Quantinuum achieves moonshot years ahead of schedule, demonstrating fault-tolerant high-fidelity teleportation of a logical qubit
While it sounds like a gadget from Star Trek, teleportation is real – and it is happening at Quantinuum. In a new paper published in Science, our researchers moved a quantum state from one place to another without physically moving it through space - and they accomplished this feat with fault-tolerance and excellent fidelity. This is an important milestone for the whole quantum computing community and the latest example of Quantinuum achieving critical milestones years ahead of expectations.
While it seems exotic, teleportation is a critical piece of technology needed for full scale fault-tolerant quantum computing, and it is used widely in algorithm and architecture design. In addition to being essential on its own, teleportation has historically been used to demonstrate a high level of system maturity. The protocol requires multiple qubits, high-fidelity state-preparation, single-qubit operations, entangling operations, mid-circuit measurement, and conditional operations, making it an excellent system-level benchmark.
Our team was motivated to do this work by the US Government Intelligence Advance Research Projects Activity (IARPA), who set a challenge to perform high fidelity teleportation with the goal of advancing the state of science in universal fault-tolerant quantum computing. IARPA further specified that the entanglement and teleportation protocols must also maintain fault-tolerance, a key property that keeps errors local and correctable.
These ambitious goals required developing highly complex systems, protocols, and other infrastructure to enable exquisite control and operation of quantum-mechanical hardware. We are proud to have accomplished these goals ahead of schedule, demonstrating the flexibility, performance, and power of Quantinuum’s Quantum Charge Coupled Device (QCCD) architecture.
Quantinuum’s demonstration marks the first time that an arbitrary quantum state has been teleported at the logical level (using a quantum error correcting code). This means that instead of teleporting the quantum state of a single physical qubit we have teleported the quantum information encoded in an entangled set of physical qubits, known as a logical qubit. In other words, the collective state of a bunch of qubits is teleported from one set of physical qubits to another set of physical qubits. This is, in a sense, a lot closer to what you see in Star Trek – they teleport the state of a big collection of atoms at once. Except for the small detail of coming up with a pile of matter with which to reconstruct a human body...
This is also the first demonstration of a fully fault-tolerant version of the state teleportation circuit using real-time quantum error correction (QEC), decoding mid-circuit measurement of syndromes and implementing corrections during the protocol. It is critical for computers to be able to catch and correct any errors that happen along the way, and this is not something other groups have managed to do in any robust sense. In addition, our team achieved the result with high fidelity (97.5%±0.2%), providing a powerful demonstration of the quality of our H2 quantum processor, Powered by Honeywell.
Our team also tried several variations of logical teleportation circuits, using both transversal gates and lattice surgery protocols, thanks to the flexibility of our QCCD architecture. This marks the first demonstration of lattice surgery performed on a QEC code.
Lattice surgery is a strategy for implementing logical gates that requires only 2D nearest-neighbor interactions, making it especially useful for architectures whose qubit locations are fixed, such as superconducting architectures. QCCD and other technologies that do not have fixed qubit positioning might employ this method, another method, or some mixture. We are fortunate that our QCCD architecture allows us to explore the use of different logical gating options so that we can optimize our choices for experimental realities.
While the teleportation demonstration is the big result, sometimes it is the behind-the-scenes technology advancements that make the big differences. The experiments in this paper were designed at the logical level using an internally developed logical-level programming language dubbed Simple Logical Representation (SLR). This is yet another marker of our system’s maturity – we are no longer programming at the physical level but have instead moved up one “layer of abstraction”. Someday, all quantum algorithms will need to be run on the logical level with rounds of quantum error correction. This is a markedly different state than most present experiments, which are run on the physical level without quantum error correction. It is also worth noting that these results were generated using the software stack available to any user of Quantinuum’s H-Series quantum computers, and these experiments were run alongside customer jobs – underlining that these results are commercial performance, not hero data on a bespoke system.
Ironically, a key element in this work is our ability to move our qubits through space the “normal” way - this capacity gives us all-to-all connectivity, which was essential for some of the QEC protocols used in the complex task of fault-tolerant logical teleportation. We recently demonstrated solutions to the sorting problem and wiring problem in a new 2D grid trap, which will be essential as we scale up our devices.
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.
I continue to be inspired by our team's pioneering efforts to redefine what’s possible through quantum computing. With more than 550 dedicated employees, we’re constantly pushing the boundaries to uncover meaningful applications for this transformative technology.
This week marked one of my proudest moments: the announcement of a joint venture with Al Rabban Capital to accelerate the commercial adoption of quantum technology in Qatar and the Gulf region. This partnership lays the groundwork for up to USD $1 billion in investment from Qatar over the next decade in Quantinuum’s state-of-the-art quantum technologies, co-development of quantum computing applications tailored to regional needs, and workforce development. This collaboration is a major step forward in our strategy to expand our commercial reach through long-term, strategic alliances that foster economic growth in both the U.S. and Qatar.
I had the unique opportunity to attend a business roundtable in Doha with President Trump, U.S. and Qatari policymakers, and other industry leaders. The conversation centered on the importance of U.S.-Qatari relations and the role of shared commercial interests in strengthening that bond.
A recurring theme was innovation in Artificial Intelligence (AI), reinforcing the role that hybrid quantum-classical systems will play in enhancing AI capabilities across sectors. By integrating quantum computing, AI, and high-performance computing, we can unlock powerful new use cases critical to economic growth and national security.
We also addressed the growing energy demands of AI-powered data centers. Quantum computing offers a potential path forward here, as well. Our H2-1 system has demonstrated an estimated 30,000x reduction in power consumption compared to classical supercomputers, making it a highly efficient tool for solving complex computational challenges.
What struck me most about the conversations in Qatar was the emphasis on cooperation over competition. While quantum is often framed as a race, our partnership with Al Rabban Capital underscores the value of cross-border collaboration. As I noted in a recent Time Magazine article co-authored with Honeywell CEO Vimal Kapur, quantum computing isn’t just a technology—it’s a national capability. Countries that lead will shape how it is regulated, protected, and deployed. Our joint venture and this week’s dialogue reaffirm that both the U.S. and Qatar are taking the necessary first steps to lead in this space. Yet much work remains.
I believe we’re witnessing the emergence of a new kind of global alliance—one rooted not just in trade, but in shared technological advancement. Quantum computing holds the promise to unlock innovative solutions that will tackle challenges that have long been beyond reach. Realizing that promise will require visionary leadership, global collaboration, and a bold commitment to shaping the future together.
I was honored to attend today’s roundtable during the President’s State Visit to Qatar and to see our announcement featured as part of that engagement. This milestone reflects a shared commitment by the U.S. and Qatar to strengthen strategic ties, spur bilateral investment in future-defining industries, and foster technological leadership and shared prosperity.
Quantinuum’s expansion into the Gulf region, starting with Qatar, follows our successful growth in the U.S., U.K., Europe and Indo-Pacific. We will continue working across borders and sectors to accelerate the commercial adoption of quantum computing and realize quantum’s full potential—for the benefit of all!
Details of the JV are available in this link, along with the official White House communication.
Onward and Upward,
Rajeeb Hazra
Back in 2020, we made a promise to increase our Quantum Volume (QV), a measure of computational power, by 10x per year for 5 years.
Today, we’re pleased to share that we’ve followed through on our commitment: Our System Model H2 has reached a Quantum Volume of 2²³ = 8,388,608, proving not just that we always do what we say, but that our quantum computers are leading the world forward.
The QV benchmark was developed by IBM to represent a machine’s performance, accounting for things like qubit count, coherence times, qubit connectivity, and error rates. In IBM's words:
“the higher the Quantum Volume, the higher the potential for exploring solutions to real world problems across industry, government, and research."
Our announcement today is precisely what sets us apart from the competition. No one else has been bold enough to make a similar promise on such a challenging metric – and no one else has ever completed a five-year goal like this.
We chose QV because we believe it’s a great metric. For starters, it’s not gameable, like other metrics in the ecosystem. Also, it brings together all the relevant metrics in the NISQ era for moving towards fault tolerance, such as gate fidelity and connectivity.
Our path to achieve a QV of over 8 million was led in part by Dr. Charlie Baldwin, who studied under the legendary Ivan H. Deutsch. Dr. Baldwin has made his name as a globally renowned expert in quantum hardware performance over the past decade, and it is because of his leadership that we don’t just claim to be the best, but that we can prove we are the best.
Sources: [1][2][3][4][5]
Alongside the world’s biggest quantum volume, we have the industry’s most benchmarked quantum computers. To that point, the table below breaks down the leading commercial specs for each quantum computing architecture.
Download Benchmarking Results
We’ve never shied away from benchmarking our machines, because we know the results will be impressive. It is our provably world-leading performance that has enabled us to demonstrate:
- Quantum Supremacy via Random Circuit Sampling
- Quantum Magnetism at the Frontier of Classical Simulations
- Encoded Memory that Outperforms All Previous Implementations
- Quantum Supremacy for Certified Randomness
- High Fidelity Teleportation of Logical Qubits
As we look ahead to our next generation system, Helios, Quantinuum’s Senior Director of Engineering, Dr. Brian Neyenhuis, reflects: “We finished our five-year commitment to Quantum Volume ahead of schedule, showing that we can do more than just maintain performance while increasing system size. We can improve performance while scaling.”
Helios’ performance will exceed that of our previous machines, meaning that Quantinuum will continue to lead in performance while following through on our promises.
As the undisputed industry leader, we’re racing against no one other than ourselves to deliver higher performance and to better serve our customers.
At the heart of quantum computing’s promise lies the ability to solve problems that are fundamentally out of reach for classical computers. One of the most powerful ways to unlock that promise is through a novel approach we call Generative Quantum AI, or GenQAI. A key element of this approach is the Generative Quantum Eigensolver (GQE).
GenQAI is based on a simple but powerful idea: combine the unique capabilities of quantum hardware with the flexibility and intelligence of AI. By using quantum systems to generate data, and then using AI to learn from and guide the generation of more data, we can create a powerful feedback loop that enables breakthroughs in diverse fields.
Unlike classical systems, our quantum processing unit (QPU) produces data that is extremely difficult, if not impossible, to generate classically. That gives us a unique edge: we’re not just feeding an AI more text from the internet; we’re giving it new and valuable data that can’t be obtained anywhere else.
The Search for Ground State Energy
One of the most compelling challenges in quantum chemistry and materials science is computing the properties of a molecule’s ground state. For any given molecule or material, the ground state is its lowest energy configuration. Understanding this state is essential for understanding molecular behavior and designing new drugs or materials.
The problem is that accurately computing this state for anything but the simplest systems is incredibly complicated. You cannot even do it by brute force—testing every possible state and measuring its energy—because the number of quantum states grows as a double-exponential, making this an ineffective solution. This illustrates the need for an intelligent way to search for the ground state energy and other molecular properties.
That’s where GQE comes in. GQE is a methodology that uses data from our quantum computers to train a transformer. The transformer then proposes promising trial quantum circuits; ones likely to prepare states with low energy. You can think of it as an AI-guided search engine for ground states. The novelty is in how our transformer is trained from scratch using data generated on our hardware.
Here's how it works:
- We start with a batch of trial quantum circuits, which are run on our QPU.
- Each circuit prepares a quantum state, and we measure the energy of that state with respect to the Hamiltonian for each one.
- Those measurements are then fed back into a transformer model (the same architecture behind models like GPT-2) to improve its outputs.
- The transformer generates a new distribution of circuits, biased toward ones that are more likely to find lower energy states.
- We sample a new batch from the distribution, run them on the QPU, and repeat.
- The system learns over time, narrowing in on the true ground state.
To test our system, we tackled a benchmark problem: finding the ground state energy of the hydrogen molecule (H₂). This is a problem with a known solution, which allows us to verify that our setup works as intended. As a result, our GQE system successfully found the ground state to within chemical accuracy.
To our knowledge, we’re the first to solve this problem using a combination of a QPU and a transformer, marking the beginning of a new era in computational chemistry.
The Future of Quantum Chemistry
The idea of using a generative model guided by quantum measurements can be extended to a whole class of problems—from combinatorial optimization to materials discovery, and potentially, even drug design.
By combining the power of quantum computing and AI we can unlock their unified full power. Our quantum processors can generate rich data that was previously unobtainable. Then, an AI can learn from that data. Together, they can tackle problems neither could solve alone.
This is just the beginning. We’re already looking at applying GQE to more complex molecules—ones that can’t currently be solved with existing methods, and we’re exploring how this methodology could be extended to real-world use cases. This opens many new doors in chemistry, and we are excited to see what comes next.