Quantinuum introduces hybrid solver for industrially relevant chemical modeling
New solution could have significant impacts for the automotive, aerospace, semiconductor and oil and gas industries
It’s believed that quantum computing will transform the way we solve chemistry problems, and the Quantinuum scientific team continues to push the envelope towards making that a reality.
In their latest research paper published on the arXiv, Quantinuum scientists describe a new hybrid classical-quantum solver for chemistry. The method they developed can model complex molecules at a new level of efficiency and precision.
Dr. Michał Krompiec, Scientific Project Manager, and his colleague Dr. David Muñoz Ramo, Head of Quantum Chemistry, co-authored the paper, "Strongly Contracted N-Electron Valence State Perturbation Theory Using Reduced Density Matrices from a Quantum Computer".
The implications are significant as their innovation “tackles one of the biggest bottlenecks in modelling molecules on quantum computers,” according to Dr. Krompiec.
Quantum computers are a natural platform to solve chemistry problems. Chemical molecules are made of many interacting electrons, and quantum mechanics can describe the behavior and energies of these electrons.
As Dr. Krompiec explains, “nature is not classical, it is quantum. We want to map the quantum system of interacting electrons into a quantum system of interacting qubits, and then solve it.”
Solving the full picture of electron interactions is extremely difficult, but fortunately it is not always necessary. Scientists usually simplify the task by focusing on the active space of the molecule, a smaller subset of the problem which matters most.
Even with these simplifications, difficulties remain. One challenge is carefully choosing this smaller subset, which describes strongly correlated electrons and is therefore more complex. Another challenge is accurately solving the rest of the system. Solving the chemistry of the complex subset can often be done from perturbation theory using so-called “multi-reference” methods.
In their work, the Quantinuum team came up with a new multi-reference technique. They maintain that only the strongly correlated part of the molecule should be calculated on a quantum computer. This is important, as this part usually scales exponentially with the size of the molecule, making it classically intractable.
The quantum algorithm they used on this part relied on measuring reduced density matrices and feeding them into a multi-reference perturbation theory calculation, a combination that had never been used in this context. Implementing the quantum electronic structure solver on the active space and using measured reduced density matrices makes the problem less computationally expensive and the solution more accurate.
The team tested their workflow on two molecules - H2 and Li2 – using Quantinuum’s hybrid solver implemented in the InQuanto quantum computational chemistry platform and IBM’s 27-qubit device. Quantinuum software is platform inclusive and is often tested on both its own H Series ion-trap quantum systems as well as others.
The non-strongly correlated regions of the molecules were run classically, as they would not benefit from a quantum speedup. The team’s results showed excellent agreement with previous models, meaning their method worked. Beyond that, the method showed great promise for reaching new levels of speed and accuracy for larger molecules.
The future impact of this work could create a new paradigm to perform quantum chemistry. The authors of the paper believe it may represent the best way of computing dynamic correlation corrections to active space-type quantum methods.
As Dr. Krompiec said, “Quantum chemistry can finally be solved with an application of a quantum solver. This can remove the factorial scaling which limits the applicability of this rigorous method to a very small subsystem.”
The idea to use a multi-reference method along with reduced density matrix measurement is quite novel and stems from the diverse backgrounds of the team at Quantinuum. It is a unique application of well-known quantum algorithms to a set of theoretical quantum chemistry problems.
What’s Next
The use cases are vast. Analysis of catalyst and material properties may first benefit from this new method, which will have a tremendous impact in the automotive, aerospace, fine chemicals, semiconductor, and energy industries.
Implementing this method on real hardware is limited by the current noise levels. But as the quality of the qubits increases, the method will unleash its full potential. Quantinuum’s System Model H1 trapped-ion hardware, Powered by Honeywell, benefits from high fidelity qubits, and will be a valuable resource for quantum chemists wishing to follow this work.
This hybrid quantum-classical method promises a path to quantum advantage for important chemistry problems, as machines become more powerful.
As Dr. Krompiec summarizes, “we haven’t just created a toy model that works for near-term devices. This is a fundamental method that will still be relevant as quantum computers continue to mature.”
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.
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 Quantinuum Systems.
Today, a paper published in Physical Review Research marks the first of many breakthroughs coming from this international supercomputing partnership. The team from RIKEN and Quantinuum 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 here, and read more about our partnership with RIKEN here.
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 report 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:
- Financial services
- Information and communication technology
- Chemicals and advanced materials
- Energy and utilities
- Pharmaceuticals and healthcare
In line with these trends, recent research 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 pilot 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 NIST SP 800-90B Entropy Source validation, 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.
Quantinuum delivers the highest quality quantum randomness, enabling our customers to confront the most advanced cybersecurity challenges present today.
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 announced 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 paper 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 Quantinuum’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, “it is impossible to represent the results of quantum mechanics with a classical universal device.” 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.