ҹɫֱ extends its significant lead in quantum computing, achieving historic milestones for hardware fidelity and Quantum Volume
ҹɫֱ 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 , ҹɫֱ 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.
ҹɫֱ 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, ҹɫֱ 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 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, ҹɫֱ 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 , as are
The combination of high QV and gate fidelities puts the ҹɫֱ 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. ҹɫֱ 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 ҹɫֱ.
“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.”
ҹɫֱ’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.
ҹɫֱ 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 ҹɫֱ
ҹɫֱ, the world’s largest integrated quantum company, pioneers powerful quantum computers and advanced software solutions. ҹɫֱ’s technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With over 500 employees, including 370+ scientists and engineers, ҹɫֱ leads the quantum computing revolution across continents.
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 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 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 ҹɫֱ’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, “.” 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 ҹɫֱ, 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 ҹɫֱ 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 ҹɫֱ-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. ҹɫֱ’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 ҹɫֱ and Google DeepMind’s collaboration, please read the scientific paper .
Few things are more important to the smooth functioning of our digital economies than trustworthy security. From finance to healthcare, from government to defense, quantum computers provide a means of building trust in a secure future.
ҹɫֱ and its partners JPMorganChase, Oak Ridge National Laboratory, Argonne National Laboratory and the University of Texas used quantum computers to solve a known industry challenge, generating the “random seeds” that are essential for the cryptography behind all types of secure communication. As our partner and collaborator, JPMorganChase explain in this that true randomness is a scarce and valuable commodity.
This year, ҹɫֱ will introduce a new product based on this development that has long been anticipated, but until now thought to be some years away from reality.
It represents a major milestone for quantum computing that will reshape commercial technology and cybersecurity: Solving a critical industry challenge by successfully generating certifiable randomness.
Building on the extraordinary computational capabilities of ҹɫֱ’s H2 System – the highest-performing quantum computer in the world – our team has implemented a groundbreaking approach that is ready-made for industrial adoption. of a proof of concept with JPMorganChase, Oak Ridge National Laboratory, Argonne National Laboratory, and the University of Texas alongside ҹɫֱ. It lays out a new quantum path to enhanced security that can provide early benefits for applications in cryptography, fairness, and privacy.
By harnessing the powerful properties of quantum mechanics, we’ve shown how to generate the truly random seeds critical to secure electronic communication, establishing a practical use-case that was unattainable before the fidelity and scalability of the H2 quantum computer made it reliable. So reliable, in fact, that it is now possible to turn this into a commercial product.
ҹɫֱ will integrate quantum-generated certifiable randomness into our commercial portfolio later this year. Alongside Generative Quantum AI and our upcoming Helios system – capable of tackling problems a trillion times more computationally complex than H2 – ҹɫֱ is further cementing its leadership in the rapidly-advancing quantum computing industry.
This Matters Because Cybersecurity Matters
Cryptographic security, a bedrock of the modern economy, relies on two essential ingredients: standardized algorithms and reliable sources of randomness – the stronger the better. Non-deterministic physical processes, such as those governed by quantum mechanics, are ideal sources of randomness, offering near-total unpredictability and therefore, the highest cryptographic protection. Google, when it originally announced , speculated on the possibility of using the random circuit sampling (RCS) protocol for the commercial production of certifiable random numbers. RCS has been used ever since to demonstrate the performance of quantum computers, including a milestone achievement in June 2024 by ҹɫֱ and JPMorganChase, demonstrating their first quantum computer to defy classical simulation. More recently RCS was used again by Google for the launch of its Willow processor.
In today’s , our joint team used the world’s highest-performing quantum and classical computers to generate certified randomness via RCS. The work was based on advanced research by Shih-Han Hung and Scott Aaronson of the University of Texas at Austin, who are co-authors on today’s paper.
Following a string of major advances in 2024 – solving the scaling challenge, breaking new records for reliability in partnership with Microsoft, and unveiling a hardware roadmap, today proves how quantum technology is capable of creating tangible business value beyond what is available with classical supercomputers alone.
What follows is intended as a non-technical explainer of the results in today’s Nature paper.
Certified Randomness: The First Commercial Application for Quantum Computers
For security sensitive applications, classical random number generation is unsuitable because it is not fundamentally random and there is a risk it can be “cracked”. The holy grail is randomness whose source is truly unpredictable, and Nature provides just the solution: quantum mechanics. Randomness is built into the bones of quantum mechanics, where determinism is thrown out the door and outcomes can be true coin flips.
At ҹɫֱ, we have a strong track record in developing methods for generating certifiable randomness using a quantum computer. In 2021, we introduced Quantum Origin to the market, as a quantum-generated source of entropy targeted at hardening classically-generated encryption keys, using well known quantum technologies that prior to that it had not been possible to use.
In their theory paper, , Hung and Aaronson ask the question: is it possible to repurpose RCS, and use it to build an application that moves beyond quantum technologies and takes advantage of the power of a quantum computer running quantum circuits?
This was the inspiration for the collaboration team led by JPMorganChase and ҹɫֱ to draw up plans to execute the proposal using real-world technology. Here’s how it worked:
- The team sent random circuits to ҹɫֱ’s H2, the world’s highest performing commercially available quantum computer.
- The quantum computer executed each circuit and returned the corresponding sample. The response times were remarkably short, and it could be proven that the circuits could not have been simulated classically within those times, even using the best-known techniques on computing resources greater than those available in the world’s most powerful classical supercomputer.
- The randomness of the returned sample was mathematically certified using Frontier, the world’s most powerful classical supercomputer, establishing it achieved a “passing threshold” on a measure known as the “cross-entropy benchmark”. The better your quantum computer, the higher you can set the “passing threshold”. When the threshold is sufficiently high, "spoofing" the cross-entropy benchmark using only classical methods becomes inefficient.
- Therefore, if the samples are returned quickly and meet the high threshold, the team could be confident that they were generated by a quantum computer – and thus be truly random.
This confirmed that ҹɫֱ’s quantum computer is not only incapable of being matched by classical computers but can also be used reliably to produce a certifiably random seed from a quantum computer without the need to build your own device, or even trust the device you are accessing.
Looking ahead
The use of randomness in critical cybersecurity environments will gravitate towards quantum resources, as the security demands of end users grows in the face of ongoing cyber threats.
The era of quantum utility offers the promise of radical new approaches to solving substantial and hard problems for businesses and governments.
ҹɫֱ’s H2 has now demonstrated practical value for cybersecurity vendors and customers alike, where non-deterministic sources of encryption may in time be overtaken by nature’s own source of randomness.
In 2025, we will launch our Helios device, capable of supporting at least 50 high-fidelity logical qubits – and further extending our lead in the quantum computing sector. We thus continue our track record of disclosing our objectives and then meeting or surpassing them. This commitment is essential, as it generates faith and conviction among our partners and collaborators, that empirical results such as those reported today can lead to successful commercial applications.
Helios, which is already in its late testing phase, ahead of being commercially available later this year, brings higher fidelity, greater scale, and greater reliability. It promises to bring a wider set of hybrid quantum-supercomputing opportunities to our customers – making quantum computing more valuable and more accessible than ever before.
And in 2025 we look forward to adding yet another product, building out our cybersecurity portfolio with a quantum source of certifiably random seeds for a wide range of customers who require this foundational element to protect their businesses and organizations.