Quantinuum extends its significant lead in quantum computing, achieving historic milestones for hardware fidelity and Quantum Volume
Quantinuum has raised the bar for the global ecosystem by achieving the historic and much-vaunted “three 9's” 2-qubit gate fidelity in its commercial quantum computer and announcing that its Quantum Volume has surpassed one million – exponentially higher than its nearest competitors.
By Ilyas Khan, Founder and Chief Product Officer, Jenni Strabley, Sr Director of Offering Management
All quantum error correction schemes depend for their success on physical hardware achieving high enough fidelity. If there are too many errors in the physical qubit operations, the error correcting code has the effect of amplifying rather than diminishing overall error rates. For decades now, it has been hoped that one day a quantum computer would achieve “three 9's” – an iconic, inherent 99.9% 2-qubit physical gate fidelity – at which point many of the error-correcting codes required for universal fault tolerant quantum computing would successfully be able to squeeze errors out of the system.
That day has now arrived. Building on several previous laboratory demonstrations 1 2 3, Quantinuum has become the first company ever to achieve “three 9's” in a commercially-available quantum computer, with the first demonstration of 99.914(3)% 2-qubit gate fidelity, showing repeatable performance across all qubit pairs on our H1-1 system that is constantly available to customers. This production-environment announcement is a marked difference to one-offs recorded in carefully contrived laboratory conditions. This demonstrates what will fast become the expected standard for the entire quantum computing sector.
Quantinuum is also announcing another milestone, a seven-figure Quantum Volume (QV) of 1,048,576 – or in terms preferred by the experts, 220 – reinforcing our commitment to building, by a significant margin, the highest-performing quantum computers in the world.
These announcements follow a historic month that started when we proved our ability to scale our systems to the sizes needed to solve some of the world’s most pressing problems – and in a way that offers the best path to universal quantum computing.
On March 5th, 2024, Quantinuum researchers disclosed details of our experiments that provide a solution to a totemic problem faced by all quantum computing architectures, known as the wiring problem. Supported by a video showing qubits being shuffled through a 2-dimensional grid ion-trap, our team presented concrete proof of the scalability of the quantum charge-coupled device (QCCD) architecture used in our H-Series quantum computers.
Stop-motion ion transport video showing a chosen sorting operation implemented on an 8-site 2D grid trap with the swap-or-stay primitive. The sort is implemented by discrete choices of swaps or stays between neighboring sites. The numbers shown (indicated by dashed circles) at the beginning and end of the video show the initial and final location of the ions after the sort, e.g. the ion that starts at the top left site ends at the bottom right site. The stop-motion video was collected by segmenting the primitive operation and pausing mid-operation such that Yb fluorescence could be detected with a CMOS camera exposure.
On April 3rd, 2024 in partnership with Microsoft, our teams announced a breakthrough in quantum error correction that delivered as its crowning achievement the most reliable logical qubits on record.
We revealed detailed demonstrations in an arXiv pre-print paper of the reliability achieved via 4 logical qubits encoded into just 30 physical qubits on our System Model H2 quantum computer. Our joint teams were able to demonstrate logical circuit error rates far below physical circuit error rates, a capability that our full-stack quantum computer is currently the only one in the world with the fidelity required to achieve.
Explaining the importance of 2-qubit gate fidelity
Reaching this level of physical fidelity is not optional for commercial scale computers – it is essential for error correction to work, and that in turn is a necessary foundation for any useful quantum computer. Our record two-qubit gate fidelity of 99.914(3)% marks a symbolic inflection point for the industry: at ”three 9's” fidelity, we are nearing or surpassing the break-even point (where logical qubits outperform physical qubits) for many quantum error correction protocols, and this will generate great interest among research and industrial teams exploring fault-tolerant methods for tackling real-world problems.
Without hardware fidelity this good, error-corrected calculations are noisier than un-corrected computations. This is why we call it a “threshold” – when gate errors are “above threshold”, quantum computers will remain noisy no matter what you do. Below threshold, you can use quantum error correction to push error rates way, way down, so that quantum computers eventually become as reliable as classical computers.
Four years ago, Quantinuum claimed that it would improve the performance of its H-Series quantum computers by 10x each year for five years, when measured by the industry’s most widely recognized benchmark, QV (an industry standard not to be confused with less comprehensive metrics such as Algorithmic Qubits).
Today’s achievement of a 220 QV – which as with all our demonstrations was achieved on our commercially-available machine – shows that our team is living up to this audacious commitment. We are completely confident we can continue to overcome the technical problems that stand in the way of even better fidelity and QV performance. Our QV data is available on GitHub, as are our hardware specifications
The combination of high QV and gate fidelities puts the Quantinuum system in a class by-itself – it is far and away the best of any commercially-available quantum computer.
QCCD: the path to fault tolerance
Additionally, and notably, these benchmarks were achieved “inherently”, without error mitigation, thanks to the H Series’ all-to-all connectivity and QCCD architecture. Full connectivity results in less errors when running large, complicated circuits. While other modalities depend on error mitigation techniques, such techniques are not scalable and present only a modest near-term value.
Lower physical error and high connectivity means our quantum computers have a provably lower overhead for error-corrected computation.
Looking more deeply, experts look for high fidelities that are valid in all operating zones and between any pair of qubits. In contrast to our competitors, this is precisely what our H Series delivers. We do not suffer from a broad distribution of gate fidelities between different pairs of qubits, meaning that some pairs of qubits have significantly lower fidelities. Quantinuum is the only quantum computing company with all qubit pairs boasting above 99.9% fidelity.
Alongside these benefits and demonstrations of scalability, fidelity, connectivity, and reliability, it is worth noting how these features impact what arguably matters the most to users – time to solution. In the QCCD architecture, speed of operations is decoupled from speed to reach a computational solution thanks to a combination of:
- a better signal to noise ratio than other modalities
- drastically reducing or eliminating the number of swap gates required (because we can move our ions through space), and
- reducing the number of trials required for an accurate result.
The net effect is that for increasingly complex circuits it takes a high-fidelity QCCD-type quantum computer less time to achieve accurate results than other 2D connected or lower-fidelity architectures.
“Getting to three 9’s in the QCCD architecture means that ~1000 entangling operations can be done before an error occurs. Our quantum computers are right at the edge of being able to do computations at the physical level that are beyond the reach of classical computers, which would occur somewhere between 3 nines and 4 nines. Some tasks become hard for classical computers before this regime (e.g. Google’s random circuit sampling problem) but this new regime allows for much less contrived problems to be solved. At that point, these machines become real tools for new discoveries – albeit they will still be limited in what they can probe, likely to be physics simulations or closely related problems,” said Dave Hayes, a Senior R&D manager at Quantinuum.
“Additionally, these fidelities put us, some would say comfortably, within the regime needed to build fault-tolerant machines. These fidelities allow us to start adding more qubits without needing to improve performance further, and to take advantage of quantum error correction to improve the computational power necessary for tackling truly large problems. This scaling problem gets easier with even better fidelities (which is why we’re not satisfied with 3 nines) but it is possible in principle.”
Quantinuum’s new records in fidelity and quantum volume on our commercial H1 device are expected to be achieved on the H2, once upgrades are implemented, underscoring the value that we offer to users for whom stability, reliability and robust performance are pre-requisites. The quantum computing landscape is complex and changing, but we remain at the head of the pack in all key metrics. The relationship with our world-class applications teams means that co-designed devices for solving some of the world’s most intractable problems are a big step closer to reality.
Quantinuum is the world’s leading quantum computing company, and our world-class scientists and engineers are continually driving our technology forward while expanding the possibilities for our users. Their work on applications includes cybersecurity, quantum chemistry, quantum Monte Carlo integration, quantum topological data analysis, condensed matter physics, high energy physics, quantum machine learning, and natural language processing – and we are privileged to support them to bring new solutions to bear on some of the greatest challenges we face.
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.
In our increasingly connected, data-driven world, cybersecurity threats are more frequent and sophisticated than ever. To safeguard modern life, government and business leaders are turning to quantum randomness.
What is quantum randomness, and why should you care?
The term to know: quantum random number generators (QRNGs).
QRNGs exploit quantum mechanics to generate truly random numbers, providing the highest level of cryptographic security. This supports, among many things:
- Protection of personal data
- Secure financial transactions
- Safeguarding of sensitive communications
- Prevention of unauthorized access to medical records
Quantum technologies, including QRNGs, could protect up to $1 trillion in digital assets annually, according to a recent report by the World Economic Forum and Accenture.
Which industries will see the most value from quantum randomness?
The World Economic Forum report identifies five industry groups where QRNGs offer high business value and clear commercialization potential within the next few years. Those include:
- Financial services
- Information and communication technology
- Chemicals and advanced materials
- Energy and utilities
- Pharmaceuticals and healthcare
In line with these trends, recent research by The Quantum Insider projects the quantum security market will grow from approximately $0.7 billion today to $10 billion by 2030.
When will quantum randomness reach commercialization?
Quantum randomness is already being deployed commercially:
- Early adopters use our Quantum Origin in data centers and smart devices.
- Amid rising cybersecurity threats, demand is growing in regulated industries and critical infrastructure.
Recognizing the value of QRNGs, the financial services sector is accelerating its path to commercialization.
- Last year, HSBC conducted a pilot combining Quantum Origin and post-quantum cryptography to future-proof gold tokens against “store now, decrypt-later” (SNDL) threats.
- And, just last week, JPMorganChase made headlines by using our quantum computer for the first successful demonstration of certified randomness.
On the basis of the latter achievement, we aim to broaden our cybersecurity portfolio with the addition of a certified randomness product in 2025.
How is quantum randomness being regulated?
The National Institute of Standards and Technology (NIST) defines the cryptographic regulations used in the U.S. and other countries.
- NIST’s SP 800-90B framework assesses the quality of random number generators.
- The framework is part of the FIPS 140 standard, which governs cryptographic systems operations.
- Organizations must comply with FIPS 140 for their cryptographic products to be used in regulated environments.
This week, we announced Quantum Origin received NIST SP 800-90B Entropy Source validation, marking the first software QRNG approved for use in regulated industries.
What does NIST validation mean for our customers?
This means Quantum Origin is now available for high-security cryptographic systems and integrates seamlessly with NIST-approved solutions without requiring recertification.
- Unlike hardware QRNGs, Quantum Origin requires no network connectivity, making it ideal for air-gapped systems.
- For federal agencies, it complements our "U.S. Made" designation, easing deployment in critical infrastructure.
- It adds further value for customers building hardware security modules, firewalls, PKIs, and IoT devices.
The NIST validation, combined with our peer-reviewed papers, further establishes Quantum Origin as the leading QRNG on the market.
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It is paramount for governments, commercial enterprises, and critical infrastructure to stay ahead of evolving cybersecurity threats to maintain societal and economic security.
Quantinuum delivers the highest quality quantum randomness, enabling our customers to confront the most advanced cybersecurity challenges present today.
The most common question in the public discourse around quantum computers has been, “When will they be useful?” We have an answer.
Very recently in Nature we announced a successful demonstration of a quantum computer generating certifiable randomness, a critical underpinning of our modern digital infrastructure. We explained how we will be taking a product to market this year, based on that advance – one that could only be achieved because we have the world’s most powerful quantum computer.
Today, we have made another huge leap in a different domain, providing fresh evidence that our quantum computers are the best in the world. In this case, we have shown that our quantum computers can be a useful tool for advancing scientific discovery.
Understanding magnetism
Our latest paper shows how our quantum computer rivals the best classical approaches in expanding our understanding of magnetism. This provides an entry point that could lead directly to innovations in fields from biochemistry, to defense, to new materials. These are tangible and meaningful advances that will deliver real world impact.
To achieve this, we partnered with researchers from Caltech, Fermioniq, EPFL, and the Technical University of Munich. The team used Quantinuum’s System Model H2 to simulate quantum magnetism at a scale and level of accuracy that pushes the boundaries of what we know to be possible.
As the authors of the paper state:
“We believe the quantum data provided by System Model H2 should be regarded as complementary to classical numerical methods, and is arguably the most convincing standard to which they should be compared.”
Our computer simulated the quantum Ising model, a model for quantum magnetism that describes a set of magnets (physicists call them ‘spins’) on a lattice that can point up or down, and prefer to point the same way as their neighbors. The model is inherently “quantum” because the spins can move between up and down configurations by a process known as “quantum tunneling”.
Gaining material insights
Researchers have struggled to simulate the dynamics of the Ising model at larger scales due to the enormous computational cost of doing so. Nobel laureate physicist Richard Feynman, who is widely considered to be the progenitor of quantum computing, once said, “it is impossible to represent the results of quantum mechanics with a classical universal device.” When attempting to simulate quantum systems at comparable scales on classical computers, the computational demands can quickly become overwhelming. It is the inherent ‘quantumness’ of these problems that makes them so hard classically, and conversely, so well-suited for quantum computing.
These inherently quantum problems also lie at the heart of many complex and useful material properties. The quantum Ising model is an entry point to confront some of the deepest mysteries in the study of interacting quantum magnets. While rooted in fundamental physics, its relevance extends to wide-ranging commercial and defense applications, including medical test equipment, quantum sensors, and the study of exotic states of matter like superconductivity.
Instead of tailored demonstrations that claim ‘quantum advantage’ in contrived scenarios, our breakthroughs announced this week prove that we can tackle complex, meaningful scientific questions difficult for classical methods to address. In the work described in this paper, we have proved that quantum computing could be the gold standard for materials simulations. These developments are critical steps toward realizing the potential of quantum computers.
With only 56 qubits in our commercially available System Model H2, the most powerful quantum system in the world today, we are already testing the limits of classical methods, and in some cases, exceeding them. Later this year, we will introduce our massively more powerful 96-qubit Helios system - breaching the boundaries of what until recently was deemed possible.
The marriage of AI and quantum computing is going to have a widespread and meaningful impact in many aspects of our lives, combining the strengths of both fields to tackle complex problems.
Quantum and AI are the ideal partners. At Quantinuum, we are developing tools to accelerate AI with quantum computers, and quantum computers with AI. According to recent independent analysis, our quantum computers are the world’s most powerful, enabling state-of-the-art approaches like Generative Quantum AI (Gen QAI), where we train classical AI models with data generated from a quantum computer.
We harness AI methods to accelerate the development and performance of our full quantum computing stack as opposed to simply theorizing from the sidelines. A paper in Nature Machine Intelligence reveals the results of a recent collaboration between Quantinuum and Google DeepMind to tackle the hard problem of quantum compilation.
The work shows a classical AI model supporting quantum computing by demonstrating its potential for quantum circuit optimization. An AI approach like this has the potential to lead to more effective control at the hardware level, to a richer suite of middleware tools for quantum circuit compilation, error mitigation and correction, even to novel high-level quantum software primitives and quantum algorithms.
An AI power-up for circuit optimization
The joint Quantinuum-Google DeepMind team of researchers tackled one of quantum computing’s most pressing challenges: minimizing the number of highly expensive but essential T-gates required for universal quantum computation. This is important specifically for the fault-tolerant regime, which is becoming increasingly relevant as quantum error correction protocols are being explored on rapidly developing quantum hardware. The joint team of researchers adapted AlphaTensor, Google DeepMind’s reinforcement learning AI system for algorithm discovery, which was introduced to improve the efficiency of linear algebra computations. The team introduced AlphaTensor-Quantum, which takes as input a quantum circuit and returns a new, more efficient one in terms of number of T-gates, with exactly the same functionality!
AlphaTensor-Quantum outperformed current state-of-the art optimization methods and matched the best human-designed solutions across multiple circuits in a thoroughly curated set of circuits, chosen for their prevalence in many applications, from quantum arithmetic to quantum chemistry. This breakthrough shows the potential for AI to automate the process of finding the most efficient quantum circuit. This is the first time that such an AI model has been put to the problem of T-count reduction at such a large scale.
A quantum power-up for machine learning
The symbiotic relationship between quantum and AI works both ways. When AI and quantum computing work together, quantum computers could dramatically accelerate machine learning algorithms, whether by the development and application of natively quantum algorithms, or by offering quantum-generated training data that can be used to train a classical AI model.
Our recent announcement about Generative Quantum AI (Gen QAI) spells out our commitment to unlocking the value of the data generated by our H2 quantum computer. This value arises from the world’s leading fidelity and computational power of our System Model H2, making it impossible to exactly simulate on any classical computer, and therefore the data it generates – that we can use to train AI – is inaccessible by any other means. Quantinuum’s Chief Scientist for Algorithms and Innovation, Prof. Harry Buhrman, has likened accessing the first truly quantum-generated training data to the invention of the modern microscope in the seventeenth century, which revealed an entirely new world of tiny organisms thriving unseen within a single drop of water.
Recently, we announced a wide-ranging partnership with NVIDIA. It charts a course to commercial scale applications arising from the partnership between high-performance classical computers, powerful AI systems, and quantum computers that breach the boundaries of what previously could and could not be done. Our President & CEO, Dr. Raj Hazra spoke to CNBC recently about our partnership. Watch the video here.
As we prepare for the next stage of quantum processor development, with the launch of our Helios system in 2025, we’re excited to see how AI can help write more efficient code for quantum computers – and how our quantum processors, the most powerful in the world, can provide a backend for AI computations.
As in any truly symbiotic relationship, the addition of AI to quantum computing equally benefits both sides of the equation.
To read more about Quantinuum and Google DeepMind’s collaboration, please read the scientific paper here.