This year will be a big one for quantum computing, at least according to the United Nations: 2025 is officially the “International Year of Quantum Science and Technology,” a worldwide initiative to raise awareness of technological progress and encourage new advances.
It also coincides with the 100th anniversary of the birth of modern quantum mechanics, which has given us everything from lasers to rare-earth magnetics, the internet to global navigation. The modern world would look very different without quantum science.
But we’ve only scratched the surface of what’s possible. Although the technology is still nascent in many forms, quantum computing could change life as we know it.
Quantum technologies could transform medicine and artificial intelligence, and have the potential to be used for applications ranging from financial modeling to cryptography, designing new materials for superconductors and better batteries, and accelerating machine learning.
But what exactly is quantum computing? And does it matter beyond the realms of brainiacs in laboratories?
Unlike classical computers, which use binary digits (or bits), representing information as either 0 or 1, quantum computers use quantum bits, or qubits, which can exist as both zeroes and ones at once. This means it can solve complex problems at an exponentially faster rate.
Think of it like a mouse trying to find its way through a maze. With classical computers, the metaphorical mouse has to try each and every path, eliminating every possibility until it finds the correct one and the eventual way out.
With quantum computing, the mouse gets supercharged and is able to try every possible pathway simultaneously. It’ll find the exit in a fraction of the time.
That means scientific discoveries could happen faster, in weeks or days rather than decades. The prospects are so promising that companies across the globe are scrambling for a piece of the pie.
Earlier this week, IBM announced that it would be investing $30 billion over the next five years to develop quantum computers. Amazon has already introduced cloud-based quantum computing access for early adopters.
Chinese retail giant Alibaba is constructing its own quantum data center, while the Chinese government is constructing a $10 billion national facility for quantum research in the city of Hefei. In total, some estimates have the global quantum computing market reaching $125 billion by 2030, with North America the largest current market, but Asia the biggest in terms of growth, according to a January 2023 Precedence Research report. (Oddly, Colorado currently boasts the largest concentration of quantum computing companies and facilities in the world thanks to early research efforts at the University of Colorado.)
One of the biggest quantum developments so far this year was recently published in the journal Science. D-Wave Systems, a company based in Palo Alto, Calif., used quantum computing to simulate properties of magnetic materials, like the kind used in smartphones and medical imaging devices.
Their results were “beyond the scale of what can be done with classical approaches,” Trevor Lanting, D-Wave’s chief development officer, told The Post. “We believe we’re the first and the only organization in the world to demonstrate quantum supremacy on a real-world problem.”
According to their findings, a quantum computer was able to complete the magnetic materials simulation in just under 20 minutes. “That same problem would’ve taken a state-of-the-art classical computer, like one of the world’s leading supercomputers at Oak Ridge National Laboratory, almost a million years to do,” says Andrew King, one of D-Wave’s senior scientists.
If true, it could mean we’re on the path to faster research and scientific discovery. “This is the promise of quantum computing realized,” says Lanting. “This is why huge corporations are investing in quantum computing technologies.”
But not everybody in the science community is ready to give D-Wave its accolades. Some labs are hitting back with their own experiments, proving that classical computers can still hold their own against quantum computers. Indeed, the United Nations may be promoting a year of quantum science goodwill, but at laboratories and institutions around the world, the battle is brewing for quantum supremacy.
Joseph Tindall, a quantum physics researcher at the Flatiron Institute, for instance, led a study in March as a direct response to D-Wave, performing similar calculations to their test on a plain old laptop and getting the same results in just two hours. Not lightning fast, but a far cry from a million years.
“[D-Wave] certainly obtained some impressive results on multiple complex problems, and I really don’t want to undersell that,” Tindall told The Post. “It’s more that their claims of ‘supremacy’ or ‘we did something that would take millions of years on a supercomputer’ are not really true and far more nuanced than that.”
Miles Stoudenmire, another research scientist involved in the Flatiron Institute, says part of the problem with D-Wave’s supremacy claim is how fast science moves in modern times. “Their comparisons were based on state-of-the-art classical methods at the time the work was done [in 2024],” he told The Post. D-Wave underestimated classical computing by assuming that their algorithms would be static and unchanging, like challenging a Honda owner to a car race and assuming the car company hadn’t made any upgrades since the Model T.
“Firmly establishing quantum advantage is a tricky business,” adds Dries Sels, a physics professor at New York University.
King at D-Wave just shrugs his shoulders at these criticisms. “Everybody loves a controversy,” he says. But he continues to believe that we’ve just seen the beginning of what’s possible with quantum supremacy. It’s true that science is always catching up to itself, and “the boundary of what we considered easy gets pushed forward and eats up our results,” he says. But while the goalpost may change, the speed and efficiency of their machine don’t.
D-Wave isn’t the first to stake a claim on “quantum supremacy.” The grandiose-sounding concept has been around for just over a decade. It was first coined by Caltech theoretical professor John Preskill, who hoped to “hasten the day when well-controlled quantum systems can perform tasks surpassing what can be done in the classical world.”
In 2019, Google introduced Sycamore, a quantum computer capable of calculations that would take 10,000 years to run on the world’s leading supercomputer. But those bragging rights were lost last year, when researchers from the Shanghai Artificial Intelligence Laboratory in China completed the same task on a conventional computer in just 14.22 seconds.
Google tried again last December with Willow, a 105-qubit superconducting quantum computing processor that can allegedly perform a computation in five minutes that would take most computers 10 septillion years.
Researchers at the University of Science and Technology of China also developed a “quantum supremacy”-capable computer last year, a 105-qubit chip prototype named the Zuchongzhi 3.0, which they claimed was one quadrillion times faster than the best supercomputers on the planet.
But even with those impressive numbers, Filippo Vicentini, a professor of AI and condensed-matter physics at the École Polytechnique in Palaiseau, France, warns that companies may be “overselling and overly exaggerating the implications and impact of the milestones they achieve and of what they think they will be able to do.”
What’s more, the resources needed to build and operate a quantum computer are a huge drawback, with costs running in the “tens of billions of dollars,” according to computer hardware manufacturer SEEQC.
“One has to weigh that against their speed and other benefits,” says Stoudenmire.
Still, with the billions being poured into AI right now, a similar investment stream into quantum computing could be forthcoming if it proves as effective.
Stoudenmire also insists it’s too soon to give up on classical computers. There’ve been significant changes in the development of classical algorithms in recent years. They’re faster than ever, at a fraction of the cost of quantum computers.
For now, at least, the big advantage of quantum computers is generating “solutions to certain large problems very rapidly,” says Tindall. The benefit here is scale — even if it comes, like all emerging technologies, with drawbacks.
“Currently, all quantum devices are imperfect, and they make errors that are not yet fully correctable. This means their solutions to problems are only approximate.”
Vicentini, despite his skepticism of the “supremacy” claims, says he’s optimistic for the future of quantum platforms. The next five years could see “a paradigm shift in the field of computational quantum sciences,” Vicentini says. “It’ll just be a much slower development than what companies argue.”
But Lanting at D-Wave promises that more advances are coming, and they’ll be anything but slow.
“Later this year, we’re looking to launch larger-scale processors, with 4,000 to 4,400 qubits.” (By comparison, IBM’s “Condor” processor, introduced in 2023, had 1,121 superconducting qubits.) “You’re going to see an increasing number of more complicated and sophisticated quantum computing results,” Lanting says.
If D-Wave accomplishes even half of what they have planned, the UN’s International Year of Quantum Science will have more than lived up to its name.
