The research team behind Quantinuum's state-of-the-art quantum computational chemistry platform, InQuanto, has demonstrated a new method that makes more efficient use of today's "noisy" quantum computers, for simulating chemical systems.
In a new paper, “Variational Phase Estimation with Variational Fast Forwarding”, published on the arXiv, a team led by Nathan Fitzpatrick and co-authors Maria-Andreea Filip and David Muñoz Ramo, explored different methods and the trade-offs required to achieve results on near-term quantum hardware. The paper also assesses the hardware requirements for the proposed method.
Starting with the recently published Variational Quantum Phase Estimation (VQPE) algorithm, commonly used to calculate molecular ground-state and excited state energies, the team combined it with variational fast-forwarding (VFF) to reduce the quantum circuit depth required to achieve good results.
The demonstration made use of a Krylov subspace diagonalization algorithm, which can be used as a low-cost alternative to the traditional quantum phase estimation algorithm to estimate both the ground and excited-state energies of a quantum many-body system. The Krylov method uses time evolution to generate the subspace used in the algorithm, which can be very expensive in terms of gate depth. The new method demonstrated is less expensive, making the circuit depth required to achieve good results manageable.
The team decreased the circuit depth by using VFF, a hybrid classical-quantum algorithm, which provides an approximation to time-evolution, allowing VQPE to be applied with linear cost in the number of time-evolved states. Introducing VFF allows the time evolved states to be expressed with a lower fixed depth therefore the quantum computing resources required to run the algorithm are drastically decreased.
This new approach resulted in a circuit with a depth of 57 gates for the H2 Molecule, of which 24 are CNOTs. This is a significant improvement from the original trotterized time-evolution implementation, particularly as the depth of this circuit remains constant for any number of steps. Whereas, the original trotterized circuit required 34 CNOTs per step, with a large number of steps required for high accuracy.
The techniques demonstrated in this paper will be of interest to quantum chemists seeking near-term results in fields such as, excited state quantum chemistry and strongly correlated materials.
The tradeoff involved in this use of VFF is that the results are more approximate. Improving this will be an area for future research.
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.
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:
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.
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:
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.
Quantum randomness is already being deployed commercially:
Recognizing the value of QRNGs, the financial services sector is accelerating its path to commercialization.
On the basis of the latter achievement, we aim to broaden our cybersecurity portfolio with the addition of a certified randomness product in 2025.
The National Institute of Standards and Technology (NIST) defines the cryptographic regulations used in the U.S. and other countries.
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.
This means Quantum Origin is now available for high-security cryptographic systems and integrates seamlessly with NIST-approved solutions without requiring recertification.
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.
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”.
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.