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Quantum Computing Advance Begins New Era, IBM Says

A quantum computer came up with better answers to a physics problem than a conventional supercomputer.

A model of the interior of a quantum computer at the IBM Thomas J. Watson Research Center in Yorktown Heights, N.Y. Credit... James Estrin/The New York Times

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By Kenneth Chang

• Published June 14, 2023 Updated June 19, 2023

Quantum computers today are small in computational scope — the chip inside your smartphone contains billions of transistors while the most powerful quantum computer contains a few hundred of the quantum equivalent of a transistor. They are also unreliable. If you run the same calculation over and over, they will most likely churn out different answers each time.

But with their intrinsic ability to consider many possibilities at once, quantum computers do not have to be very large to tackle certain prickly problems of computation, and on Wednesday, IBM researchers announced that they had devised a method to manage the unreliability in a way that would lead to reliable, useful answers.

“What IBM showed here is really an amazingly important step in that direction of making progress towards serious quantum algorithmic design,” said Dorit Aharonov, a professor of computer science at the Hebrew University of Jerusalem who was not involved with the research.

While researchers at Google in 2019 claimed that they had achieved “quantum supremacy” — a task performed much more quickly on a quantum computer than a conventional one — IBM’s researchers say they have achieved something new and more useful, albeit more modestly named.

“We’re entering this phase of quantum computing that I call utility,” said Jay Gambetta, a vice president of IBM Quantum. “The era of utility.”

A team of IBM scientists who work for Dr. Gambetta described their results in a paper published on Wednesday in the journal Nature .

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IBM Quantum Computer Demonstrates Next Step Towards Moving Beyond Classical Supercomputing

ARMONK, N.Y. , June 14, 2023 / PRNewswire / -- IBM (NYSE: IBM ) today announced a new breakthrough, published on the cover of the scientific journal  Nature , demonstrating for the first time that quantum computers can produce accurate results at a scale of 100+ qubits reaching beyond leading classical approaches.

One of the ultimate goals of quantum computing is to simulate components of materials that classical computers have never efficiently simulated. Being able to model these is a crucial step towards the ability to tackle challenges such as designing more efficient fertilizers, building better batteries, and creating new medicines. But today's quantum systems are inherently noisy and they produce a significant number of errors that hamper performance. This is due to the fragile nature of quantum bits or qubits and disturbances from their environment.

In their experiment, the IBM team demonstrates that it is possible for a quantum computer to outperform leading classical simulations by learning and mitigating errors in the system. The team used the IBM Quantum 'Eagle' quantum processor composed of 127 superconducting qubits on a chip to generate large, entangled states that simulate the dynamics of spins in a model of material and accurately predict properties such as its magnetization.

To verify the accuracy of this modeling, a team of scientists at UC Berkeley simultaneously performed these simulations on advanced classical computers located at Lawrence Berkeley National Lab's National Energy Research Scientific Computing Center (NERSC) and Purdue University . As the scale of the model increased, the quantum computer continued to turn out accurate results with the help of advanced error mitigation techniques, even while the classical computing methods eventually faltered and did not match the IBM Quantum system.

"This is the first time we have seen quantum computers accurately model a physical system in nature beyond leading classical approaches," said Darío Gil, Senior Vice President and Director of IBM Research. "To us, this milestone is a significant step in proving that today's quantum computers are capable, scientific tools that can be used to model problems that are extremely difficult – and perhaps impossible – for classical systems, signaling that we are now entering a new era of utility for quantum computing."

To learn more about the details of the demonstration and the results, read the IBM Research blog .

IBM Commits to Utility-Scale Processors Across IBM Quantum Systems

Following this groundbreaking work, IBM is also announcing that its IBM Quantum systems running both on the cloud and on-site at partner locations will be powered by a minimum of 127 qubits, to be completed over the course of the next year.

These processors provide access to computational power large enough to surpass classical methods for certain applications and will offer improved coherence times as well as lower error rates over previous IBM quantum systems. Such capabilities can be combined with continuously advancing error mitigation techniques to enable IBM Quantum systems to meet a new threshold for the industry, which IBM has termed 'utility-scale,' a point at which quantum computers could serve as scientific tools to explore a new scale of problems that classical systems may never be able to solve.

"As we progress our mission to bring useful quantum computing to the world, we have solid evidence of the cornerstones needed to explore an entirely new class of computational problems," said Jay Gambetta , IBM Fellow and Vice President, IBM Quantum. "By equipping our IBM Quantum systems with processors capable of utility scale, we are inviting our clients, partners and collaborators to bring their hardest problems to explore the limits of today's quantum systems and to begin extracting real value."

All IBM Quantum users will be able to run problems on utility-scale processors larger than 100 qubits. The over 2,000 participants in the IBM Quantum Spring Challenge had access to these utility-scale processors as they explored dynamic circuits, a technology that makes it easier to run more-advanced quantum algorithms.

Global Researchers and Industry Leaders Pursue Value with IBM Quantum

As IBM expands its quantum technology stack, research institutions and private-sector leaders are mobilizing across industries for which quantum holds immediate potential. Equipped with more powerful quantum technology, including advanced hardware and tools to explore how error mitigation can enable accuracy today, pioneering organizations and universities are working with IBM to advance the value of quantum computing.

These working groups that are exploring the potential value quantum computing offers include:

• Healthcare and Life Sciences: led by organizations such as Cleveland Clinic and Moderna, are exploring applications of quantum chemistry and quantum machine learning to challenges such as accelerated molecular discovery and patient risk prediction models.
• High Energy Physics: comprised of groundbreaking research institutions such as CERN and DESY , are working to identify the best suited quantum calculations, for areas such as identification and reconstruction algorithms for particle collision events, and the investigation of theoretical models for high energy physics.
• Materials:  spearheaded by the teams at Boeing , Bosch , The University of Chicago , Oak Ridge National Lab , ExxonMobil and RIKEN , aim to explore the best methods to build workflows for materials simulation.
• Optimization:  aimed at establishing collaboration across global institutions such as  E.ON, Wells Fargo  and others to explore key questions that progress the identification of optimization problems best suited for quantum advantage in sustainability and finance.

IBM is a leading provider of global hybrid cloud and AI, and consulting expertise. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. More than 4,000 government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM's hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM's breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and consulting deliver open and flexible options to our clients. All of this is backed by IBM's legendary commitment to trust, transparency, responsibility, inclusivity and service.

Visit www.ibm.com for more information.

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There is a huge global effort to engineer a computer capable of harnessing the power of quantum physics to carry out computations of unprecedented complexity. While formidable technological obstacles still stand in the way of creating such a quantum computer, today’s early prototypes are still capable of remarkable feats.

The Google Sycamore chip used in the creation of a time crystal. (Image credit: Google Quantum AI)

For example, the creation of a new phase of matter called a “time crystal.” Just as a crystal’s structure repeats in space, a time crystal repeats in time and, importantly, does so infinitely and without any further input of energy – like a clock that runs forever without any batteries. The quest to realize this phase of matter has been a longstanding challenge in theory and experiment – one that has now finally come to fruition.

In research published Nov. 30 in Nature , a team of scientists from Stanford University, Google Quantum AI, the Max Planck Institute for Physics of Complex Systems and Oxford University detail their creation of a time crystal using Google’s Sycamore quantum computing hardware.

“The big picture is that we are taking the devices that are meant to be the quantum computers of the future and thinking of them as complex quantum systems in their own right,” said Matteo Ippoliti, a postdoctoral scholar at Stanford and co-lead author of the work. “Instead of computation, we’re putting the computer to work as a new experimental platform to realize and detect new phases of matter.”

For the team, the excitement of their achievement lies not only in creating a new phase of matter but in opening up opportunities to explore new regimes in their field of condensed matter physics, which studies the novel phenomena and properties brought about by the collective interactions of many objects in a system. (Such interactions can be far richer than the properties of the individual objects.)

“Time-crystals are a striking example of a new type of non-equilibrium quantum phase of matter,” said Vedika Khemani , assistant professor of physics at Stanford and a senior author of the paper. “While much of our understanding of condensed matter physics is based on equilibrium systems, these new quantum devices are providing us a fascinating window into new non-equilibrium regimes in many-body physics.”

What a time crystal is and isn’t

The basic ingredients to make this time crystal are as follows: The physics equivalent of a fruit fly and something to give it a kick. The fruit fly of physics is the Ising model, a longstanding tool for understanding various physical phenomena – including phase transitions and magnetism – which consists of a lattice where each site is occupied by a particle that can be in two states, represented as a spin up or down.

During her graduate school years, Khemani, her doctoral advisor Shivaji Sondhi, then at Princeton University, and Achilleas Lazarides and Roderich Moessner at the Max Planck Institute for Physics of Complex Systems stumbled upon this recipe for making time crystals unintentionally. They were studying non-equilibrium many-body localized systems – systems where the particles get “stuck” in the state in which they started and can never relax to an equilibrium state. They were interested in exploring phases that might develop in such systems when they are periodically “kicked” by a laser. Not only did they manage to find stable non-equilibrium phases, they found one where the spins of the particles flipped between patterns that repeat in time forever, at a period twice that of the driving period of the laser, thus making a time crystal.

The periodic kick of the laser establishes a specific rhythm to the dynamics. Normally the “dance” of the spins should sync up with this rhythm, but in a time crystal it doesn’t. Instead, the spins flip between two states, completing a cycle only after being kicked by the laser twice . This means that the system’s “time translation symmetry” is broken. Symmetries play a fundamental role in physics, and they are often broken – explaining the origins of regular crystals, magnets and many other phenomena; however, time translation symmetry stands out because unlike other symmetries, it can’t be broken in equilibrium. The periodic kick is a loophole that makes time crystals possible.

The doubling of the oscillation period is unusual, but not unprecedented. And long-lived oscillations are also very common in the quantum dynamics of few-particle systems. What makes a time crystal unique is that it’s a system of millions of things that are showing this kind of concerted behavior without any energy coming in or leaking out.

“It’s a completely robust phase of matter, where you’re not fine-tuning parameters or states but your system is still quantum,” said Sondhi, professor of physics at Oxford and co-author of the paper. “There’s no feed of energy, there’s no drain of energy, and it keeps going forever and it involves many strongly interacting particles.”

While this may sound suspiciously close to a “perpetual motion machine,” a closer look reveals that time crystals don’t break any laws of physics. Entropy – a measure of disorder in the system – remains stationary over time, marginally satisfying the second law of thermodynamics by not decreasing.

Between the development of this plan for a time crystal and the quantum computer experiment that brought it to reality, many experiments by many different teams of researchers achieved various almost-time-crystal milestones. However, providing all the ingredients in the recipe for “many-body localization” (the phenomenon that enables an infinitely stable time crystal) had remained an outstanding challenge.

For Khemani and her collaborators, the final step to time crystal success was working with a team at Google Quantum AI. Together, this group used Google’s Sycamore quantum computing hardware to program 20 “spins” using the quantum version of a classical computer’s bits of information, known as qubits.

Revealing just how intense the interest in time crystals currently is, another time crystal was published in Science this month. That crystal was created using qubits within a diamond by researchers at Delft University of Technology in the Netherlands.

Quantum opportunities

The researchers were able to confirm their claim of a true time crystal thanks to special capabilities of the quantum computer. Although the finite size and coherence time of the (imperfect) quantum device meant that their experiment was limited in size and duration – so that the time crystal oscillations could only be observed for a few hundred cycles rather than indefinitely – the researchers devised various protocols for assessing the stability of their creation. These included running the simulation forward and backward in time and scaling its size.

A view of the Google dilution refrigerator, which houses the Sycamore chip. (Image credit: Google Quantum AI)

“We managed to use the versatility of the quantum computer to help us analyze its own limitations,” said Moessner, co-author of the paper and director at the Max Planck Institute for Physics of Complex Systems. “It essentially told us how to correct for its own errors, so that the fingerprint of ideal time-crystalline behavior could be ascertained from finite time observations.”

A key signature of an ideal time crystal is that it shows indefinite oscillations from all states. Verifying this robustness to choice of states was a key experimental challenge, and the researchers devised a protocol to probe over a million states of their time crystal in just a single run of the machine, requiring mere milliseconds of runtime. This is like viewing a physical crystal from many angles to verify its repetitive structure.

“A unique feature of our quantum processor is its ability to create highly complex quantum states,” said Xiao Mi, a researcher at Google and co-lead author of the paper. “These states allow the phase structures of matter to be effectively verified without needing to investigate the entire computational space – an otherwise intractable task.”

Creating a new phase of matter is unquestionably exciting on a fundamental level. In addition, the fact that these researchers were able to do so points to the increasing usefulness of quantum computers for applications other than computing. “I am optimistic that with more and better qubits, our approach can become a main method in studying non-equilibrium dynamics,” said Pedram Roushan, researcher at Google and senior author of the paper.

“We think that the most exciting use for quantum computers right now is as platforms for fundamental quantum physics,” said Ippoliti. “With the unique capabilities of these systems, there’s hope that you might discover some new phenomenon that you hadn’t predicted.”

This work was led by Stanford University, Google Quantum AI, the Max Planck Institute for Physics of Complex Systems and Oxford University. The full author list is available in the Nature paper.

This research was funded by the Defense Advanced Research Projects Agency (DARPA), a Google Research Award, the Sloan Foundation, the Gordon and Betty Moore Foundation and the Deutsche Forschungsgemeinschaft.

To read all stories about Stanford science, subscribe to the biweekly   Stanford Science Digest .

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What’s next for quantum computing

Companies are moving away from setting qubit records in favor of practical hardware and long-term goals.

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This story is a part of MIT Technology Review’s  What’s Next series , where we look across industries, trends, and technologies to give you a first look at the future

In 2023, progress in quantum computing will be defined less by big hardware announcements than by researchers consolidating years of hard work, getting chips to talk to one another, and shifting away from trying to make do with noise as the field gets ever more international in scope.

For years, quantum computing’s news cycle was dominated by headlines about record-setting systems. Researchers at Google and IBM have had spats over who achieved what—and whether it was worth the effort. But the time for arguing over who’s got the biggest processor seems to have passed: firms are heads-down and preparing for life in the real world. Suddenly, everyone is behaving like grown-ups.

As if to emphasize how much researchers want to get off the hype train, IBM is expected to announce a processor in 2023 that bucks the trend of putting ever more quantum bits, or “qubits,” into play. Qubits, the processing units of quantum computers, can be built from a variety of technologies, including superconducting circuitry, trapped ions, and photons, the quantum particles of light. 

IBM has long pursued superconducting qubits, and over the years the company has been making steady progress in increasing the number it can pack on a chip. In 2021, for example, IBM unveiled one with a record-breaking 127 of them. In November, it debuted  its 433-qubit Osprey processor , and the company aims to release a 1,121-qubit processor called Condor in 2023. 

But this year IBM is also expected to debut its Heron processor, which will have just 133 qubits. It might look like a backwards step, but as the company is keen to point out, Heron’s qubits will be of the highest quality. And, crucially, each chip will be able to connect directly to other Heron processors, heralding a shift from single quantum computing chips toward “modular” quantum computers built from multiple processors connected together—a move that is expected to help quantum computers scale up significantly. 

Heron is a signal of larger shifts in the quantum computing industry. Thanks to some recent breakthroughs, aggressive roadmapping, and high levels of funding, we may see general-purpose quantum computers earlier than many would have anticipated just a few years ago, some experts suggest. “Overall, things are certainly progressing at a rapid pace,” says Michele Mosca, deputy director of the Institute for Quantum Computing at the University of Waterloo. 

Here are a few areas where experts expect to see progress.

Stringing quantum computers together

IBM’s Heron project is just a first step into the world of modular quantum computing. The chips will be connected with conventional electronics, so they will not be able to maintain the “quantumness” of information as it moves from processor to processor. But the hope is that such chips, ultimately linked together with quantum-friendly fiber-optic or microwave connections, will open the path toward distributed, large-scale quantum computers with as many as a million connected qubits. That may be how many are needed to run useful, error-corrected quantum algorithms. “We need technologies that scale both in size and in cost, so modularity is key,” says Jerry Chow, director at IBM Quantum Hardware System Development.

Other companies are beginning similar experiments. “Connecting stuff together is suddenly a big theme,” says Peter Shadbolt, chief scientific officer of PsiQuantum , which uses photons as its qubits. PsiQuantum is putting the finishing touches on a silicon-based modular chip. Shadbolt says the last piece it requires—an extremely fast, low-loss optical switch—will be fully demonstrated by the end of 2023. “That gives us a feature-complete chip,” he says. Then warehouse-scale construction can begin: “We’ll take all of the silicon chips that we’re making and assemble them together in what is going to be a building-scale, high-performance computer-like system.” 

The desire to shuttle qubits among processors means that a somewhat neglected quantum technology will come to the fore now, according to Jack Hidary , CEO of SandboxAQ, a quantum technology company that was spun out of Alphabet last year . Quantum communications, where coherent qubits are transferred over distances as large as hundreds of kilometers, will be an essential part of the quantum computing story in 2023, he says.

“The only pathway to scale quantum computing is to create modules of a few thousand qubits and start linking them to get coherent linkage,” Hidary told MIT Technology Review. “That could be in the same room, but it could also be across campus, or across cities. We know the power of distributed computing from the classical world, but for quantum, we have to have coherent links: either a fiber-optic network with quantum repeaters, or some fiber that goes to a ground station and a satellite network.”

Many of these communication components have been demonstrated in recent years. In 2017, for example, China’s Micius satellite showed that coherent quantum communications could be accomplished between nodes separated by 1,200 kilometers. And in March 2022, an international group of academic and industrial researchers demonstrated a quantum repeater that effectively relayed quantum information over 600 kilometers of fiber optics. 

Taking on the noise

At the same time that the industry is linking up qubits, it is also moving away from an idea that came into vogue in the last five years—that chips with just a few hundred qubits might be able to do useful computing, even though noise easily disrupts their operations. 

This notion, called “noisy intermediate-scale quantum” (NISQ), would have been a way to see some short-term benefits from quantum computing, potentially years before reaching the ideal of large-scale quantum computers with many hundreds of thousands of qubits devoted to correcting errors. But optimism about NISQ seems to be fading. “The hope was that these computers could be used well before you did any error correction, but the emphasis is shifting away from that,” says Joe Fitzsimons, CEO of Singapore-based Horizon Quantum Computing.

Some companies are taking aim at the classic form of error correction, using some qubits to correct errors in others. Last year, both Google Quantum AI and Quantinuum , a new company formed by Honeywell and Cambridge Quantum Computing, issued papers demonstrating that qubits can be assembled into error-correcting ensembles that outperform the underlying physical qubits.

Other teams are trying to see if they can find a way to make quantum computers “fault tolerant” without as much overhead. IBM, for example, has been exploring characterizing the error-inducing noise in its machines and then programming in a way to subtract it (similar to what noise-canceling headphones do). It’s far from a perfect system—the algorithm works from a prediction of the noise that is likely to occur, not what actually shows up. But it does a decent job, Chow says: “We can build an error-correcting code, with a much lower resource cost, that makes error correction approachable in the near term.”

Maryland-based IonQ , which is building trapped-ion quantum computers, is doing something similar. “The majority of our errors are imposed by us as we poke at the ions and run programs,” says Chris Monroe, chief scientist at IonQ. “That noise is knowable, and different types of mitigation have allowed us to really push our numbers."

Getting serious about software

For all the hardware progress, many researchers feel that more attention needs to be given to programming. “Our toolbox is definitely limited, compared to what we need to have 10 years down the road,” says Michal Stechly of Zapata Computing , a quantum software company based in Boston. 

The way code runs on a cloud-accessible quantum computer is generally “circuit-based,” which means the data is put through a specific, predefined series of quantum operations before a final quantum measurement is made, giving the output. That’s problematic for algorithm designers, Fitzsimons says. Conventional programming routines tend to involve looping some steps until a desired output is reached, and then moving into another subroutine. In circuit-based quantum computing, getting an output generally ends the computation: there is no option for going round again.

Horizon Quantum Computing is one of the companies that have been building programming tools to allow these flexible computation routines. “That gets you to a different regime in terms of the kinds of things you’re able to run, and we’ll start rolling out early access in the coming year,” Fitzsimons says.

Helsinki-based Algorithmiq is also innovating in the programming space. “We need nonstandard frameworks to program current quantum devices,” says CEO Sabrina Maniscalco. Algorithmiq’s newly launched drug discovery platform, Aurora, combines the results of a quantum computation with classical algorithms. Such “hybrid” quantum computing is a growing area, and it’s widely acknowledged as the way the field is likely to function in the long term. The company says it expects to achieve a useful quantum advantage—a demonstration that a quantum system can outperform a classical computer on real-world, relevant calculations—in 2023. 

Competition around the world

Change is likely coming on the policy front as well. Government representatives including Alan Estevez, US undersecretary of commerce for industry and security, have hinted that trade restrictions surrounding quantum technologies are coming. 

Tony Uttley, COO of Quantinuum, says that he is in active dialogue with the US government about making sure this doesn’t adversely affect what is still a young industry. “About 80% of our system is components or subsystems that we buy from outside the US,” he says. “Putting a control on them doesn’t help, and we don’t want to put ourselves at a disadvantage when competing with other companies in other countries around the world.”

And there are plenty of competitors. Last year, the Chinese search company Baidu opened access to a 10-superconducting-qubit processor that it hopes will help researchers make forays into applying quantum computing to fields such as materials design and pharmaceutical development. The company says it has recently completed the design of a 36-qubit superconducting quantum chip. “Baidu will continue to make breakthroughs in integrating quantum software and hardware and facilitate the industrialization of quantum computing,” a spokesman for the company told MIT Technology Review. The tech giant Alibaba also has researchers working on quantum computing with superconducting qubits.

In Japan, Fujitsu is working with the Riken research institute to offer companies access to the country’s first home-grown quantum computer in the fiscal year starting April 2023. It will have 64 superconducting qubits. “The initial focus will be on applications for materials development, drug discovery, and finance,” says Shintaro Sato, head of the quantum laboratory at Fujitsu Research.

Not everyone is following the well-trodden superconducting path, however. In 2020, the Indian government pledged to spend 80 billion rupees ($1.12 billion when the announcement was made) on quantum technologies. A good chunk will go to photonics technologies—for satellite-based quantum communications, and for innovative “qudit” photonics computing.

Qudits expand the data encoding scope of qubits—they offer three, four, or more dimensions, as opposed to just the traditional binary 0 and 1, without necessarily increasing the scope for errors to arise. “This is the kind of work that will allow us to create a niche, rather than competing with what has already been going on for several decades elsewhere,” says Urbasi Sinha, who heads the quantum information and computing laboratory at the Raman Research Institute in Bangalore, India.

Though things are getting serious and internationally competitive, quantum technology remains largely collaborative—for now. “The nice thing about this field is that competition is fierce, but we all recognize that it’s necessary,” Monroe says. “We don’t have a zero-sum-game mentality: there are different technologies out there, at different levels of maturity, and we all play together right now. At some point there’s going to be some kind of consolidation, but not yet.”

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• Quantum Research

Expanding the IBM Quantum roadmap to anticipate the future of quantum-centric supercomputing

We are explorers. we’re working to explore the limits of computing, chart the course of a technology that has never been realized, and map how we think these technologies will benefit our clients and solve the world’s biggest challenges. but we can’t simply set out into the unknown. a good explorer needs a map..

10 May 2022

Jay Gambetta

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A challenge of near-term quantum computation is the limited number of available qubits. Suppose we want to run a circuit for 400 qubits, but we only have 100 qubit devices available. What do we do? Read about circuit knitting with classical communication .

Two years ago, we issued our first draft of that map to take our first steps: our ambitious three-year plan to develop quantum computing technology, called our development roadmap . Since then, our exploration has revealed new discoveries, gaining us insights that have allowed us to refine that map and travel even further than we’d planned. Today, we’re excited to present to you an update to that map: our plan to weave quantum processors, CPUs, and GPUs into a compute fabric capable of solving problems beyond the scope of classical resources alone.

Our goal is to build quantum-centric supercomputers. The quantum-centric supercomputer will incorporate quantum processors, classical processors, quantum communication networks, and classical networks, all working together to completely transform how we compute. In order to do so, we need to solve the challenge of scaling quantum processors, develop a runtime environment for providing quantum calculations with increased speed and quality, and introduce a serverless programming model to allow quantum and classical processors to work together frictionlessly.

But first: where did this journey begin? We put the first quantum computer on the cloud in 2016, and in 2017, we introduced an open source software development kit for programming these quantum computers, called Qiskit . We debuted the first integrated quantum computer system, called the IBM Quantum System One , in 2019, then in 2020 we released our development roadmap showing how we planned to mature quantum computers into a commercial technology. 

IBM Quantum broke the 100‑qubit processor barrier in 2021. Read more about Eagle.

In 2021, we demonstrated a 120x speedup in simulating molecules thanks to a host of improvements, including the ability to run quantum programs entirely on the cloud with Qiskit Runtime .

Now, our updated map will show us the way forward.

IBM Quantum 2022 Updated Development Roadmap

Preparing for serverless quantum computation

In order to benefit from our world-leading hardware, we need to develop the software and infrastructure so that our users can take advantage of it. Different users have different needs and experiences, and we need to build tools for each persona: kernel developers, algorithm developers, and model developers. 

For our kernel developers — those who focus on making faster and better quantum circuits on real hardware — we’ll be delivering and maturing Qiskit Runtime. First, we will add dynamic circuits, which allow for feedback and feedforward of quantum measurements to change or steer the course of future operations. Dynamic circuits extend what the hardware can do by reducing circuit depth, by allowing for alternative models of constructing circuits, and by enabling parity checks of the fundamental operations at the heart of quantum error correction.

To continue to increase the speed of quantum programs in 2023, we plan to bring threads to the Qiskit Runtime, allowing us to operate parallelized quantum processors, including automatically distributing work that is trivially parallelizable. In 2024 and 2025, we’ll introduce error mitigation and suppression techniques into Qiskit Runtime so that users can focus on improving the quality of the results obtained from quantum hardware. These techniques will help lay the groundwork for quantum error correction in the future.

However, we have work to do if we want quantum will find broader use, such as among our algorithm developers — those who use quantum circuits within classical routines in order to make applications that demonstrate quantum advantage. 

For our algorithm developers, we’ll be maturing the Qiskit Runtime Service’s primitives. The unique power of quantum computers is their ability to generate non-classical probability distributions at their outputs. Consequently, much of quantum algorithm development is related to sampling from, or estimating properties of these distributions. The primitives are a collection of core functions to easily and efficiently work with these distributions. 

To bring value to our users, we need our programing model to fit seamlessly into their workflows, where they can focus on their code and not have to worry about the deployment and infrastructure. We need a serverless architecture .

What is circuit knitting? Circuit knitting techniques break larger circuits into smaller pieces to run on a quantum computer, and then knit the results back together using a classical computer. 

Earlier this year, we demonstrated 1 a circuit knitting method called entanglement forging to double the size of the quantum systems we could address with the same number of qubits. However, circuit knitting requires that we can run lots of circuits split across quantum resources and orchestrated with classical resources. We think that parallelized quantum processors with classical communication will be able to bring about quantum advantage even sooner, and a recent paper suggests a path forward .

With all of these pieces in place, we’ll soon have quantum computing ready for our model developers — those who develop quantum applications to find solutions to complex problems in their specific domains. We think by next year, we’ll begin prototyping quantum software applications for specific use cases. We’ll begin to define these services with our first test case — machine learning — working with partners to accelerate the path toward useful quantum software applications. By 2025, we think model developers will be able to explore quantum applications in machine learning, optimization, natural sciences, and beyond.

Solving the scaling problem

Of course, we know that central to quantum computing is the hardware that makes running quantum programs possible. We also know that a quantum computer capable of reaching its full potential could require hundreds of thousands, maybe millions of high-quality qubits, so we must figure out how to scale these processors up. With the 433-qubit “Osprey” processor and the 1,121-qubit “Condor” processors — slated for release in 2022 and 2023, respectively — we will test the limits of single-chip processors and controlling large-scale quantum systems integrated into the IBM Quantum System Two.  But we don’t plan to realize large-scale quantum computers on a giant chip. Instead, we’re developing ways to link processors together into a modular system capable of scaling without physics limitations.

To tackle scale, we are going to introduce three distinct approaches. First, in 2023, we are introducing “Heron”: a 133-qubit processor with control hardware that allows for real-time classical communication between separate processors, enabling the knitting techniques described above. The second approach is to extend the size of quantum processors by enabling multi-chip processors. “Crossbill,” a 408 qubit processor, will be made from three chips connected by chip-to-chip couplers that allow for a continuous realization of the heavy-hex lattices across multiple chips. The goal of this architecture is to make users feel as if they’re just using just one, larger processor.

The 133-qubit “Heron” processor, slated for 2023.

Along with scaling through modular connection of multi-chip processors, in 2024, we also plan to introduce our third approach: quantum communication between processors to support quantum parallelization. We will introduce the 462-qubit “Flamingo” processor with a built-in quantum communication link, and then release a demonstration of this architecture by linking together at least three Flamingo processors into a 1,386-qubit system. We expect that this link will result in slower and lower-fidelity gates across processors. Our software needs to be aware of this architecture consideration in order for our users to best take advantage of this system.

Quantum communication via two-qubit gates between separate chips.

Our learning about scale will bring all of these advances together in order to realize their full potential. So, in 2025, we’ll introduce the “Kookaburra” processor. Kookaburra will be a 1,386 qubit multi-chip processor with a quantum communication link. As a demonstration, we will connect three Kookaburra chips into a 4,158-qubit system connected by quantum communication for our users.

In 2025, we’ll introduce the 1,386-qubit multi-chip processor, “Kookaburra.” With its communication link support for quantum parallelization, three Kookaburra chips can connect into a 4,158-qubit system.

The combination of these technologies — classical parallelization, multi-chip quantum processors, and quantum parallelization — gives us all the ingredients we need to scale our computers to wherever our roadmap takes. By 2025, we will have effectively removed the main boundaries in the way of scaling quantum processors up with modular quantum hardware and the accompanying control electronics and cryogenic infrastructure. Pushing modularity in both our software and our hardware will be key to achieving scales well ahead of our competitors, and we’re excited to deliver it to you.

The quantum-centric supercomputer

Our updated roadmap takes us as far as 2025 — but development won’t stop there. By then, we will have removed some of the biggest roadblocks in the way of scaling quantum hardware, while developing the tools and techniques capable of integrating quantum into computing workflows. This sea change will be the equivalent of replacing paper maps with GPS satellites as we navigate into the quantum future.

This sea change will be the equivalent of replacing paper maps with GPS satellites.

We aren’t just thinking about quantum computers, though. We’re trying to induce a paradigm shift in computing overall. For many years, CPU-centric supercomputers were society’s processing workhorse, with IBM serving as a key developer of these systems. In the last few years, we’ve seen the emergence of AI-centric supercomputers, where CPUs and GPUs work together in giant systems to tackle AI-heavy workloads.

Now, IBM is ushering in the age of the quantum-centric supercomputer, where quantum resources — QPUs — will be woven together with CPUs and GPUs into a compute fabric. We think that the quantum-centric supercomputer will serve as an essential technology for those solving the toughest problems, those doing the most ground-breaking research, and those developing the most cutting-edge technology.

We may be on track, but exploring uncharted territory isn’t easy. We’re attempting to rewrite the rules of computing in just a few years. Following our roadmap will require us to solve some incredibly tough engineering and physics problems.

But we’re feeling pretty confident — we’ve gotten this far, after all, with the new help of our world-leading team of researchers, the IBM Quantum Network, the Qiskit open source community, and our growing community of kernel, algorithm, and model developers. We’re glad to have you all along for the ride as we continue onward.

Learn more about:

Quantum Chemistry : Few fields will get value from quantum computing as quickly as chemistry. Even today’s supercomputers struggle to model a single molecule in its full complexity. We study algorithms designed to do what those machines can’t.

Eddins, A., Motta, M., Gujarati, T., et al. Doubling the size of quantum simulators by entanglement forging . arXiv. (2021)

IBM Quantum: Tomorrow's computing today

Keep exploring, ibm quantum developer conference 2024: apply today.

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Quantum computing research trends report

Get ready for the second quantum revolution.

Report highlights

Publication on quantum computing has increased steeply since the early 1990s

Publication is international and significant investments are happening

The top 10 institutions with the highest publication output are located in China, France, Canada, the US, the UK and Singapore

The two most prolific authors are from Chinese and US institutions

Learn more about tracking current R&D priorities while also monitoring influential trends

Are we at the brink of a second quantum revolution?

Quantum computing is a hallmark "moonshot" of a second quantum revolution. Whereas the first revolution enabled lasers and transistors based on rules of quantum mechanics, the second aims to control quantum systems. 1,2  Quantum computing uses quantum phenomena to perform computations. Quantum computing is part of the broader area of quantum information technologies or quantum technologies. Quantum technologies seek to understand how quantum phenomena can be used in computing, communication, sensing and metrology to go beyond what classical systems can do.

For example, qubits 3  — the quantum version of the classical bit — are not restricted to the pure 0 or 1 of binary digits. Physically a qubit could be realized using the polarization of a single photon, or electron spin, or currents in a superconductor. At the end of a calculation when the answer is read, each qubit will come out as either 0 or 1. But during the calculation the qubit represents both 0 and 1 simultaneously. This is called superposition. This core aspect of quantum computing enables quantum computers to outperform classical computers in some problems requiring intense computation. A second crucial aspect is entanglement, or the superposition of a pair of more than one qubits. This allows a quantum computer to explore a much larger computational space than any classical computer can explore.

The second quantum revolution is where you’re really using the quantum mechanics to do everything for you.

Ray Simmonds, U.S. National Institute of Standards and Technology 1

Quantum computing has made a big splash across the news in the last few years — from Google’s 53-qubit quantum computer “Sycamore” achieving what has been coined quantum supremacy to multibillion-dollar initiatives around the world to develop quantum technologies for computing and beyond. The race is on.

Research methodology

This report is based on research and analysis conducted in Scopus, an expert-curated abstract and citation database, in February 2021.

The search was conducted assuming a limited knowledge of the topic and interest in research activity around possible applications of quantum computing. It began with "quantum comput*" to combine a loose phrase with a wild card (*), which accommodated word variations like computation.

To broaden the search slightly, we added the terms "quantum algorith*", "quantum simulation*", "qubit" and "quantum bit" to arrive at the search used for this research trends report:

TITLE-ABS-KEY ("Quantum comput*") OR TITLE-ABS-KEY ("Qauntum algorith*") OR TITLE-ABS-KEY ("Quantum simulation*")) OR (TITLE-ABS-KEY ("Qubit*") OR TITLE-ABS-KEY ("quantum bit*")

This report provides search results for document titles, abstracts and keywords. Scopus indexes content from 25,000 active titles and 7,000 publishers, as well as patents and conference abstracts. Scopus enriches data, metrics and analytical tools inform both research and business strategy, driving better decisions and outcomes.

The search will pick up some documents in related areas such as quantum communication, but also exclude some of the major works in these areas. It could be further refined to include or remove a portion of other areas, such as "quantum simulation", "quantum communication", "quantum cryptography", and "quantum sensing". Am ore extensive search can be done to cover the broader area of quantum technologies, but here the focus is more on quantum computing, including quantum simulation.

A brief history of quantum computing

In 1982, the physicist and 1957 Nobel Laureate Richard Feynman discussed a machine that would operate on quantum mechanical principles to simulate the behavior of one quantum system using another quantum system - a quantum simulator. 4 In 1985, David Deutsch of oxford University further advanced the field by proposing a quantum Turing machine (based on the pioneering work of Alan Turing on what constitutes a general computer) and specified an algorithm designed to run on a quantum computer. 5 Beyond the realm of researchers in quantum physics and theoretical computer science, the field really took off in the mid-90s. In 1994, the mathematician Peter Shor proposed an algorithm for a real world "killer application" of quantum computers. It would factorize large numbers into their prime number counterparts exponentially faster than possible with a classical computer. 6

Why was Shor's result so important? Much of modern encryption, such as RSA encryption, is based on the idea that it is very difficult to factor a large integer that is the product of two large prime numbers. 7 While it is easy to take two primes and multiply them together to form a big number, doing the inverse from a large number to find its constituting unknown primes is hard. In fact, so hard that a classical computer might take a lifetime or more to perform the calculation. However, on a quantum computer, if it can be made to operate with a large number of qubits, finding prime numbers could be done efficiently (mathematically in polynomial time), putting the basis of much modern encryption used on the internet at risk, If that hard problem can be solved, what other hard problems might become much easier? Actually, quite a few, including hacking bitcoins and other cryptocurrencies.

Publication rate on quantum computing has steeply increased

Figure 1. Quantum computing documents by year, 1982-2020

Scopus search results show a steady increase in research output in quantum computing and related areas, really kicking off in 1994. The growth increases steadily resulting in over 48,000 publication. Especially from 2015 onward there is sa steeper rate of publication.

Concurrent with the faster research developments, achievements in quantum computing in terms of number of qubits used for computations emerge:

2012 — A group at University of Bristol factored the number 21 with Shor's algorithm 8

2017 — D-Wave Systems announced the first sale of its D-Wave 2000Q quantum computer; it is not a general purpose quantum computer, but can address optimization problems 9

2020 — Google accurately simulated the binding of hydrogen chains and isomerization of diazene using Sycamore 10

A significant hurdle in quantum computing

Progress in quantum computing and the broader area of quantum technologies has been quite remarkable. However, we still may face significant hurdles before a general purpose quantum computer is available to tackle, for instance, really large scale factorization into prime numbers or computational tasks, optimization problems excluded. The challenge is that a quantum computer must do its computation, the superposition that allows for the computational advantage breaks down, a process called decoherence. 11 The more qubits used, the more susceptible to noise the superposition becomes. This is why real-world quantum computers have been so hard to build.

Physical implementations of quantum computers today, such as those using semiconduction technology, must operate at close to absolute zero temperature in a highly isolated environment. Related areas like quantum communication (notably quantum cryptography) and quantum sensing do not rely on a large number of qubits to operate. As an interesting twist, while quantum computing may potentially make current encryption schemes unsecure, quantum cryptography would be a way to provide fundamentally secure encryption schemes. 12

Are there potential solutions to make computer more resistant to distubances? In classical computing and communication, error correcting codes are introduced to correct for noise; for instance, if someone cannot hear what you say, you repeat your message. Impressive work has been done to generalize the concept of error correction codes into quantum error correction for an overview, see the now classical textbook by Michael Nielsen and Isaac Chuang. 13 To correct errors in one qubit, however, requires the use of several qubits, and the technological race is still to scale up quantum, computers for large scale operations. Physicist John Preskill called this the Noisy Intermediate-Scale Quantum (NISQ) era as physicist and engineers are still working hard to solve all technical challenges.

As quantum computing moves toward real-world applications, it continues to be an area for fundamental new discoveries in physics. In 2012, Serge Haroche and David Wineland were awarded the Nobel Prize in Physics "for ground-breaking experimental methods that enable measuring and manipulation of individual quantum systems". 14

Their work has profound implications for quantum information and quantum computing:

Their ground-breaking methods have enabled this field of research to take the very first steps towards building a new type of super fast computer based on quantum physics. Perhaps the quantum computer will change our everyday lives in this century in the same radical way as the classical computer did in the last century." - NobelPize.org

Top quantum computing publication types are journal articles and conference papers

Figure 2. Quantum computing documents by source, 1982-2020

Quantum technologies/computing research outputs with Scopus are primarily journal articles. This reflects a long history of basic research in physics, with many well-established journals (more on journals below). The novelty and rapid evolution of the field is reflected in the high proportion of publications emerging from conferences (21%), which is about twice as high as the overall proportion of conference papers in Scopus(11%). It is notable that the quantum technology community was early adopters of using the ArXiv preprint server to share their works.

Quantum computing research has an international footprint

Figure 3. Quantum comp[uting global top affiliations by document count, 1982-2020

The 10 institutions with the highest publication output are located in China, France (via the CNRS laboratories), Canada, the US, the UK and Singapore. The Chinese Academy of Sciences shows particularly high output. China's overall spending on quantum technologies, including quantum computing is not public information. However, the government's interest in funding quantum technologies is clear from the-Five-Year Plan 2016-202 and a 10 billion USD investment to build the world's largest quantum research facility. 15

The majority of author affiliations are academic and governmental research institutes. Private sector enterprises appear much further down the list with companies such as Nippon Telegraph and Telephone (NTT), IBM Thomas Watson Research Center, and Microsoft Research.

Top Contributors to quantum computing

Figure 4. Quantum computing global top authors by document count, 1982-2020

The two first authors on the list are Professors Guang-Can Guo and Franco Nori. Prof. Guang-Can Guo opens in new tab/window , University of Science and Technology, Hefei, China, publishes on the broad topics of quantum information and has many publications in photonic quantum computing.

Figure 5. Scopus author profile of Guang-Can Guo opens in new tab/window , University of Science and Technology of China (excerpt of full profile)

Prof. Franco Nori opens in new tab/window , University of Michigan, Ann Arbor, US, is a leading researcher on solid state quantum computing. Prof. Nori also has a long history working in Japan.

Figure 6.  Scopus author profile of Franco Nori opens in new tab/window , University of Michigan, USA, and RIKEN, Japan (excerpt of full profile)

Physics, optical sciences and engineering journals lead in quantum computing publications

Figure 7. Quantum computing documents per year by source, 1982–2020

Physics, optical sciences and engineering journals top the list of journals leading in quantum computing publications. The journal with the highest number of publications in the field is  Physical Review A . Over the last decade, the journal has undergone topical restructuring that led to a change in statement scope in the 1990s ( Atomic, Molecular and Optical Physics ) and then the explicit inclusion of quantum information in  Physical Review A  as of 2016. The Journal  Quantum Information Processing  was first published in 2002 and is a relatively new contributor to the body of literature.

Do you need to follow developments in quantum computing and the broader area of quantum technologies?

Absolutely.

Quantum technologies, not only quantum computing, are shifting towards enabling real-world uses. Quantum cryptography is already seeing some commercial applications. Research and quantum technology applications are fueled by strategic government investment in the US, 19 the EU 20 and China. 14 Industry initiatives include the Pistoia Alliance 21 and IBM's Quantum Summit 2020, 22 , where, among others, IBM discussed their ambition to build a 1000 bit quantum computer by 2023. 23

Technology business journalist Kara Swisher once asked Google CEO Sundar Pichai it was possible that Google missed the Cloud service trend in the early 2000s and allowed Amazon a head start. (Google has invested heavily to catch up.) Pichai's answer was that they had been busy doing other things.

Don't miss out on an important research trend. Bookmark this page for updates and a head start in planning for quantum computing.

Business Intelligence for science and technology

With Scopus, track your current R&D priorities while also monitoring influential trends. This rich abstract and citation database provides insights into comprehensive interdisciplinary research and analytics. Gain scientific knowledge and competitive intelligence as you:

Track research trends Get alerts of breakthroughs that can impact your business

Analyze output of key contributors Find collaborators or competitive white space

Explore relevant and trusted research Access a comprehensive knowledge base

Would you like to learn more about how Scopus can benefit your research and business?

J. Dowling and G. Milburn, “ Quantum Technology, the Second Quantum Revolution opens in new tab/window ,” Phil. Trans. R. Soc. Lond. A (2003).

NIST. 2018.  The second quantum revolution opens in new tab/window . Accessed September 2020.

The word qubit coined in 1995 by B. Shumacher and W.K. Wooters,see https://quantumfrontiers.com/2015/06/09/who-named-the-qubit/ opens in new tab/window

Feynman, R. 1982. Simulating physics with computers. Int. J. Theor. Phys. 21: 467.

Deutsch, David (1985). "Quantum theory, the Church-Turing principle and the universal quantum computer." Proceedings of the Royal Society A. 400(1818): 97–117.

Shor, P.W. (1994). "Algorithms for quantum computation: discrete logarithms and factoring". Proceedings 35th Annual Symposium on Foundations of Computer Science. IEEE Comput. Soc. Press: 124–134.

For an explanation of RSA encryption, https://www.abc.net.au/news/science/2018-01-20/how-prime-numbers-rsa-encryption-works/ opens in new tab/window , accessed Feb. 2021.

Martin-Lopez, E. et al. 2012. Experimental realization of Shor’s quantum factoring algorithm using qubit recycling. Nature Photonics 6: 773.

D-Wave Systems. 2017. Temporal Defense Systems purchases the first D-Wave 2000Q quantum computer opens in new tab/window . Accessed September 2020.

Google AI Quantum and Collaborators. 2020. Hartree-Fock on a superconducting qubit quantum computer. Science 369: 1084.

W. Zhurek, Decoherence and the Transition from Quantum to Classical”  Physics” Today 44, 10, 36 (1991);  https://doi.org/10.1063/1.881293 opens in new tab/window .

For a brief on quantum cryptography, see for instance  ETSI White Paper No. 8

Quantum Safe Cryptography and Security An introduction, benefits, enablers and challenges opens in new tab/window June 2015 ISBN No. 979-10-92620-03-0.

Michael A. Nielsen and Isaac L. Chuang. Quantum Computation and Quantum Information. Cambridge University Press (2000).

Nobel Prize in Physics 2012, Press Release opens in new tab/window .

IDQ. 2018. China’s growing investment in quantum computing opens in new tab/window . Accessed September 2020.

Marr, B. 2017. 6 Practical Examples Of How Quantum Computing Will Change Our World opens in new tab/window . Accessed September 2020.

Drug Discovery Online. 2020. Researchers use NSF Convergence Accelerator to shorten drug discovery timeline opens in new tab/window . Accessed November 2020.

Alvarez-Rodriguez, U. et al. (2918) Quantum artificial life in an IBM quantum computer. Scientific Reports 8: 14793.

Kratsios, M. and Liddell, C. 2020. The Trump administration is investing 1 billion USD in research institutes to advance industries of the future. Accessed September 2020.

European Commission. 2018. Quantum Technologies Flagship kicks off with first 20 projects opens in new tab/window . Accessed September 2020.

Pistoia Alliance. Almost one third of life science companies set to being quantum computing evaluation this year opens in new tab/window . Accessed September 2020.

Annunziata, A. 2020. IBM Quantum Summit 2020: Exploring the promise of quantum computing for industry opens in new tab/window . Accessed November 2020.

Adrian Cho. IBM promises 1000-qubit quantum computer — a milestone — by 2023 opens in new tab/window , Science, Sep. 15, By Adrian ChoSep. 15, 2020.

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• TECHNOLOGY FEATURE
• 05 August 2024

Quantum computing aims for diversity, one qubit at a time

• Amanda Heidt 0

Amanda Heidt is a science writer in Moab, Utah.

You can also search for this author in PubMed   Google Scholar

Irene Fernández de Fuentes (centre) co-founded the Australian charity Quantum Women. Credit: Sydney Quantum Academy

Feeling adrift and disconnected during the COVID-19 pandemic, Elisa Torres Durney decided to jump headlong into one of the hottest, and most challenging, disciplines around. She took a virtual course on quantum computing.

Then a secondary-school student in Chile, Torres Durney knew little about the field, but coming from a family of engineers and artists, she felt drawn to the opportunities that quantum computing offered to combine practicality and creativity. Over eight months, she learnt the basics from experts in academia and industry, in a course run by the non-profit organization, Qubit by Qubit. She also started writing code to simulate quantum circuits, and later ran her own experiments on a quantum computer.

‘Quantum internet’ demonstration in cities is most advanced yet

The experience was “transformative”, says Torres Durney, who will soon start an engineering undergraduate degree at Duke University in Durham, North Carolina. But she realized that it was also a privilege, one that few students could access. So, in 2022, Torres Durney co-founded Girls in Quantum to further democratize quantum computing around the world. “So many people think that quantum is just for experts with a PhD, but I started at 16 years old, and I’m still here,” she says.

Girls in Quantum is one of a handful of initiatives aimed at increasing representation in quantum computing, which is one of the fastest-growing disciplines in science, technology, engineering and mathematics (STEM). By targeting every step of the career path, these groups aim to broaden tomorrow’s workforce, introducing the field to a younger, more diverse audience, imparting technological know-how and professional skills and ushering a new generation into positions of leadership. The hope is to avoid the diversity challenges that plague physics more broadly — the field has some of the lowest representation of women and people of other marginalized identities in STEM ( T. Berry and S. Mordijck Commun. Phys. 7 , 77; 2024 ).

Elisa Torres Durney made her first foray into quantum computing as a secondary-school student in Chile. Credit: Tell Magazine/Javiera Díaz e Valdés

“What I find really exciting about emerging technologies like quantum computing is we have the chance to get things right early on,” says Kiera Peltz, founder and chief executive of Qubit by Qubit, who is based in the Bay Area of California. Since its launch in 2020, the organization has introduced some 22,000 students worldwide to quantum computing, says Peltz, and more than half come from under-represented backgrounds. “Quantum computing will most certainly impact society, and I think that makes it even more critical to have diverse voices and experiences shaping these technologies.”

‘A glass ceiling for diversity’

Quantum computing draws on the foundational principles of quantum mechanics, a branch of physics that describes the behaviour of atomic and subatomic particles. Scientists have leveraged these properties to build computers powered by basic units of information called qubits that can occupy two states concurrently — a phenomenon known as superposition. These computers have different strengths compared with conventional devices that use a binary system of ones and zeros, such as the ability to evaluate a vast number of possibilities simultaneously, and researchers are optimistic about the opportunity this affords to tackle previously intractable problems in drug development, climate science, cybersecurity and other applications.

The future is quantum: universities look to train engineers for an emerging industry

Excitement over these tools — which remain, for the moment, rudimentary — is driving renewed interest in careers in physics. US jobs in the field are expected to grow by 5% by 2032, yet only one in 54 applicants for quantum roles are women, and 80% of quantum companies do not have a woman in a senior leadership role.

Fewer data exist on other marginalized identities, but a survey published this year of some 2,500 physics students and professionals in Canada, for example, revealed that only 1.5% of respondents identified as Black or Indigenous, 3.5% as gender diverse and 7% as having a disability ( E. J. Hennessey et al . Preprint at arXiv https://doi.org/m9qk; 2024 ).

“There’s still very much a glass ceiling for diversity,” says Denise Ruffner, an independent consultant based in Pasadena, California, who advises quantum companies on diversity practices. “I’m glad that we started early to try to break through, but it’s something that’s still there and needs to be acknowledged.”

Equipping the next generation

The technology behind quantum computers can be daunting, and groups invested in engaging younger audiences must contend with a steep learning curve. Quantum mechanics doesn’t relate in clear ways to daily life, so educators must get creative when teaching foundational principles .

For Chris Cantwell, the founder of Quantum Realm Games, this has meant engaging with quantum concepts through play. Cantwell, who is based in Chino Hills, California, spent years developing a version of quantum chess to join the ranks of existing games such as quantum noughts-and-crosses and a quantum version of the popular world-building computer game, Minecraft .

Chris Cantwell plays quantum chess with his son. Credit: Christopher and Laurie Cantwell

In Cantwell’s quantum chess, pieces can occupy two positions on the board — signifying superposition — and others can become ‘entangled’, another quantum concept, to move together in predictable ways. He has begun playing it with his five-year-old son, and says the goal is not to teach quantum theory but to create a space in which people can experience quantum phenomena for themselves. “We have to start young, and we have to start diverse, to develop a generation with an intuitive understanding of things,” Cantwell says. “They’ll imagine uses for quantum computing that we can’t even conceive of right now.”

Quantum computers: what are they good for?

Among more-conventional learning opportunities, Qubit by Qubit offers virtual courses to secondary-school students and undergraduates globally, with minimal academic prerequisites. Many courses are days long, but others span up to two semesters and include hands-on laboratory work in partnership with academic scientists and industry leaders. Students who complete these courses can then apply for summer internships that pair them with researchers pursuing quantum computing projects.

“The biggest point of attrition” in physics, according to Shohini Ghose, a physicist at Wilfrid Laurier University in Waterloo, Canada, “is in the period right after high school, when people are picking a potential career”. Ghose, who is also a regional chair for women in science and engineering at Canada’s Natural Sciences and Engineering Research Council, the country’s federal funding agency, says that keeping students “invested through this critical juncture is a good step”.

Offering quantum-computing courses virtually or, in some cases, at a discount does make them more accessible, but cost and the fact that they are taught in English remain a barrier to broader participation. Qubit by Qubit makes as many of its programmes as possible free — including a one-week virtual ‘boot camp’ for students at historically Black colleges and universities and other minority-serving institutions in the United States — and offers scholarships.

Students do a basic superposition experiment at a summer camp run by Qubit by Qubit. Credit: Trent Peltz of The Coding School

Girls in Quantum’s programmes are free, including a nine-week virtual course. The group is also one of the few actively working to translate resources into other languages; its network of global ambassadors has created guides in Spanish, Russian and Tamil. And last year, in partnership with IBM, Girls in Quantum organized a quantum hackathon in Latin America.

Quantum retention

Still other groups are tackling cultural and social barriers that could otherwise drive people out of the field.

“I think it’s better to have a workforce that’s 20% minorities, but they’re happy, versus one that’s 50% minorities, but they’re miserable,” says Tzula Propp, a quantum information theorist at Delft University of Technology in the Netherlands and co-founder, with Ruffner, of the non-profit body Diversity in Quantum (DiviQ). “Quantum is a pressure-cooker environment, and the people who get cooked out quickest are marginalized people with intersecting struggles.”

The Australian charity Quantum Women, founded in 2021, focuses on teaching ‘soft skills’ to make women more-effective communicators and competitors in the jobs market. “What we really want is to try to get women into positions of leadership,” says Irene Fernández de Fuentes, a co-founder of Quantum Women and an experimental quantum physicist at the research institute QuTech, based in Delft, the Netherlands. “There are many fields that have proven that a more diverse team can only bring good.”

Quantum is a pressure-cooker environment, says Tzula Propp, co-founder of Diversity in Quantum. Credit: Quantum Delta NL/Rebekka Mell

Besides highlighting the work of its members, Quantum Women offers virtual and in-person workshops on public speaking, grant writing, building a CV and other topics in professional development. It’s also hosting ‘matchmaking’ sessions involving early-career professionals and industry partners. De Fuentes says that the first job offers for attendees have started to trickle in, “which feels great”.

NatureTech hub

DiviQ is currently building special-interest groups — including ones for women, queer scientists, people of colour and people with disabilities — to allow people to tap into networks of supportive peers. In June, the organization held its first Proud to be in Quantum summit for Pride month, and Propp is now piloting a mentorship programme for DiviQ members. Rather than one-on-one pairings, mentors will have two peers at similar career stages to meet with monthly, as well as a senior mentor “to call in a pinch”, Propp says.

And more mentors are needed. Ruffner says that when she gives talks, she often asks whether anyone is mentoring a woman or member of an under-represented group. “There usually aren’t a lot of hands up in the air,” she says.

“Don’t just talk about diversity or read about it,” Ruffner concludes. “Take action and find someone that you can mentor, and make a difference in someone’s life.”

Nature 632 , 464-465 (2024)

doi: https://doi.org/10.1038/d41586-024-02541-z

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New Oxford quantum hub to tackle key challenges in quantum technologies

Today, the UK Government has announced the launch of five new research hubs to develop quantum technologies in areas ranging from healthcare and computing to national security and critical infrastructure.  One of the hubs will be led by the University of Oxford, and aims to develop the technologies needed for the UK to play a key role in the development of quantum  computers - a market estimated to be worth $1.3 trillion by 2035.

'This isn't just about research; it's about putting that research to work. These hubs will bridge the gap between brilliant ideas and practical solutions. They will not only transform sectors like healthcare and security, but also create a culture of accelerated innovation that helps to grow our economy.'

Quantum technologies harness quantum physics to gain a functionality or performance which is otherwise unattainable, deriving from science which cannot be explained by classical physics such as Newton’s laws of motion or thermodynamics.

The Hub for Quantum Computing via Integrated and Interconnected Implementations (QCI3) is led by the University of Oxford. Within the hub, researchers will work closely with industry partners to identify and develop real-world applications of quantum computing, including focusing on design for new materials, chemicals, fluid simulation techniques, and machine learning. For example, the hub will work on the development of quantum machine learning protocols which are key to the development of quantum neural networks with applications in areas such as fraud detection.

The hub will undertake research under three broad themes:

• Improve quantum computing performance through hardware research to show quantum advantage across several platforms,
• Develop networking technologies to enable quantum technologies to scale to large systems, ultimately creating distributed quantum computing networks,
• Build collaborations with application scientists and engineers to develop algorithms suitable for testing the quantum hardware developed.

The work will involve over 50 co-investigators with expertise across many different aspects of quantum computing, based at 18 institutions throughout the UK. The Hub will also engage with around 30 industry partners, who have already pledged support through £9.9M funding.

Our hub brings together researchers with broad expertise on the forefront of hardware and software for quantum computing with leading experts in application areas. We will work with our industrial partners to unlock critical challenges in the development of quantum technologies, and drive impact through the development of real-world use cases for quantum computing. Professor Andrew Daley (Principal Investigator of the QCI3 hub and Professor of Quantum Physics at Oxford)

Professor Dominic O’Brien , Director of the Oxford-led Hub, said: ‘The UK has invested in a coordinated National Programme over the past decade, creating a vibrant research and exploitation landscape. In the next decade, the quantum strategy and recently announced quantum missions set ambitious goals for the next phase of the programme. The QCI3 Hub, with Oxford as a lead partner, is very much looking forward to playing a part in delivering these, collaborating with our partners to develop concepts and early demonstrations, training researchers, and engaging with the community.’

The new hub builds on work across the first two phases of the National Quantum Technologies Programme, including the Networked Quantum Information Technologies (NQIT) Hub (led by Professor Ian Walmsley at Oxford’s Department of Physics) and the Quantum Computing & Simulation Hub (Directed by Professor Dominic O’Brien). Oxford also has a strong track record in launching quantum spinouts and startups, including Oxford Ionics , which is harnessing the power of trapped ions, and Oxford Quantum Circuits , which is developing quantum computers based on superconducting devices.

‘The five Quantum Technology Hubs announced today will harness the UK’s expertise to foster innovation, support growth, and ensure that we capitalise on the profound opportunities of this transformative technology.’

Oxford also has a strong involvement in the other four newly-launched quantum hubs.  Professor Dame Molly Stevens  (Kavli Insitute for Nanoscience Discovery, Department of Engineering Science and Department of Physiology, Anatomy and Genetics, University of Oxford) will be Deputy Director of the Q-BIOMED hub led by UCL and Cambridge which aims to use quantum technologies to transform early disease diagnosis. This could include quantum-enhanced blood tests to diagnose infectious diseases and cancer quickly and cheaply using portable instruments, saving time and reducing costs to the NHS.

Professor Jason Smith (Department of Materials, Oxford University) will be Associate Director of the new Integrated Quantum Networks (IQN) hub led by Herriot-Watt University. This will develop quantum communications systems to deliver secure communications and cloud-based quantum computing, with Oxford researchers focusing on memory devices that will form the basis of a new quantum internet.

Harnessing the unique properties of quantum physics such as entanglement and quantum memory, the networks will be designed to ensure secure access to future quantum computing services, as well as future-proof secure quantum communications and distributed quantum sensing applications.

Further information about the new hubs can be found on the UKRI website .

The hubs are delivered by the UKRI Engineering and Physical Sciences Research Council (EPSRC), with a £106 million investment from EPSRC, the UKRI Biotechnology and Biological Research Council, UKRI Medical Research Council, and the National Institute for Health and Care Research.

Industry collaboration is a key element to all of the hubs, which leverage significant cash and in-kind contributions from partners worth more than £54 million.

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Quantum Computing

Microsoft Azure Quantum innovates across every layer of the quantum stack, from software and applications to control and devices. This includes the pursuit of fault-tolerant topological qubits that scale towards a general-purpose quantum computer.

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Senior Applied Scientist – Microsoft Egypt  

Posted : April 17, 2024 Location : Cairo, Egypt Research Area(s) : Artificial intelligence, Data platforms and analytics, Quantum computing

Embark on a rewarding career as an Applied Sciences professional at Microsoft Egypt. As a key member of our team, you’ll collaborate with experts in areas like machine learning, data science, and quantum computing. Contribute…

Interferometric Single-Shot Parity Measurement in an InAs-Al Hybrid Device  

M. Aghaee, Alejandro Alcaraz Ramirez, Zulfi Alam, Rizwan Ali, Mariusz Andrzejczuk, Andrey Antipov , M. Astafev, Amin Barzegar, Bela Bauer , Jonathan Becker, U. Bhaskar, Alex Bocharov , S. Boddapati, David Bohn, Jouri D. S. Bommer, L. Bourdet, Arnaud Bousquet, Samuel Boutin, Lucas Casparis , Benjamin James Chapman, S. Chatoor, Anna Wulff Christensen, Cassandra Chua, Patrick Codd, William Cole, Paul Cooper, Fabiano Corsetti, Ajuan Cui, Paolo Dalpasso, J. P. Dehollain, Gijs de Lange (gidelang) , M. Moor, Andreas Ekefjard, Tareq El Dandachi, J. C. E. Saldaña, S. Fallahi, L. Galletti, Geoff Gardner , D. Govender, F. Griggio, Ruben Grigoryan , Sebastian Grijalva, Sergei Gronin , Jan Gukelberger , Marzie Hamdast, Firasamine Hamze, Esben Bork Hansen, Sebastian Heedt (seheedt) , Zahra Heidarnia, Jes'us Herranz Zamorano, Samantha Ho, Laurens Holgaard, John Hornibrook, Jinnapat Indrapiromkul, Henrik Ingerslev, Lovro Ivancevic, Thomas Jensen, Jaspreet Jhoja, Jeffrey Jones, Konstantin V. Kalashnikov, Ray Kallaher , R. Kalra, Farhad Karimi, Torsten Karzig , Evelyn King, M. E. Kloster, Christina Knapp, D. Kocoń, J. Koski, P. Kostamo, Mahesh Kumar, T. Laeven, T. Larsen, Jason Lee, Kyunghoon Lee, Grant Leum, Kongyi Li, T. Lindemann, Matthew Looij, J. Love, Marijn Lucas, Roman Lutchyn , Morten Hannibal Madsen, Nash Madulid, Albert Malmros, M. Manfra, Devashish Mantri, S. Markussen, Esteban Martinez, Marco Mattila, R. McNeil, Antonio Rodolph Mei, R. Mishmash, Gopakumar Mohandas, Christian Mollgaard, Trevor Morgan, George Moussa, Dr. Chetan Nayak , Jens Nielsen, Jens Munk Nielsen, William HP Nielsen , B. Nijholt, Mike Nystrom, Eoin O'Farrell , Thomas Ohki, K. Otani, Brian Paquelet Wutz, S. Pauka, Karl Petersson , Luca Petit, D. Pikulin, G. Prawiroatmodjo, F. Preiss, Eduardo Puchol Morejon, Mohana Rajpalke, Craig Ranta, K. Rasmussen, David Razmadze, Outi Reentila, David Reilly, Yuan Ren, Ken Reneris, Richard Rouse, Ivan Sadovskyy (ivsadovs) , L. Sainiemi, I. Sanlorenzo, E. Schmidgall, Cristina Sfiligoj, Mustafeez Bashir Shah, Kevin Simoes, Shilpi Singh, Sarat Sinha, Thomas Soerensen, P. Sohr, T. Stankevič, Lieuwe Stek, Eric Stuppard, H. Suominen, Judith Suter , Sam Teicher, Nivetha Thiyagarajah, R. Tholapi, Mason Thomas , Emily A Toomey, Josh Tracy, Michelle Turley, Shivendra Upadhyay, Ivica Urban, Kevin Van Hoogdalem , David Van Woerkom , D. Viazmitinov, Dominik Vogel, John Watson, Alex Webster, Joseph Weston, Georg Wolfgang Winkler , Di Xu, Chung Kai Yang , Emrah Yücelen , R. Zeisel, Guoji Zheng, Justin Zilke

Microsoft Quantum Innovator Series: The Path to Quantum at Scale  

October 10, 2023 – November 28, 2023  |  Virtual

Get the inside, first-hand account of Microsoft’s strategy to scaled quantum computing. In this series, you will hear directly from Microsoft’s Azure Quantum scientists and leaders about the path to quantum at scale and how…

Research Focus: Week of May 8, 2023  

May 10, 2023

In this issue: Microsoft researchers win four more awards; AutoRXN automates calculations of molecular systems; LLM accelerator losslessly improves the efficiency of autoregressive decoding; a frequency domain approach to predict power system transients.

Research Focus: Week of January 9, 2023  

January 11, 2023

Welcome to Research Focus, a new series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. Jan P. Unsleber, Hongbin Liu, Leopold Talirz,…

Quantum Speedups for Zero-Sum Games via Improved Dynamic Gibbs Sampling  

Adam Bouland, Yosheb Getachew, Yujia Jin, Aaron Sidford, Kevin Tian

ICML 2023 | January 2023

High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference validation  

Jan P. Unsleber, Hongbin Liu , Leopold Talirz, Thomas Weymuth, Maximilian Morchen, Adam Grofe, Dave Wecker, Christopher J. Stein, Ajay Panyala, Bo Peng, Karol Kowalski, Matthias Troyer, Markus Reiher

November 2022

Research Summit 2022  

October 18, 2022 – October 20, 2022  |  Virtual

Microsoft Research Summit 2022, held October 18-20, 2022, explores what’s next for technology and humanity.

InAs-Al Hybrid Devices Passing the Topological Gap Protocol  

August 5, 2022  |  Dr. Chetan Nayak

Dr. Chetan Nayak, Distinguished Engineer of Quantum at Microsoft, met with leaders in the Quantum industry to discuss Microsoft’s recent hardware progress in July 2022. In this session, Dr. Nayak presents the measurements and simulations…

Pareto-optimal cycles for power, efficiency and fluctuations of quantum heat engines using reinforcement learning  

Paolo Andrea Erdman, Alberto Rolandi, Paolo Abiuso, Martí Perarnau-Llobet, Frank Noé

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Quantum Computing Is Coming. What Can It Do?

• Francesco Bova,
• Avi Goldfarb,
• Roger Melko

A guide to the next computer age.

Digital computing has limitations in regards to an important category of calculation called combinatorics, in which the order of data is important to the optimal solution. These complex, iterative calculations can take even the fastest computers a long time to process. Computers and software that are predicated on the assumptions of quantum mechanics have the potential to perform combinatorics and other calculations much faster, and as a result many firms are already exploring the technology, whose known and probable applications already include cybersecurity, bio-engineering, AI, finance, and complex manufacturing.

Quantum technology is approaching the mainstream. Goldman Sachs recently announced that they could introduce quantum algorithms to price financial instruments in as soon as five years. Honeywell anticipates that quantum will form a $1 trillion industry in the decades ahead. But why are firms like Goldman taking this leap — especially with commercial quantum computers being possibly years away?

• FB Francesco Bova is a professor at the University of Toronto’s Rotman School of Management in Toronto and is the academic lead and lab economist for the quantum stream in Rotman’s Creative Destruction Lab.
• Avi Goldfarb is the Rotman Chair in Artificial Intelligence and Healthcare at the Rotman School of Management, University of Toronto. He is also the chief data scientist at the Creative Destruction Lab and a co-author of Power and Prediction: The Disruptive Economics of Artificial Intelligence (Harvard Business Review Press, 2022).
• RM Roger Melko is a professor in theDepartment of Physics and Astronomy, University of Waterloo in Ontario, and holds a Canada Research Chair in Computational Many-Body Physics.  He is also an associate faculty member at the University’s Perimeter Institute for Theoretical Physics and Creative Destruction Lab.

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Quantum computers can accelerate the transition to net zero power grids

Associate Professor in Power Systems, Department of Engineering Science, University of Oxford

Disclosure statement

Thomas Morstyn receives research funding from the UK Engineering and Physical Sciences Research Council (EPSRC), Innovate UK, Outlook Energy and IONATE. The research this article is based on was supported by EPSRC (ref. EP/Y004418/1).

University of Oxford provides funding as a member of The Conversation UK.

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Power grid operators, such as National Grid in the UK, rely on high-performance computers to plan grid expansions and to schedule when energy should be produced from different sources. These problems are becoming larger and more complex due to the transition to net zero carbon emissions, and they are now reaching the limits of even the world’s largest supercomputers.

Quantum computing opens up a new avenue for progress. My research group at the University of Oxford investigates how quantum computing can offer value for the net zero transition. My colleague Xiangyue Wang and I recently published a paper in the journal Joule that identifies promising opportunities for quantum computing to help optimise the planning and operation of net zero power grids.

Over the next five years, National Grid plans to spend £30 billion on updating power grid infrastructure as part of the UK’s transition to a decarbonised grid. Large investments are also planned for low-carbon technologies , including wind, solar, nuclear and batteries. Additionally, millions of electric vehicles (EVs) and heat pumps will be added to local distribution networks to decarbonise transport and heating.

Planning decisions, including where to build renewables, when to upgrade electrical transmission lines, and how to roll out EV chargers, will directly affect how high our energy bills are, how often people experience power cuts and how quickly the UK can achieve its net zero targets. With billions being invested in the grid, it is crucial that grid planners understand how to spend this money wisely.

Read more: How long before quantum computers can benefit society? That's Google's US$5 million question

In addition to grid planning, operating a net zero grid is also a challenging optimisation problem because grid power flows must match demand while remaining within safe limits at all times. Otherwise, the grid risks power outages. This is becoming more difficult because of the variability and uncertainty of wind and solar generation.

Another challenge is the electrification of transport and heating, which concentrates demand when people arrive home from work. One solution is to adjust when EVs are charged and when heat pumps are run. Small shifts in usage, added up across millions of homes, can be equivalent to the output of large power plants . However, this significantly increases the number of devices on the grid that need to be scheduled, making scheduling much more difficult.

The race to innovate

In 2019, Google demonstrated quantum supremacy – solving a problem that no classical computer could solve in any feasible amount of time – by completing a physics simulation problem in 200 seconds. That same problem would have taken an equivalent classical supercomputer 10,000 years to solve using the best algorithm known at the time. This kicked off an ongoing race between researchers working on expanding the limits of both classical and quantum computing . Quantum computers are now reaching the scale and maturity where they can offer tangible value for industries including pharmaceuticals and finance .

Classical computers store information in strings of bits, where each bit has a value of 0 or 1. Logical operations on bits are used for computation. Within a quantum computer, the basic unit of information is instead the quantum bit or “qubit”. Qubits can be built in a variety of ways, for example using superconducting circuits or atoms trapped by lasers.

When measured, a qubit will read as a 0 or 1 just like a classical bit. However, within a quantum computer, qubits can be controlled using the principles of quantum physics –the laws governing the behaviour of subatomic particles. This lets quantum computers represent large amounts of classical information with only a few qubits and perform specific types of calculations that are practically impossible for classical computers.

Researchers describe quantum computing as being in the noisy intermediate scale quantum (NISQ) era. Large, general-purpose quantum computers are expected to remain out of reach for at least a decade . However, NISQ devices already show promise for combinatorial grid optimisation problems. These are problems with interlinked yes-or-no decisions that create an exponentially large set of possibilities, such as deciding where to build new generators, which transmission lines to upgrade and which specific power plants to start up or shut down.

There are also a wider set of opportunities where quantum computing is underexplored. Quantum computing could speed up the simulation and optimisation of grid power flows. It could also accelerate machine learning – the use of algorithms that improve their performance when exposed to data. This could help grid operators make use of high-volume smart meter data to improve forecasting, scheduling and planning. With small NISQ devices, a promising approach is to team them up with large classical computers and use them to accelerate specific parts of complex algorithms which are most suited to quantum computation.

Despite the early stage of power grid quantum computing research, there are already industry initiatives underway to develop quantum algorithms that could enable grid expansion and intelligent scheduling of EV charging .

Given the goal of decarbonisation, the energy needed for quantum computers is a potential concern , particularly the energy for cooling, since quantum computers often require extremely low temperatures ( near absolute zero or -273.15°C ) for reliable operation. However, research indicates that when a quantum computer can solve a problem using many fewer operations than a classical computer this can also save energy. For example, Google’s quantum supremacy demonstration not only massively increased the speed of computation, but also reduced energy use by a factor of 557,000.

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Notre Dame Professor Jankó and collaborators receive Army grant for Quantum Computing Research

Published: August 06, 2024

Author: Deanna Csomo Ferrell

Boldizsár Jankó , physics professor at the University of Notre Dame, and collaborators have received a grant from the Army Research Office, a directorate of the U.S. Army Combat Capabilities Development Command Research Office, for research on vortex manipulation in superconductors — a process that will be necessary to advance quantum computing technology in the future.

Superconducting circuits can conduct electricity without any resistance in cold temperatures. However, they can contain tiny magnetic whirlpools, called vortices, that are destructive, much like tornadoes.

"When these superconducting vortices — these tiny filaments or tornadoes — get stuck in the device, just a few of them will basically render the device useless,” said Jankó, who has been studying vortices throughout his career. “The operation margins shift, and the device just doesn't work well."

The grant will span four years and is divided between Jankó, who is the principal investigator in charge of the project, and six co-principal investigators from Notre Dame, Argonne National Laboratory in Lemont, Illinois; Northern Illinois University, in DeKalb, Illinois; the University of Bath in Bath, England; and the University of Antwerp in Antwerp, Belgium.

The project calls for the addition of three postdoctoral scholars at Notre Dame. Two will be theoretical physicists, and one will be an experimentalist who will be based at Argonne.

Using computer simulations and experiments, Jankó and his team will design and test new types of circuits with specific patterns that can control and remove the tiny magnetic whirlpools. The work will involve adding new device features that will actively remove the vortices without the costly and time consuming thermal cycling. Their work should lead to significant improvements in the circuits that will increase their applications.

Using microscopy is key as the researchers map the surface of samples. The team at the University of Bath, led by physics professor Simon Bending, will use a novel form of scanning probe imaging called scanning Hall probe microscopy.

“By mapping the surface of samples with a nanoscale Hall sensor at cryogenic temperatures we can image vortices and vortex patterns and follow their dynamics under various driving currents and driving fields,” Bending said. “In this way we plan to visualize experimentally the effects that the theoretical collaborating groups will be predicting and simulating, allowing new generations of more effective chip designs to be developed.

The project began in March. In addition to the three postdocs hired at Notre Dame, four more will be hired elsewhere, along with six graduate students. Two research professors — Alexei Koshelev and Vitalii Vlasko-Vlasov — were appointed at Notre Dame after the grant was awarded.

Despite the technical challenges, Jankó, who is affiliated with the Institute for Theoretical Sciences , the Stavropoulos Center for Complex Quantum Matter and Notre Dame Energy, and other collaborators remain optimistic about the project's potential.

“The goals of the project are very clear and feasible, and simulations are already underway. What may be the most exciting part of the work will be the integration of our concepts in an actual device of relevance to the current technology, which we hope to achieve in collaboration with the Lincoln Laboratory (at the Massachusetts Institute of Technology),” said Milorad Milošević , professor in the Department of Physics at the University of Antwerp, who is one of the project’s co-principal investigators.

Other researchers on the project include Andreas Glatz of Argonne National Laboratory and Northern Illinois University and Zhili Xiao of Northern Illinois University.

“By providing support for our project, the Army Research Office will allow us to push to an unprecedented level the complexity and accuracy of the numerical simulations and characterization of superconducting vortex matter in devices,” Jankó said. “This is not an overstatement: the members of our team are already leaders of the field. With this ARO project, we hope to provide substantial, tangible improvements for superconducting logic devices.”

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New cooling technology developed for quantum computing circuits

by National Physical Laboratory

Typical superconducting quantum circuits, such as qubits—basic processing units of a quantum computer, must be operated at very low temperatures, of a few 10s of millikelvin, or hundredths of a degree from absolute zero temperature. These temperatures are today easily accessible in modern refrigerators. However, the intrinsic temperature of devices turns out to be much higher because the materials required to make good qubit circuits are by their nature very poor thermal conductors. This thermalization problem becomes more and more acute as the scale and complexity of circuits grow.

Much like water (or liquid nitrogen ) cooling is sometimes used to effectively cool down high-performance digital computers, a quantum computer could benefit from similar liquid cooling. But at the very low temperatures that quantum circuits operate, most liquids will have turned into ice. Only two isotopes of Helium, Helium-3 and Helium-4, remain in the liquid form at millikelvin temperatures.

In recent work published in Nature Communications , researchers from the National Physical Laboratory, Royal Holloway University of London, Chalmers University of Technology and Google developed new technology to cool down a quantum circuit to less than a thousand of a degree above absolute zero, almost 100 times lower temperature than achieved before. This was made possible by immersing the circuit in liquid 3 He, chosen for its superior thermal properties.

Remarkably, the researchers observed that 3 He couples very strongly to atomic-scale defects in the quantum circuit material and takes away excess energy from these defects more than 1,000 times faster compared to when 3 He is not present. Crucially, at the same time the 3 He does not directly interfere with the circuit itself. Furthermore, the research showed that the noise in the present experiment was also reduced more than 1,000 times at the lowest temperatures using 3 He immersion, compared to extrapolated theoretical predictions.

This mechanism, when optimized, has the potential to improve coherence of quantum circuits significantly. In particular, it may be able to fundamentally change the behavior of the noisy environment, silence it and improve coherence of the circuits even further. The noise and energy losses caused by these material defects is currently the main obstacle the field is facing towards scaling to practical quantum computers.

"Improving the coherence that is spoiled by material defects is the biggest challenge quantum computing is facing to scale up and build practical quantum computers. Going to these extremely low temperatures allows us to study the fundamental physics of quantum circuits in greater detail, and we're hopeful that the knowledge obtained in this way will help us improve the coherence of the circuits also when operated at the easily achievable temperatures of 10s of mK in typical refrigerators used today," said NPL's Sebastian de Graaf.

"Cooling devices down to ultra-low temperatures is a significant technological challenge. In the present study we have solved many technical challenges to reach this goal, and our results demonstrate the benefits of doing so on the performance of the circuits. Moreover, we are confident this technology can be scaled up to immersion-cool much larger quantum circuits to benefit future quantum computing developments," said Professor John Saunders, director of the London Low Temperature Laboratory at Royal Holloway University of London.

Journal information: Nature Communications

Provided by National Physical Laboratory

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California NanoSystems Institute > News > July 31, 2024 | UCLA RESEARCH BRIEF: Layered superconductor coaxed to show unusual properties with potential for quantum computing

Layered superconductor coaxed to show unusual properties with potential for quantum computing

UCLA RESEARCH BRIEF

This article was originally published by UCLA Newsroom

A team led by researchers from the  California NanoSystems Institute at UCLA  designed a unique material based on a conventional superconductor — that is, a substance that enables electrons to travel through it with zero resistance under certain conditions, such as extremely low temperature. The experimental material showed properties signaling its potential for use in quantum computing, a developing technology with capabilities beyond those of classical digital computers.

Conventional superconductors usually fail under magnetic fields of a certain strength. The new material continued to retain superconducting properties under a much higher magnetic field than the theoretical limit of a conventional superconductor. The team also measured how large an electrical current the new material can accommodate before it breaks superconductivity, applying electricity from one direction and then again from the opposite direction. The researchers found that one direction allowed notably higher current than the other. This is often referred to as the superconducting diode effect. In contrast, conventional superconductors would lose their zero-resistance property at equal current from either direction.

Quantum computers operate based on the counterintuitive rules that govern how subatomic particles interact. The basic unit of information in quantum computing, the qubit, can have a multitude of values. Meanwhile, the bit — the basic unit of information in classical computing — can only have one of two values.

While quantum computers could perform calculations that traditional computers cannot, the technology is still in its early days, with obstacles left to overcome before realizing its promise. One such obstacle is the fragility of the qubit. Minor changes in conditions can cause qubits to lose their quantum properties, which last only millionths of a second.

Researchers have theorized that an unconventional type of superconductor, called a chiral superconductor, may help increase qubits’ ability to maintain accuracy while performing a program’s steps.

Both chiral and conventional superconductors depend on quantum phenomena. Pairs of electrons become linked at a distance in a state known as entanglement, which imposes certain rules upon the properties of the electrons. In conventional superconductors, to abide by these rules, entangled electrons move in opposite directions and spin in opposite directions. In chiral superconductors, entangled electrons could spin in the same direction, and they have to abide by rules that make the relationship between their motion extremely complex, potentially opening new possibilities for tailoring the flow of current or processing information.

As an upshot of this contrast, the activity of electrons in conventional superconductors display symmetries that are broken in chiral superconductors, which favor flow in one direction over the other, as seen in the superconducting diode effect. Today, only a few compounds are candidates for chiral superconductivity, and they are extremely rare. In the current study, the researchers found a way to customize their material to coax a conventional superconductor to act like a chiral one.

The UCLA-led team created a lattice with alternating layers. One layer made of tantalum disulfide, a conventional superconductor, was as thin as three atoms. The next was made of a “left-handed” or “right-handed” molecular layer of a different compound. The investigators tested tiny nanoscale devices made from their lattice to evaluate whether the material showed the properties of a chiral superconductor.

Quantum computing may yield innovations such as unbreakable cybersecurity, supercharged artificial intelligence and high-fidelity simulations of phenomena, from the action of drugs in the body to the flow of city traffic to the fluctuations of financial markets. To get to those applications, quantum computers will need to make leaps in their ability to function despite potential disturbances to fragile qubits. Superconducting circuits are foundational to many quantum computing approaches, and the superconducting diode effect achieved by chiral superconductors is expected to be useful for creating more efficient and stable qubits.

In addition to its utility for quantum computing, chiral superconductors’ superconducting diode effect could make conventional electronics and communication technologies operate much faster while minimizing energy consumption. These qualities are particularly well suited for specialized applications such as computers working at extremely low temperatures in deep space.

Because chiral superconductors have been so difficult to find, engineering them from more readily available ingredients — such as in the new hybrid material reported in this study — could help unlock quantum computing’s potential while also driving improvements to electronic devices.

The study’s corresponding authors are CNSI members  Yu Huang , Traugott and Dorothea Frederking Endowed Professor and chair of the materials science and engineering department at the  UCLA Samueli School of Engineering ;  Kang Wang , Raytheon Company Professor of Electrical Engineering and a distinguished professor of electrical and computer engineering and of material science and engineering at UCLA Samueli; and  Xiangfeng Duan , a professor of chemistry and biochemistry at the  UCLA College . The study’s co-first authors are Zhong Wan, a UCLA postdoctoral researcher, and Gang Qiu, a former UCLA postdoctoral researcher now on the faculty of the University of Minnesota. Other co-authors are Huaying Ren, Qi Qian, Yaochen Li, Dong Xu, Jingyuan Zhou, Jingxuan Zhou, Boxuan Zhou, Laiyuan Wang and Ting-Hsun Yang, all of UCLA; and Zdeněk Sofer of the University of Chemistry and Technology, Prague.

DISCLOSURES

There are no disclosures associated with this research.

The study was published in the journal  Nature.

The study was supported by the U.S. Office of Naval Research and Army Research Office as well as the Czech Republic’s Ministry of Education, Youth and Sports and Advanced Functional Nanorobots project.

Download a PDF of this article here. 

Thursday, August 08, 2024

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UMD and IonQ Partner to Advance Quantum Computing in Support of National Security

Discovery District-Based Project Aims to Help New Breed of Computers Further Mature

By Maryland Today Staff Aug 06, 2024

UMD will work with the quantum computing hardware and software firm IonQ, based in the university's Discovery District, to advance quantum computing and enable it to contribute to national security.

Illustration by iStock

The University of Maryland and a College Park-based leading firm in quantum computing are collaborating on a new system to advance the use of quantum computers in national security, the university announced Tuesday.

UMD’s Applied Research Laboratory for Intelligence and Security ( ARLIS ) selected IonQ , a leading quantum computing hardware and software company, for the $5.7 million contract for initial work on the project, with a potential second phase worth up to $12 million. The groundbreaking system will be based at ARLIS, which like IonQ is located in UMD’s Discovery District.

“The purpose of the project is to help mature quantum computers to the point where they reliably support national security,” said Craig Lawrence, interim executive director of ARLIS, a Department of Defense University Affiliated Research Center dedicated to intelligence and security in the human domain. “There is significant research and development that is needed before the defense and intelligence community can reach that goal.”

The University of Maryland has long been a global center of excellence in quantum science and computing, and is home to one of the laboratories out of which IonQ emerged. Under the new agreement with ARLIS, IonQ will design and build a two-node quantum computing system that will enable hands-on research into multi-party quantum algorithms and the cybersecurity of quantum computation. In some experiments, the system will use blind quantum computing protocols to shield the information processed through them from observation.

This effort began in 2023 with an $18 million award to the University of Maryland by the Secretary of the Air Force Concepts, Development, and Management Office that helped ARLIS to begin work on the current project, known as Securing Experimental Quantum Computing Usage in Research Environments (SEQCURE). The project follows a 2022 national security memorandum issued by the White House to outline the steps needed to maintain the country’s competitive advantage in quantum information science. The guidance also calls for mitigating future risks of quantum computers to the nation’s cyber, economic and national security.

The SEQCURE project has multiple milestones that include several design, security, technical and algorithm reviews before the end of 2024, with an optional second phase of work starting next year.

Cybersecurity National Security Quantum Science Research

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Researchers at MIT recently signed a four-year collaboration agreement with the Novo Nordisk Foundation Quantum Computing Programme (NQCP) at Niels Bohr Institute, University of Copenhagen (UCPH), focused on accelerating quantum computing hardware research.

The agreement means that both universities will set up identical quantum laboratories at their respective campuses in Copenhagen and Cambridge, Massachusetts, facilitating seamless cooperation as well as shared knowledge and student exchange.

“To realize the promise of quantum computing, we must learn how to build systems that are robust, reproducible, and extensible. This unique program enables us to innovate faster by exchanging personnel and ideas, running parallel experiments, and comparing results. Even better, we get to continue working with Professor Morten Kjaergaard, a rising star in the field, and his team in Copenhagen,” says William Oliver, the Henry Ellis Warren (1894) Professor within the MIT Department of Electrical Engineering and Computer Science (EECS), professor of physics, associate director of the Research Laboratory of Electronics, and the head of the Center for Quantum Engineering at MIT.

Oliver’s team will supervise the funded research, which will focus specifically on the development of fault-tolerant quantum computing hardware and quantum algorithms that solve life-science relevant chemical and biological problems. The agreement provides 18 million Danish kroner (approximately $2.55 million) from the Novo Nordisk Foundation Quantum Computing Program to support MIT’s part in the research.

“A forefront objective in quantum computing is the development of state-of-the-art hardware with consistent operation,” says Maria Zuber, MIT’s presidential advisor for science and technology policy, who helped facilitate the relationship between MIT and the Danish university. “The goal of this collaboration is to demonstrate this system behavior, which will be an important step in the path to practical application.”

“Fostering collaborations between MIT and other universities is truly essential as we look to accelerate the pace of discovery and research in fast-growing fields such as quantum computing,” adds Anantha Chandrakasan, chief innovation and strategy officer, dean of engineering, and the Vannevar Bush Professor of EECS. “The support from the Novo Nordisk Foundation Quantum Computing Programme will ensure the world’s leading experts can focus on advancing research and developing solutions that have real-world impact.”

“This is an important recognition of our work at UCPH and NQCP. Professor Oliver’s team at MIT is part of the international top echelon of quantum computing research,” says Morten Kjaergaard, associate professor of quantum information physics and research group leader at the Niels Bohr Institute at UCPH. “This project enables Danish research in quantum computing hardware to learn from the best as we collaborate on developing hardware for next-generation fault-tolerant quantum computing. I have previously had the pleasure of working closely with Professor Oliver, and with this ambitious collaboration as part of our the Novo Nordisk Foundation Quantum Computing Programme, we are able to push our joint research to a new level.”

Peter Krogstrup, CEO of NQCP and professor at Niels Bohr Institute, follows up, “We are excited to work with Will Oliver and his innovative team at MIT. It aligns very well with our strategic focus on identifying a path with potential to enable quantum computing for life sciences. The support aims to strengthen the already strong collaboration between Will and Morten’s team, a collaboration we hope to make an important part of the NQCP pathfinder phase over the coming years.”

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