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ҹɫֱ accelerates the path to Universal Fully Fault-Tolerant Quantum Computing

Supports Microsoft’s AI and quantum-powered compute platform and “the path to a Quantum Supercomputer”

September 10, 2024

ҹɫֱ is uniquely known for, and has always put a premium on, demonstrating rather than merely promising breakthroughs in quantum computing.

When we unveiled the first H-Series quantum computer in 2020, not only did we pioneer the world-leading quantum processors, but we also went the extra mile. We included industry leading comprehensive benchmarking to ensure that any expert could independently verify our results. Since then, our computers have maintained the lead against all competitors in performance and transparency. Today our System Model H2 quantum computer with 56 qubits is the most powerful quantum computer available for industry and scientific research – and the most benchmarked.

More recently, in a period where we upgraded our H2 system from 32 to 56 qubits and demonstrated the scalability of our QCCD architecture, we also , and announced that we had achieved “three 9’s” fidelity, enabling real gains in fault-tolerance – which we proved within months as we demonstrated the most reliable logical qubits in the world with our partner Microsoft.

We don’t just promise what the future might look like; we demonstrate it.

Today, at Quantum World Congress, we shared how recent developments by our integrated hardware and software teams have, yet again, accelerated our technology roadmap. It is with the confidence of what we’ve already demonstrated that we can uniquely announce that by the end of this decade ҹɫֱ will achieve universal fully fault-tolerant quantum computing, built on foundations such as a universal fault-tolerant gate set, high fidelity physical qubits uniquely capable of supporting reliable logical qubits, and a fully-scalable architecture.

ҹɫֱ's hardware development roadmap to achieve universal, fully fault-tolerant quantum computing

We also demonstrated, with Microsoft, what rapid acceleration looks like with the creation of 12 highly reliable logical qubits – tripling the number from just a few months ago. Among other demonstrations, we supported Microsoft to create the first ever chemistry simulation using reliable logical qubits combined with Artificial Intelligence (AI) and High-Performance Computing (HPC), producing results within chemical accuracy. This is a critical demonstration of what Microsoft has called “the path to a Quantum Supercomputer”.

ҹɫֱ’s H-Series quantum computers, Powered by Honeywell, were among the first devices made available via Microsoft Azure, where they remain available today. Building on this, we are excited to share that ҹɫֱ and Microsoft have completed integration of ҹɫֱ’s InQuanto™ computational quantum chemistry software package with Azure Quantum Elements, the AI enabled generative chemistry platform. The integration mentioned above is accessible to customers participating in a private preview of Azure Quantum Elements, which can be requested from Microsoft and ҹɫֱ. 

We created a short video on the importance of logical qubits, which you can see here:

These demonstrations show that we have the tools to drive progress towards scientific and industrial advantage in the coming years. Together, we’re demonstrating how quantum computing may be applied to some of humanity’s most pressing problems, many of which are likely only to be solved with the combination of key technologies like AI, HPC, and quantum computing.

Our credible roadmap draws a direct line from today to hundreds of logical qubits - at which point quantum computing, possibly combined with AI and HPC, will outperform classical computing for a range of scientific problems.

“The collaboration between ҹɫֱ and Microsoft has established a crucial step forward for the industry and demonstrated a critical milestone on the path to hybrid classical-quantum supercomputing capable of transforming scientific discovery.” – Dr. Krysta Svore – Technical Fellow and VP of Advanced Quantum Development for Microsoft Azure Quantum

What we revealed today underlines the accelerating pace of development. It is now clear that enterprises need to be ready to take advantage of the progress we can see coming in the next business cycle.

Why now?

The industry consensus is that the latter half of this decade will be critical for quantum computing, prompting many companies to develop roadmaps signalling their path toward error corrected qubits. In their entirety, ҹɫֱ’s technical and scientific advances accelerate the quantum computing industry, and as we have shown today, reveal a path to universal fault-tolerance much earlier than expected.

Grounded in our prior demonstrations, we now have sufficient visibility into an accelerated timeline for a highly credible hardware roadmap, making now the time to release an update. This provides organizations all over the world with a way to plan, reliably, for universal fully fault-tolerant quantum computing. We have shown how we will scale to more physical qubits at fidelities that support lower error rates (made possible by QEC), with the capacity for “universality” at the logical level. “Universality” is non-negotiable when making good on the promise of quantum computing: if your quantum computer isn’t universal everything you do can be efficiently reproduced on a classical computer.

“Our proven history of driving technical acceleration, as well as the confidence that globally renowned partners such as Microsoft have in us, means that this is the industry’s most bankable roadmap to universal fully fault-tolerant quantum computing,” said Dr. Raj Hazra, ҹɫֱ’s CEO.

Where we go from here?

Before the end of the decade, our quantum computers will have thousands of physical qubits, hundreds of logical qubits with error rates less than 10-6, and the full machinery required for universality and fault-tolerance – truly making good on the promise of quantum computing.

ҹɫֱ has a proven history of achieving our technical goals. This is evidenced by our leadership in hardware, software, and the ecosystem of developer tools that make quantum computing accessible. Our leadership in quantum volume and fidelity, our consistent cadence of breakthrough publications, and our collaboration with enterprises such as Microsoft, showcases our commitment to pushing the boundaries of what is possible.

We are now making an even stronger public commitment to deliver on our roadmap, ushering the industry toward the era of universal fully fault-tolerant quantum computing this decade. We have all the machinery in place for fault-tolerance with error rates around 10-6, meaning we will be able to run circuits that are millions of gates deep – putting us on a trajectory for scientific quantum advantage, and beyond.

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.

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March 28, 2025
Being Useful Now – Quantum Computers and Scientific Discovery

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.

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March 27, 2025
ҹɫֱ and Google DeepMind Unveil the Reality of the Symbiotic Relationship Between Quantum and AI

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 .

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March 26, 2025
ҹɫֱ Introduces First Commercial Application for Quantum Computers

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.

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