Artistic rendition of a quantum simulation of 1T-TaS2 being performed on the quantum processing unit of a quantum annealer. Credit: Jozef Stefan Institute / Jaka Vodeb und Yevhenii Vaskivskyi, edited

Scientists have utilized a quantum annealer to simulate quantum materials effectively, marking a crucial development in applying quantum computing in material science and enhancing quantum memory device performance.

Physicists have long been pursuing the idea of simulating quantum particles with a computer that is itself made up of quantum particles. This is exactly what scientists at Forschungszentrum Jlich have done together with colleagues from Slovenia. They used a quantum annealer to model a real-life quantum material and showed that the quantum annealer can directly mirror the microscopic interactions of electrons in the material. The result is a significant advancement in the field, showcasing the practical applicability of quantum computing in solving complex material science problems. Furthermore, the researchers discovered factors that can improve the durability and energy efficiency of quantum memory devices.

In the early 1980s, Richard Feynman asked whether it was possible to model nature accurately using a classical computer. His answer was: No. The world consists of fundamental particles, described by the principles of quantum physics. The exponential growth of the variables that must be included in the calculations pushes even the most powerful supercomputers to their limits. Instead, Feynman suggested using a computer that was itself made up of quantum particles. With his vision, Feynman is considered by many to be the Father of the Quantum Computing.

Scientists at Forschungszentrum Jlich, together with colleagues from Slovenian institutions, have now shown that this vision can actually be put into practice. The application they are looking at is a so-called many-body system. Such systems describe the behavior of a large number of particles that interact with each other. In the context of quantum physics, they help to explain phenomena such as superconductivity or quantum phase transitions at absolute zero. At a temperature of 0 Kelvin, instead of thermal fluctuations, only quantum fluctuations occur when a physical parameter like the magnetic field changes.

D-Wave Quantum Annealer JUPSI at Forschungszentrum Jlich. Credit: Forschungszentrum Jlich / Sascha Kreklau

One challenge in researching quantum materials is to quantitatively measure and model the phase transitions of many-body systems, explains Dragan Mihailovi from the Joef Stefan Institute in Slovenia. In this study, the scientists investigated the quantum material 1T-TaS2, which is used in a wide range of applications, including superconducting electronics and energy-efficient storage devices.

Jaka Vodeb from the Jlich Supercomputing Centre describes the approach: We have placed the system in a non-equilibrium state and observed how the electrons in the solid-state lattice rearrange themselves after a non-equilibrium phase transition, both experimentally and through simulations.

All calculations were conducted using the quantum annealer from the company D-Wave, which is integrated into the Jlich Unified Infrastructure for Quantum Computing, JUNIQ.

The researchers could successfully model the crossover from temperature-driven to noisy quantum fluctuation dominated dynamics. Furthermore, the scientists demonstrated that the quantum annealers qubit interconnections can directly mirror the microscopic interactions between electrons in a quantum material. Only one single parameter in the quantum annealer must be modified. The outcome aligns closely with the experimental findings.

However, the research also has practical applications. For instance, a deeper understanding of 1T-TaS2-based memory devices can lead to a practical quantum memory device, implemented directly on a quantum processing unit (QPU). Such devices can contribute to the development of energy-efficient electronic devices, thereby significantly reducing the energy consumption of computing systems.

The research highlights the potential of quantum annealers in solving practical problems, paving the way for their broader application in various fields such as cryptography, material science, and complex system simulations. Moreover, the findings have direct implications for the development of energy-efficient quantum memory devices.

Reference: Non-equilibrium quantum domain reconfiguration dynamics in a two-dimensional electronic crystal and a quantum annealer by Jaka Vodeb, Michele Diego, Yevhenii Vaskivskyi, Leonard Logaric, Yaroslav Gerasimenko, Viktor Kabanov, Benjamin Lipovsek, Marko Topic and Dragan Mihailovic, 6 June 2024, Nature Communications. DOI: 10.1038/s41467-024-49179-z

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In a recent study published in Physical Review Letters, Professor Wei Guo from Florida State Universityprovided valuable insights into the quantum states of electrons on qubits.

Quantum computers have the potential to revolutionize technology by performing calculations that would take classical computers many years to complete.

To build an effective quantum computer, a reliable quantum bit, or qubit, is essential. A qubit must be able to exist simultaneously in both the 0 and 1 states for a sufficiently long period, known as its coherence time.

One promising approach involves trapping a single electron on a solid neon surface, creating what is known as an electron-on-solid-neon qubit.

Guos team discovered that small bumps on the surface of solid neon can naturally bind electrons, forming ring-shaped quantum states. These quantum states describe various properties of an electron, such as position, momentum, and other characteristics before measurement. When these bumps are of a certain size, the electrons transition energythe energy required for an electron to move from one quantum ring state to anotheraligns with the energy of microwave photons, another type of elementary particle.

This alignment allows for the controlled manipulation of electrons, which is crucial for quantum computing.

This work significantly advances our understanding of the electron-trapping mechanism on a promising quantum computing platform, it not only clarifies puzzling experimental observations but also delivers crucial insights for the design, optimization, and control of electron-on-solid-neon qubits.

Wei Guo, Professor, Florida State University

Guo and collaborators previously demonstrated the feasibility of a solid-state single-electron qubit platform using electrons trapped on solid neon. Recent research has revealed coherence times of up to 0.1 milliseconds100 times longer than the typical 1 microsecond coherence time for conventional semiconductor-based and superconductor-based charge qubits.

The extended coherence time of the electron-on-solid-neon qubit is attributed to the inertness and purity of solid neon. This system also addresses the issue of liquid surface vibrations, a problem inherent in the more extensively studied electron-on-liquid-helium qubit. The current research provides crucial insights into further optimizing the electron-on-solid-neon qubit.

A key aspect of this optimization involves creating qubits that are smooth across most of the solid neon surface while having bumps of the right size where needed. Designers aim to minimize naturally occurring surface bumps that attract disruptive background electrical charge. Simultaneously, intentionally fabricating bumps of the correct size within the microwave resonator on the qubit enhances its ability to trap electrons effectively.

This research underscores the critical need for further study of how different conditions affect neon qubit manufacturing, Neon injection temperatures, and pressure influence the final qubit product. The more control we have over this process, the more precise we can build, and the closer we move to quantum computing that can solve currently unmanageable calculations.

Wei Guo, Professor, Florida State University

Toshiaki Kanai, a Graduate Research Student in the FSU Department of Physics, and Dafei Jin, an Associate Professor at the University of Notre Dame are the Co-authors of the study.

The National Science Foundation, the Gordon and Betty Moore Foundation, and the Air Force Office of Scientific Research supported the research.

Kanai, T., et al. (2024) Single-Electron Qubits Based on Quantum Ring States on Solid Neon Surface. Physical Review Letters. doi.org/10.1103/PhysRevLett.132.250603.

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What do underwater navigation, drug safety, and air traffic control have in common? Each creates challenges that quantum science and technology could solve.

In Connecticut, the unique public-private partnership QuantumCT is accelerating research to meet those challenges head onand to position Connecticut as a global quantum technology hub.

As of this spring, nine Connecticut-based research groups have received one-year seed grants for exploratory quantum projects. Each project aims to tackle a challenge problem issued by corporate partners in the state, like the need to develop algorithms that simulate molecular drug actions in the body, or to invent exquisitely accurate but hardy sensors that work in extreme environments with little power.

In other words, the projects are directly relevant to Connecticut industries, including aerospace, biotech, and life sciences. This practical approach to science is called use-inspired research.

These grants are fertilizing creative, potentially transformative projects in quantum science and technology across several key industries, all of which are central to Connecticuts present and future economy, says Michael Crair, Vice Provost for Research and William Ziegler III Professor of Neuroscience and Professor of Ophthalmology and Visual Science at Yale University.

The seed grants are funded by the University of Connecticut and Yale University and distributed via QuantumCT. Research results will help QuantumCT plan long-term research eligible for competitive funding through the National Science Foundations Regional Innovation Engines (a program established through the 2022 CHIPS and Science Act).

The aim of QuantumCT is to make Connecticut a global destination for quantum education, job training and equitable job growth, research innovation, and industry excellence.

Because large universities and industry in Connecticut have joined forces, sharing resources and expertise under the QuantumCT umbrella, we are realizing a faster pace of quantum innovationand advancing our states role as a leader in quantum science and technology, says Pamir Alpay, Vice President for Research, Innovation, and Entrepreneurship and Board of Trustees Distinguished Professor of Materials Science and Engineering at the University of Connecticut. The seed grants will fuel not only quantum discovery but also career opportunities in a high-demand STEM field.

Each project is collaborative, bringing together researchers from UConn, Yale, and industry partners.

The projects foster interactions among a range of researchers from faculty to students to industry scientists, allowing them to pool their knowledge and creativity at top-of-the-line laboratory facilities in Connecticut, Alpay notes. These collaborations also offer rising quantum scientists a look at potential career paths in industry.

Advanced sensing

Airplanes, ships, and other vehicles rely on sensors for accurate navigation. But current sensor technologies have important limitations, and five of the project teams are working to develop better ones.

In one, led by Charles Ahn and Alexander Balatskyphysics professors at Yale and UConn, respectivelythe aim is to develop a robust, highly sensitive radiofrequency (RF) sensor that outperforms state-of-the-art directional sensors. To do this, the team is studying how electromagnetic waves interact with atom-sized magnets.

We incorporate magnetic atoms on thin films on the nanoscale, says Dung Vu, a Yale postdoctoral associate on the team, which also includes collaborators from RTX Technology Research Center (RTRC), the research arm of RTX and its three businesses Collins Aerospace, Pratt & Whitney, and Raytheon.

By changing properties such as energy and polarization of the light we shine on to the film, we can manipulate the quantum magnets properties, then measure the change of the magnetic field around them when they interact with light, Vu says.

The devices, Vu explains, can be used to make RF sensors that may be useful for airborne and autonomous vehicles.

Another team is developing innovative fiber sensors for a magnetic-aided inertial navigation unit for a global navigation satellite system (GNSS). With its extraordinary sensitivity, this technology is designed to operate in environments like the deep ocean and underground, where GNSS signals can be jammed, spoofed, or otherwise unreliable. Electrical engineers Faquir Jain and John Chandy of UConn and Fengnian Xia of Yale are behind that effort.

The sensor can detect ultra-low magnetic fields that help with navigation with very low power consumption and cost, Jain says.

A key challenge for next-generation magnetic sensors is to limit the devices SWaP (size, weight, and power consumption). Currently, the best ones require supercooled liquid helium. A seed project by assistant professors Yu He of Yale (applied physics) and Pavel Volkov of UConn (engineering) is pursuing sensors cooled with liquid nitrogena much more user-friendly substance.

The results will form one pillar for the eventual theory-experiment-industry collaboration, Volkov says.

Highly accurate sensors are vulnerable to miniscule errors and noise in the data. A team led by Yale engineering professor Hong Tang is building ultra-thin silicon nitride microwheels to create a tough, low-SWaP sensor whose round shape is designed to reduce error.

Meanwhile, Yale associate professor of physics and applied physics Peter Rakich is developing a technique to attach microscopic mirrors to the end of silica fibers, creating a tiny, high-finesse device called a resonator. This resonator should allow precise control of quantum particles, like the ability to couple light particles with ions. That could advance not only sensors, but also quantum computers and networking.

Computing revolutions

With quantum technologies poised to revolutionize computing, many industries stand to benefit.

Quantum entanglement, the eerie phenomenon by which two particles are linked as if they were one, is central to quantum computing and a major reason why the technology is expected to deliver vast improvements. In fact, entanglement can be considered a key resource in quantum computing, and as with any resource, there are better and worse ways of distributing it. Leandros Tassiulas and Shan Zuo, electrical engineering faculty at Yale and UConn, respectively, are studying how quantum computing systems can generate entanglement across multiple users in an equitable way.

Air traffic controllers, delivery route planners, and factory managers are among the many workers who face optimization problems: how to make actions most efficient. But optimization problems can be fiendishly difficult to solve, especially where there are hard constraints like the need for airplanes to avoid no-fly zones, trucks to refuel, or machines to complete tasks in a certain order. Like classical computers, quantum computers can use heuristics to tackle optimization problemswhich remain extremely challenging to solve.

A joint Yale-UConn team led by Yale physics professor Steven Girvin is exploring whether new algorithms could help quantum computers handle hard constraints on optimization problems. The research should also have relevance to problems like portfolio optimization and risk assessment that frequently arise in domains like finance and insurance, supply-chain logistics, and flight route planning, according to Amit Surana, an RTRC researcher working with the team.

The value proposition is that even slight improvements to logistics, even by half a percent, can mean huge savings, Surana says.

Progress in life sciences

Computing is also a focus of two teams led by Yale chemistry faculty members Victor Batista and Tianyu Zhu, which are exploring quantum solutions to problems in drug development.

One complex challenge researchers face is efficiently identifying drugs that will bind tightly to the intended receptor. Zhu and Batista, with partners at UConn, including physics professor Lea Ferreira Dos Santos and representatives of Mirion Technologies and Boehringer Ingelheim, are developing algorithms that run on quantum computers to tackle this task.

Drug safety, too, might be improved by quantum computing. New drugs must be rigorously checked for possible toxic side effects on the heart, liver, and immune system. As part of a de-emphasis on animal testing, the industry has been studying the use of classical computing tools like machine learning and artificial intelligence to evaluate possible side effects. But quantum computing techniques remain relatively unexplored.

So, another group working with Zhu and Batista is developing algorithms that use toxicology data to predict the safety of drug candidates. They are studying a hybrid approach in which a classical computer does a first check for toxicity, then drug candidates that pass that test undergo a further check by a quantum algorithm. Such a hybrid quantum-classical approach is a new and potentially highly effective way to do AI. Project partners include UConn professor Bodhisattva Chaudhuri and researchers with Novartis and Pfizer.

With this method, says Anthony Smaldone, a graduate student in the Batista lab, we can remove drugs that are highly likely to fail in testing. Then we dont have to rely on animal testing so heavily.

The hybrid method allows for tinkering that should help researchers determine where quantum computers offer efficiency gains, Smaldone explains.

We can slowly change our hybrid models, taking out classical components and putting quantum components in, and see what works and what doesnt, he says. Hopefully, as were putting in these quantum components, we can start to see quantum advantages in doing so.

Currently, Smaldone says, the team is working with simulations only. Real-world success will have to wait for certain types of hardware and algorithms to catch up. But this shows the first theoretical framework to do this efficiently, he says.

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The quantum computer race has been hot for a few years now, with drug discovery, materials science, optimization, machine learning, and cryptography being just a few of the areas that will be revolutionized by its advancements. But despite all the progress, building quantum computers that solve real-world problems has been held back by three big challenges:

Now, a team at Chalmers University of Technology in Sweden has taken a significant step in addressing these challenges and accelerating the development of practical quantum computers. They recently published a new method in the journal Nature for manipulating quantum information using tunable nonlinearity in superconducting circuits. This allows for complex operations on multi-dimensional quantum states to be performed faster and more accurately than ever before.

At the heart of quantum computing is the quantum bit, or qubit, the fundamental unit of quantum information. Unlike classical bits, which are either 0 or 1, qubits can be both 0 and 1 and everything in between. Qubits can also be entangled with each other, allowing quantum computers to perform some calculations much faster than classical computers.

However, reaching this capability has been a significant challenge. One of the biggest issues is the fragility of quantum states. Qubits are sensitive to their environment and quickly lose their quantum properties through decoherence, introducing errors into the quantum computation and limiting the depth of computations.

Another major problem is scaling. As more qubits are added to a quantum processor, it becomes harder to control the interactions between them and to implement the quantum gates. This is because the control systems and cross-talk between qubits become more complex.

And theres a trade-off between coherence and controllability. Techniques that make qubits more coherent, like error correction codes, require more resources and limit some operations. Systems that have more control over individual qubits, like trapped ions or superconducting circuits, are noisier and more prone to decoherence.

Think of a qubit as a blue lamp that, quantum mechanically, can be both switched on and off simultaneously. In contrast, a continuous variable quantum system is like an infinite rainbow, offering a seamless gradient of colors. This illustrates its ability to access a vast number of states, providing far richer possibilities than the qubit's two states.

Axel Eriksson, researcher in quantum technology at Chalmers University of Technology and lead author of the study

Click here to learn about the current state of quantum computing.

The Chalmers University team, led by Drs. Axel M. Eriksson and Simone Gasparinetti have solved these problems by using superconducting circuits. Theyve developed a special component called a Superconducting Nonlinear Asymmetric Inductive eLement (SNAIL) resonator.

SNAILs are superconducting circuit elements with strong, tunable nonlinearity. Its a superconducting loop with Josephson junctions, thin insulating barriers that allow Cooper pairs (bound pairs of electrons) to tunnel through. By arranging the junctions asymmetrically, theyve made a circuit element with nonlinear inductance.

We have made a system that does complex operations on a multi-state quantum system faster than ever before.

Senior author Dr. Simone Gasparinetti, leader of the 202Q-lab at Chalmers University

The key thing the Chalmers team did was to put a SNAIL resonator inside a superconducting microwave cavity, which is a bosonic mode for encoding quantum information. They applied microwave pulses to this hybrid system and activated and deactivated the nonlinearity in the SNAIL to perform all sorts of quantum operations fast and accurately.

One of the unique things about the Chalmers teams approach is that it goes beyond the qubit paradigm and uses continuous-variable (CV) quantum states. In a CV quantum system, information is encoded in the amplitude and phase quadratures of a harmonic oscillator, like a microwave cavity field. Those quadratures can take on a continuous range of values, not just 0 and 1 like qubits. According to senior author Dr. Simone Gasparinetti, leader of the 202Q-lab at Chalmers University:

We have created a system that enables extremely complex operations on a multi-state quantum system, at an unprecedented speed.

The CV approach has advantages over discrete-variable quantum computing. (i) One, a single CV mode can encode multiple qubits worth of information, which means less hardware for fault-tolerant quantum computing. (ii) Two, the consciousness of CV states allows for better error correction codes, which are needed for quantum computing with noise and decoherence.

However, a big problem in CV quantum computing is non-Gaussian operations, which are needed for universal quantum computing. Gaussian operations like displacement and squeezing of the oscillator state can be done with linear optical elements or microwave circuits, but thats not enough for quantum speedup because it can be classically simulated.

Non-Gaussian operations require nonlinear interactions, which are much harder to make and control. Previous attempts to combine CV modes with nonlinear elements have been foiled by the Kerr effect, which messes up the quantum information and reduces the operation fidelity.

The Chalmers team has solved this by engineering the nonlinearity inside the SNAIL resonator. They operate the SNAIL at a so-called Kerr-free point, where the unwanted Kerr nonlinearity is suppressed, and the third-order nonlinearity thats needed for non-Gaussian operations is preserved.

Our community has often tried to keep superconducting elements away from quantum oscillators, not to scramble the fragile quantum states. In this work, we have challenged this paradigm. By embedding a controlling device at the heart of the oscillator we were able to avoid scrambling the many quantum states while at the same time being able to control and manipulate them. As a result, we demonstrated a novel set of gate operations performed at very high speed.

Simone Gasparinetti

To show what they can do, theyve made a universal gate set on their SNAIL-resonator platform. That includes Gaussian gates like displacement and squeezing and a cubic phase gate, which is non-Gaussian.

The Gaussian gates were made by applying microwave pulses at specific frequencies to the SNAIL circuit. Driving at the fundamental frequency gives displacement, and driving at twice the fundamental frequency gives squeezing. Thats for preparing and manipulating coherent and squeezed states, which are the blocks for CV quantum information processing.

The cubic phase gate was made by combining a trisqueezing interaction (driving at three times the fundamental frequency) with drives at lower frequencies. That applies a nonlinear phase shift to the oscillator state thats proportional to the cube of the amplitude, hence the name cubic phase.

The cubic phase gate is needed for universal CV quantum computing because it makes highly non-classical states like Gottesman-Kitaev-Preskill (GKP) states, which are for fault-tolerant quantum error correction. The cubic phase gate with Gaussian gates makes a deterministic non-Gaussian state called the cubic phase state.

The gates made by the Chalmers team were made with pulses as short as tens of nanoseconds. Thats 10-100 times faster than previous implementations with dispersive qubit-oscillator couplings. Thats because of the strong nonlinearity in the SNAIL resonator.

Another example is the Chalmers team using their universal gate set to make a highly non-classical quantum state called a cubic phase state. Cubic phase states are needed for quantum error correction, quantum metrology, and CV measurement-based quantum computing.

Cubic phase state preparation was made by applying gates to the ground state (vacuum) of the SNAIL resonator. First, a 20-ns squeezing gate was applied to make a squeezed vacuum state. Then, a 40-ns cubic phase gate was applied to that squeezed state, and voil, a cubic phase state with a cubicity of 0.11.

The state was characterized with Wigner tomography, which makes a phase-space distribution of the quantum state. The Wigner function was strongly negative, which is non-classical and cannot be seen in any classical oscillator state.

The fidelity of the cubic phase state with respect to the target state was 92%. They showed that the cubicity of the state can be increased by just extending the cubic phase gate duration. Thats much better than previous state preparation methods, which required a full re-optimization of the control sequence for each cubicity value.

While what the Chalmers team has done is already commendable, theres still more to be done:

One limitation of the quantum operations is the coherence time of the SNAIL resonator. They have coherence times of a few microseconds, which is enough for now, but longer coherence times will allow for more complex and deeper quantum circuits. Optimizing the SNAIL circuit parameters to reduce flux noise and shielding and filtering the microwave environment are ways to improve coherence.

This includes:

Click here to learn how quantum emitters and infrared lasers can help us build the next generation of quantum computers.

Another area to improve is scalability. The experiment was done with one SNAIL, but a large-scale quantum computer needs multiple SNAILs. To scale up, one could use multiple SNAILs, each connected to its own microwave cavity. This setup allows for the creation of multi-qubit gates and entangled states by designing the coupling between the cavities. However, that requires control over the fabrication and tuning of the SNAILs to be homogeneous and reproducible.

Besides scaling up the number of CV modes, we also need to scale up the number of photons in each mode. The SNAIL resonator's nonlinearity deviates from its ideal behavior at higher photon numbers, which limits the size of the computational Hilbert space.

One way to fix that is to use a multi-SNAIL design in which the nonlinearity of each SNAIL is engineered to cancel out at higher orders while preserving the lower-order interactions.

Other plausible advancements include:

Looking ahead, the Chalmers team wants to integrate their SNAIL-resonator platform with other quantum computing architectures to make hybrid systems. For example, SNAIL-mediated interactions can be used to entangle superconducting qubits and CV modes to make complex multi-qubit states. The fast and efficient CV gates in this work can be used for quantum error correction on encoded qubits, and that will make more robust and scalable quantum processors.

One exciting prospect to look forward to is integrating the SNAIL-resonator platform with optical quantum systems. Superconducting circuits are good for quantum computing, which operate at microwave frequencies and cryogenic temperatures, are good for quantum computing. In contrast, optical quantum systems, which function at room temperature, are ideal for long-distance quantum communication. By developing a quantum frequency converter, we can combine the best of both worlds to create a scalable and networked quantum computer.

What the Chalmers team has achieved is a major advancement for practical quantum computers. Theyve used tunable nonlinearity in superconducting circuits to develop a hardware-efficient and controllable quantum computer capable of rapidly and accurately performing complex operations on multidimensional quantum states.

This represents a new paradigm in CV-NISQ computing. SNAIL resonators can solve hard problems in quantum chemistry, optimization, and machine learning. As this technology matures and scales, it will open up applications that are not possible with classical computers.

However, building large-scale, fault-tolerant quantum computers still presents substantial challenges, including the coherence time of superconducting circuits, the number of qubits and CV modes, and interfaces between quantum computing platforms.

Despite these challenges, quantum computing as an applied science has come a long way, and the Chalmers team has played an instrumental role in pushing its barriers. Theyve added to the quantum computing toolbox and shown us new ways to use quantum mechanics. Now, were one step closer to accessible quantum computing.

As theory and experiments move faster, the future of quantum computing has never looked better. Quantum computers will deliver exponential speedups for a wide range of computational tasks in fields such as drug discovery, materials design, cryptography, and artificial intelligence. Coupled with advances in technologies like AI, these developments assure us that the world is on the brink of transformative changes that are hard to fully envision.

Click here for a list of the five best quantum computing companies.

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