing is measured by hardware advances plus the algorithms and quantum error-correction codes that turn quantum systems into useful computational tools.
Thanks to recent hardware advances, researchers are increasingly sharpening their tools to probe the performance of quantum algorithms and understand how they behave in realistic conditions – where stability, system architecture and algorithm design all shape performance.
A new Denmark-based collaboration between the University of Southern Denmark (SDU), ĢƵ, and the Danish e-Infrastructure Consortium (DeiC) will utilize ĢƵ Helios. Researchers at the SDU’s Centre for Quantum Mathematics, led by Jørgen Ellegaard Andersen, will use Helios to pursue research into topological quantum computing.
Their work could help explain how and why successful quantum algorithms perform as they do, informing the development of high-performance algorithms suited to emerging quantum systems. They’re exploring the scientific foundations that support future quantum applications across areas including pharmaceuticals, finance, and defense.
“We are thrilled to gain access to ĢƵ’s high-fidelity Helios system. This collaboration gives us a unique opportunity to test the limits of our algorithms and evaluate system performance, while advancing fundamental research and laying the foundation for future applications.”
— Professor Jørgen Ellegaard Andersen, Director of the Centre for Quantum Mathematics at University of Southern Denmark
Topological quantum computing is an area of research that connects quantum computation with deep mathematical structures. It includes the study of error correcting codes known as surface codes that encode quantum information in the global properties of systems of logical qubits.
The research team will explore how these codes behave, and how they may support the development of fault-tolerant quantum algorithms in practical implementations under realistic conditions.
This distinction between theory and practical implementation matters. In theory, topological approaches offer a rich framework for designing algorithms and error-correcting codes. In practice, researchers need to understand how those ideas perform when implemented on real systems, where questions of noise, stability, overhead, and scaling become central. The collaboration will allow the SDU team to investigate these questions directly.
Beyond individual algorithms and codes, the research will also develop tools for benchmarking quantum processors. The goal is to develop new ways to characterize fidelity and stability in regimes that can be difficult to access.
The team will also explore hybrid quantum–classical approaches, including machine-learning techniques assisted by quantum hardware, to study the mathematical structures at the heart of topological quantum computing. This work reflects a broader field of research in which quantum and classical methods are used together, each contributing to parts of a computational problem.
The collaboration reflects the growing role of national quantum infrastructure in supporting research and talent development. Denmark has a long tradition of scientific innovation, and this collaboration is intended to support the country’s continued development in quantum technology.
The initiative is supported by DeiC, which played a central role in securing funding and enabling access to ĢƵ’s systems. DeiC has been assigned a particular role in developing and coordinating quantum infrastructure initiatives for the benefit of universities and industry, operating without its own commercial, sectoral, or geographical interests. This includes securing dedicated access to quantum computers, producing advisory services and supporting the development of new talent in the Danish quantum sector.
“DeiC’s special effort to secure funding and access for this research initiative is rooted in our organization’s role in relation to the Danish Government’s strategy for quantum technology.”
— Henrik Navntoft Sønderskov, Head of Quantum at Danish e-Infrastructure Consortium
This collaboration promises to accelerate the development of practical algorithms. It is grounded in fundamental science – but its focus is practical: discovering and testing mathematical approaches to topological quantum computing that can be implemented, evaluated, and improved on real quantum hardware.
That work requires both theoretical insight and access to a system such as Helios capable of supporting meaningful scientific work.