ҹɫֱ

Protecting Expressive Circuits with a Quantum Error Detection Code

ҹɫֱ has optimized the “iceberg” error detection code, opening the door to early fault-tolerant quantum computing

January 8, 2024

Detecting and correcting errors has become a critical area of development in quantum computing, a key that will unlock results which put quantum computers in a different league from their classical counterparts. 

Researchers are working on ways to handle errors so that the hardware we will have in the coming months will be capable of performing useful tasks that are intractable for any classical computer — in other words, to achieve “quantum advantage”. 

The full monty, known as “large-scale fault-tolerant quantum error correction” remains an open challenge in the quantum computing landscape, placing incredibly demanding constraints on the hardware. A promising start is to implement error detection instead of full error correction. In this approach, the system regularly checks for errors, and if one is detected, throws out the computation and restarts. 

The team at ҹɫֱ realized that just such a code, nicknamed the “iceberg code”, if optimized to take advantage of the industry-leading components in ҹɫֱ’s trapped-ion quantum computers, could offer real potential for early fault-tolerance. ҹɫֱ’s H-Series hardware boasts mobile qubits, mid circuit measurement and the ability to program circuits with arbitrary-angle gates – making it ripe for new algorithm implementation and development. The team’s results, published today in Nature Physics , detail a code that’s so efficient it was able to protect much deeper and more expressive circuits than had previously been realized with quantum error correction, and it did so making extremely efficient use of the very high-fidelity qubits and gates available in ҹɫֱ’s quantum charge-coupled device (QCCD) architecture. 

“Our work sets the bar for what more advanced fully fault-tolerant codes need to beat on hardware,” said David Amaro, an author on the paper.

A key advantage of the iceberg code is how efficiently it squeezes out the maximum number of logical qubits from the given set of physical qubits – it can make k logical qubits out of only k+2 physical qubits. Every logical gate is implemented by a unique two-qubit physical gate, making it a very fast, clean, and expressive implementation. In addition to this, it needs only 2 more ancilla qubits for syndrome measurement, making for a very small overhead of only 4 physical qubits. Using the original 12-qubit configuration of ҹɫֱ’s H1-2 computer (since increased to 20), this meant the team could realize 8 logical qubits.

With these 8 logical qubits, the team implemented much deeper and more expressive circuits than had previously been demonstrated with quantum error correction codes. 

The team’s work is the first experimental demonstration that sophisticated quantum error detection techniques are useful to successfully protect very expressive circuits on a real quantum computer. In contrast, previous demonstrations of fully fault-tolerant codes on hardware showed protection only of basic logical gates or “primitives” (the building blocks of full algorithms). 

The Iceberg code is a method that’s useful today for practitioners, and can be used to protect near-term algorithms like the ‘quantum approximate optimization algorithm’, or the ‘variational quantum eigensolver’, algorithms currently put to work in domains including chemical simulation, quantum machine learning and financial optimization. In fact, it was used by a team at ҹɫֱ to protect the , a critical piece for many other quantum algorithms, and deployed in a state-of-the-art simulation of a real-world hydrogen molecule using logically-encoded qubits — a feat not possible using any other quantum computing hardware yet developed.

Looking forwards, the team plans to push the code as far as possible to determine if it is sufficient to protect quantum circuits capable of a quantum advantage. This will require setting a “minimal” quantum advantage experiment, working on careful engineering and benchmarking of every aspect of the code, and the use of ҹɫֱ’s best-in-class high fidelity gates. In parallel, they will also be working to understand if and how the Iceberg code can contribute to minimize the resource overhead of some of the most promising fully fault-tolerant codes.

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. 

Blog
April 11, 2025
ҹɫֱ’s partnership with RIKEN bears fruit

Last year, we joined forces with RIKEN, Japan's largest comprehensive research institution, to install our hardware at RIKEN’s campus in Wako, Saitama. This deployment is part of RIKEN’s project to build a quantum-HPC hybrid platform consisting of high-performance computing systems, such as the supercomputer Fugaku and ҹɫֱ Systems.  

Today, marks the first of many breakthroughs coming from this international supercomputing partnership. The team from RIKEN and ҹɫֱ joined up with researchers from Keio University to show that quantum information can be delocalized (scrambled) using a quantum circuit modeled after periodically driven systems.  

"Scrambling" of quantum information happens in many quantum systems, from those found in complex materials to black holes.  Understanding information scrambling will help researchers better understand things like thermalization and chaos, both of which have wide reaching implications.

To visualize scrambling, imagine a set of particles (say bits in a memory), where one particle holds specific information that you want to know. As time marches on, the quantum information will spread out across the other bits, making it harder and harder to recover the original information from local (few-bit) measurements.

While many classical techniques exist for studying complex scrambling dynamics, quantum computing has been known as a promising tool for these types of studies, due to its inherently quantum nature and ease with implementing quantum elements like entanglement. The joint team proved that to be true with their latest result, which shows that not only can scrambling states be generated on a quantum computer, but that they behave as expected and are ripe for further study.

Thanks to this new understanding, we now know that the preparation, verification, and application of a scrambling state, a key quantum information state, can be consistently realized using currently available quantum computers. Read the paper , and read more about our partnership with RIKEN here.  

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Blog
April 4, 2025
Why is everyone suddenly talking about random numbers? We explain.

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 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:

  1. Financial services
  2. Information and communication technology
  3. Chemicals and advanced materials
  4. Energy and utilities
  5. Pharmaceuticals and healthcare

In line with these trends, recent 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 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 , 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.

ҹɫֱ delivers the highest quality quantum randomness, enabling our customers to confront the most advanced cybersecurity challenges present today.

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Blog
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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