Quantinuum and Microsoft achieve breakthrough that unlocks a new era of reliable quantum computing
Quantinuum’s System Model H2 enabled Microsoft’s qubit-virtualization system to generate the most reliable logical qubits ever recorded, a breakthrough with wide ranging implications for everyone in quantum computing, accelerating progress and challenging current assumptions about the timeline toward large scale reliable quantum computing.
By Ilyas Khan, Chief Product Officer and Jenni Strabley, Senior Director Offering Management
Quantinuum and Microsoft have announced a vital breakthrough in quantum computing that Microsoft described as “a major achievement for the entire quantum ecosystem.”
By combining Microsoft’s innovative qubit-virtualization system with the unique architectural features and fidelity of Quantinuum’s System Model H2 quantum computer, our teams have demonstrated the most reliable logical qubits on record with logical circuit error rates 800 times lower than the corresponding physical circuit error rates.
This achievement is not just monumental for Quantinuum and Microsoft, but it is a major advancement for the entire quantum ecosystem. It is a crucial milestone on the path to building a hybrid supercomputing system that can truly transform research and innovation across many industries for decades to come. It also further bolsters H2’s title as the highest performing quantum computer in the world.
Entering a new era of quantum computing
Historically, there have been widely held assumptions about the physical qubits needed for large scale fault-tolerant quantum computing and the timeline to quantum computers delivering real-world value. It was previously thought that an achievement like this one was still years away from realization – but together, Quantinuum and Microsoft proved that fault-tolerant quantum computing is in fact a reality.
In enabling today’s announcement, Quantinuum’s System Model H2 becomes the first quantum computer to advance to Microsoft’s Level 2 – Resilient phase of quantum computing – an incredible milestone. Until now, no other computer had been capable of producing reliable logical qubits.
Using Microsoft’s qubit-virtualization system, our teams used reliable logical qubits to perform 14,000 individual instances of a quantum circuit with no errors, an overall result that is unprecedented. Microsoft also demonstrated multiple rounds of active syndrome extraction – an essential error correction capability for measuring and detecting the occurrence of errors without destroying the quantum information encoded in the logical qubit.
As we prepare to bring today’s logical quantum computing breakthrough to commercial users, there is palpable anticipation about what this new era means for our partners, customers, and the global quantum computing ecosystem that has grown up around our hardware, middleware, and software.
Collaborating to reach a new era
To understand this achievement, it is helpful to shed some light on the joint work that went into it. Our breakthrough would not have been possible without the close collaboration of the two exceptional teams at Quantinuum and Microsoft over many years.
Building on a relationship that stretches back five years, we collaborated with Microsoft Azure Quantum at a very deep level to best execute their innovative qubit-virtualization system, including error diagnostics and correction. The Microsoft team was able to optimize their error correction innovation, reducing an original estimate of 300 required physical qubits 10-fold, to create four logical qubits with only 30 physical qubits, bringing it into scope for the 32-qubit H2 quantum computer.
This massive compression of the code and efficient virtualization challenges a consensus view about the resources needed to do fault-tolerant quantum computing, where it has been routinely stated that a logical qubit will require hundreds, even thousands of physical qubits. Through our collaboration, Microsoft’s far more efficient encoding was made possible by architectural features unique to the System Model H2, including our market-leading 99.8% two-qubit gate fidelity, 32 fully-connected qubits, and compatibility with Quantum Intermediate Representation (QIR).
Thanks to this powerful combination of collaboration, engineering excellence, and resource efficiency, quantum computing has taken a major step into a new era, introducing reliable logical qubits which will soon be available to industrial and research users.
Understanding today’s error correction breakthrough
It is widely recognized that for a quantum computer to be useful, it must be able to compute correctly even when errors (or faults) occur – this is what scientists and engineers describe as fault-tolerance.
In classical computing, fault-tolerance is well-understood and we have come to take it for granted. We always assume that our computers will be reliable and fault-free. Multiple advances over the course of decades have led to this state of affairs, including hardware that is incredibly robust and error rates that are very low, and classical error correction schemes that are based on the ability to copy information across multiple bits, to create redundancy.
Getting to the same point in quantum computing is more challenging, although the solution to this problem has been known for some time. Qubits are incredibly delicate since one must control the precise quantum states of single atoms, which are prone to errors. Additionally, we must abide by a fundamental law of quantum physics known as the no cloning theorem, which says that you can’t just copy qubits – meaning some of the techniques used in classical error correction are unavailable in quantum machines.
The solution involves entangling groups of physical qubits (thereby creating a logical qubit), storing the relevant quantum information in the entangled state, and, via some complex functions, performing computations with error correction. This process is all done with the sole purpose of creating logical qubit errors lower than the errors at the physical level.
However, implementing quantum error correction requires a significant number of qubit operations. Unless the underlying physical fidelity is good enough, implementing a quantum error correcting code will add more noise to your circuit than it takes away. No matter how clever you are in implementing a code, if your physical fidelity is poor, the error correcting code will only introduce more noise. But, once your physical fidelity is good enough (aka when the physical error rate is “below threshold”), then you will see the error correcting code start to actually help: producing logical errors below the physical errors.
Quantinuum’s fault-tolerance roadmap
Today’s results are an exciting marker on the path to fault-tolerant quantum computing. The focus must and will now shift from quantum computing companies simply stating the number of qubits they have to explaining their connectivity, the underlying quality of the qubits with reference to gate fidelities, and their approach to fault-tolerance.
Our H-Series hardware roadmap has not only focused on scaling qubits, but also developing useable quantum computers that are part of a vertically integrated stack. Our work across the full stack includes major advances at every level, for instance just last month we proved that our qubits could scale when we announced solutions to the wiring problem and the sorting problem. By maintaining higher qubit counts and world class fidelity, our customers and partners are able to advance further and faster in fields such as material science, drug discovery, AI and finance.
In 2025, we will introduce a new H-Series quantum computer, Helios, that takes the very best the H-Series has to offer, improving both physical qubit count and physical fidelity. This will take us and our users below threshold for a wider set of error correcting codes and make that device capable of supporting at least 10 highly reliable logical qubits.
A path to real-world impact
As we build upon today’s milestone and lead the field on the path to fault-tolerance, we are committed to continuing to make significant strides in the research that enables the rapid advance of our technologies. We were the first to demonstrate real-time quantum error correction (meaning a fully-fault tolerant QEC protocol), a result that meant we were the first to show: repeated real-time error correction, the ability to perform quantum "loops" (repeat-until-success protocols), and real-time decoding to determine the corrections during the computation. We were the first to create non-Abelian topological quantum matter and braid its anyons, leading to topological qubits.
The native flexibility of our QCCD architecture has allowed us to efficiently investigate a large variety of fault-tolerant methods, and our best-in-class fidelity means we expect to lead the way in achieving reduced error rates with additional error correcting codes – and supporting our partners to do the same. We are already working on making reliable quantum computing a commercial reality so that our customers and partners can unlock the enormous real-world economic value that is waiting to be unleashed by the development of these systems.
In the short term – with a hybrid supercomputer powered by a hundred reliable logical qubits, we believe that organizations will be able to start to see scientific advantages and will be able to accelerate valuable progress toward some of the most important problems that mankind faces such as modelling the materials used in batteries and hydrogen fuel cells or accelerating the development of meaning-aware AI language models. Over the long-term, if we are able to scale closer to ~1,000 reliable logical qubits, we will be able to unlock the commercial advantages that can ultimately transform the commercial world.
Quantinuum customers have always been able to operate the most cutting-edge quantum computing, and we look forward to seeing how they, and our own world-leading teams, drive ahead developing new solutions based on the state-of-the-art tools we continue to put into their hands. We were the early leaders in quantum computing and now we are thrilled to be positioned at the forefront of fault-tolerant quantum computing. We are excited to see what today’s milestone unlocks for our customers in the days ahead.
For more information
- Please register for Microsoft’s upcoming Quantum Innovator Series with Quantinuum
- Visit Quantinuum InQuanto to explore this state-of-the-art chemistry platform that will soon offer reliable logical qubits
- Read Microsoft’s announcement
- See System Model H1 and H2 integrated on Azure Quantum
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.
At this year’s Q2B Silicon Valley conference from December 10th – 12th in Santa Clara, California, the Quantinuum team will be participating in plenary and case study sessions to showcase our quantum computing technologies.
Schedule a meeting with us at Q2B
Meet our team at Booth #G9 to discover how Quantinuum is charting the path to universal, fully fault-tolerant quantum computing.
Join our sessions:
Tuesday, Dec 10, 10:00 - 10:20am PT
Plenary: Advancements in Fault-Tolerant Quantum Computation: Demonstrations and Results
There is industry-wide consensus on the need for fault-tolerant QPU’s, but demonstrations of these abilities are less common. In this talk, Dr. Hayes will review Quantinuum’s long list of meaningful demonstrations in fault-tolerance, including real-time error correction, a variety of codes from the surface code to exotic qLDPC codes, logical benchmarking, beyond break-even behavior on multiple codes and circuit families.
Wednesday, Dec 11, 4:30 – 4:50pm PT
Keynote: Quantum Tokens: Securing Digital Assets with Quantum Physics
Mitsui’s Deputy General Manager, Quantum Innovation Dept., Corporate Development Div., Koji Naniwada, and Quantinuum’s Head of Cybersecurity, Duncan Jones will deliver a keynote presentation on a case study for quantum in cybersecurity. Together, our organizations demonstrated the first implementation of quantum tokens over a commercial QKD network. Quantum tokens enable three previously incompatible properties: unforgeability guaranteed by physics, fast settlement without centralized validation, and user privacy until redemption. We present results from our successful Tokyo trial using NEC's QKD commercial hardware and discuss potential applications in financial services.
Wednesday, Dec 11, 5:10 – 6:10pm PT
Quantinuum and Mitsui Sponsored Happy Hour
Join the Quantinuum and Mitsui teams in the expo hall for a networking happy hour.
Particle accelerator projects like the Large Hadron Collider (LHC) don’t just smash particles - they also power the invention of some of the world’s most impactful technologies. A favorite example is the world wide web, which was developed for particle physics experiments at CERN.
Tech designed to unlock the mysteries of the universe has brutally exacting requirements – and it is this boundary pushing, plus billion-dollar budgets, that has led to so much innovation.
For example, X-rays are used in accelerators to measure the chemical composition of the accelerator products and to monitor radiation. The understanding developed to create those technologies was then applied to help us build better CT scanners, reducing the x-ray dosage while improving the image quality.
Stories like this are common in accelerator physics, or High Energy Physics (HEP). Scientists and engineers working in HEP have been early adopters and/or key drivers of innovations in advanced cancer treatments (using proton beams), machine learning techniques, robots, new materials, cryogenics, data handling and analysis, and more.
A key strand of HEP research aims to make accelerators simpler and cheaper. A key piece of infrastructure that could be improved is their computing environments.
CERN itself has said: “CERN is one of the most highly demanding computing environments in the research world... From software development, to data processing and storage, networks, support for the LHC and non-LHC experimental programme, automation and controls, as well as services for the accelerator complex and for the whole laboratory and its users, computing is at the heart of CERN’s infrastructure.”
With annual data generated by accelerators in excess of exabytes (a billion gigabytes), tens of millions of lines of code written to support the experiments, and incredibly demanding hardware requirements, it’s no surprise that the HEP community is interested in quantum computing, which offers real solutions to some of their hardest problems.
As the authors of this paper stated: “[Quantum Computing] encompasses several defining characteristics that are of particular interest to experimental HEP: the potential for quantum speed-up in processing time, sensitivity to sources of correlations in data, and increased expressivity of quantum systems... Experiments running on high-luminosity accelerators need faster algorithms; identification and reconstruction algorithms need to capture correlations in signals; simulation and inference tools need to express and calculate functions that are classically intractable.”
The HEP community’s interest in quantum computing is growing. In recent years, their scientists have been looking carefully at how quantum computing could help them, publishing a number of papers discussing the challenges and requirements for quantum technology to make a dent (here’s one example, and here’s the arXiv version).
In the past few months, what was previously theoretical is becoming a reality. Several groups published results using quantum machines to tackle something called “Lattice Gauge Theory”, which is a type of math used to describe a broad range of phenomena in HEP (and beyond). Two papers came from academic groups using quantum simulators, one using trapped ions and one using neutral atoms. Another group, including scientists from Google, tackled Lattice Gauge Theory using a superconducting quantum computer. Taken together, these papers indicate a growing interest in using quantum computing for High Energy Physics, beyond simple one-dimensional systems which are more easily accessible with classical methods such as tensor networks.
We have been working with DESY, one of the world’s leading accelerator centers, to help make quantum computing useful for their work. DESY, short for Deutsches Elektronen-Synchrotron, is a national research center that operates, develops, and constructs particle accelerators, and is part of the worldwide computer network used to store and analyze the enormous flood of data that is produced by the LHC in Geneva.
Our first publication from this partnership describes a quantum machine learning technique for untangling data from the LHC, finding that in some cases the quantum approach was indeed superior to the classical approach. More recently, we used Quantinuum System Model H1 to tackle Lattice Gauge Theory (LGT), as it’s a favorite contender for quantum advantage in HEP.
Lattice Gauge Theories are one approach to solving what are more broadly referred to as “quantum many-body problems”. Quantum many-body problems lie at the border of our knowledge in many different fields, such as the electronic structure problem which impacts chemistry and pharmaceuticals, or the quest for understanding and engineering new material properties such as light harvesting materials; to basic research such as high energy physics, which aims to understand the fundamental constituents of the universe, or condensed matter physics where our understanding of things like high-temperature superconductivity is still incomplete.
The difficulty in solving problems like this – analytically or computationally – is that the problem complexity grows exponentially with the size of the system. For example, there are 36 possible configurations of two six-faced dice (1 and 1 or 1 and 2 or 1and 3... etc), while for ten dice there are more than sixty million configurations.
Quantum computing may be very well-suited to tackling problems like this, due to a quantum processor’s similar information density scaling – with the addition of a single qubit to a QPU, the information the system contains doubles. Our 56-qubit System Model H2, for example, can hold quantum states that require 128*(2^56) bits worth of information to describe (with double-precision numbers) on a classical supercomputer, which is more information than the biggest supercomputer in the world can hold in memory.
The joint team made significant progress in approaching the Lattice Gauge Theory corresponding to Quantum Electrodynamics, the theory of light and matter. For the first time, they were able study the full wavefunction of a two-dimensional confining system with gauge fields and dynamical matter fields on a quantum processor. They were also able to visualize the confining string and the string-breaking phenomenon at the level of the wavefunction, across a range of interaction strengths.
The team approached the problem starting with the definition of the Hamiltonian using the InQuanto software package, and utilized the reusable protocols of InQuanto to compute both projective measurements and expectation values. InQuanto allowed the easy integration of measurement reduction techniques and scalable error mitigation techniques. Moreover, the emulator and hardware experiments were orchestrated by the Nexus online platform.
In one section of the study, a circuit with 24 qubits and more than 250 two-qubit gates was reduced to a smaller width of 15 qubits thanks our unique qubit re-use and mid-circuit measurement automatic compilation implemented in TKET.
This work paves the way towards using quantum computers to study lattice gauge theories in higher dimensions, with the goal of one day simulating the full three-dimensional Quantum Chromodynamics theory underlying the nuclear sector of the Standard Model of particle physics. Being able to simulate full 3D quantum chromodynamics will undoubtedly unlock many of Nature’s mysteries, from the Big Bang to the interior of neutron stars, and is likely to lead to applications we haven’t yet dreamed of.