When Will Quantum Computers Outperform Regular Computers?

Any day now, quantum computers will solve a problem too hard for a classical computer to take on. Or at least, that’s what we’ve been hoping. Scientists and companies are racing toward this computing milestone, dubbed quantum supremacy and seemingly just beyond our reach, and if you’ve been following the quantum computing story, you might wonder why we’re not there yet, given all the hype.

The short answer is that controlling the quantum properties of particles is hard. And even if we could use them to compute, “quantum supremacy” is a misleading term. The first quantum supremacy demonstration will almost certainly be a contrived problem that won’t have a practical or consumer use. Nonetheless, it’s a crucial milestone when it comes to benchmarking these devices and establishing what they can actually do. So what’s holding us back from the future?

“We’re about to cross over into a world where we’re doing something with quantum devices that we couldn’t do classically,” John Preskill, professor of theoretical physics at the California Institute of Technology who devised the term “quantum supremacy,” told Gizmodo. “We’re at a pivotal stage.”

You might first wonder what a quantum computer is—or, fundamentally, what a computer is. Computers are devices that abstract data and store it as inputs, which they manipulate via a system of instructions and mathematical algorithms. Typically, the data is stored as manipulatable bits, two-choice physical devices, allowing systems of these bits to produce some desired output. On quantum computers, algorithms are mapped onto a different kind of architecture; instead of bits, there are two-choice devices called qubits that obey the weird rules of quantum mechanics.

Each qubit is sort of like two-sided dice that you can load with an iron piece to adjust the probability you’ll roll either side. Performing a quantum calculation is like rolling the dice. But you can entangle the qubits, which is like magnetizing the iron pieces so that the dice must be treated as a single multi-sided dice with its own set of probabilities. This might lead to interference—making certain sides of the dice more likely to roll, and other sides less likely. Quantum calculations apply gates to these dice—pulses of energy that further influence the position of the weight inside the dice and change what you’ll roll. Applications involve mapping some piece of information to each side, and often require many dice rolls in order to achieve interesting results.


Scientists and technology companies are pursuing quantum computers both for their innate scientific interest as envelope-pushing experiments and for the way they might impact artificial intelligence, cybersecurity, and healthcare. Presumably, there are some algorithms that would work faster running on this quantum architecture than they would on a classical computer, most notably Shor’s algorithm, which could factor extremely large numbers faster than classical computers can. An algorithm that can quickly factor numbers is important because most of our modern-day encryption is based on the premise that classical computers can easily multiply two numbers together but take an unreasonably long time to factor them back apart. A computer that could run Shor’s algorithm would render this encryption strategy unsecure. Others hope that quantum computers will find applications in artificial intelligence, such as in quantum neural networks, or help solve chemistry problems, like finding new drugs to cure diseases, much more efficiently than classical computers.

But a quantum computer worth getting excited about—or worrying about—should be better than regular computers doing the same task. That’s why scientists and companies, most notably Google, list quantum supremacy as a key milestone for their devices.

Proposals for quantum supremacy generally follow the same premise. Set up complicated, random quantum circuits and measure the values. You get a lot of answers. Now, use a statistical test to ensure that the experiment was done properly using these outputted answers. Theoretical physicists think that a quantum computer would demonstrate supremacy on such a task—basically, as the problem increases in complexity, the amount of time it takes to calculate the problem would increase at a higher rate for a classical computer than a quantum computer.

From a business standpoint, the task seems contrived. Quantum supremacy demonstrates that a quantum computer is better at being a quantum computer than a classical computer is. That’s not something you can cure diseases with.

But from a theoretical perspective, it’s profound, Bill Fefferman, assistant research professor at the University of Maryland and research scientist at the National Institute of Standards and Technology, told Gizmodo. There’s a hypothesis called the Church-Turing thesis stating that any computer problem can be solved with an abstract kind of computer devised by mathematician Alan Turing in 1936. This theoretical computer simplifies all computing problems to symbols on tape. Then, there’s the extended Church-Turing thesis—that no practical model of computing could solve tasks significantly faster than one of these Turing machines. Theoretical computer scientists gave strong evidence that the extended Church-Turing thesis was wrong in the early 1990s. And a machine that achieves quantum supremacy would prove the thesis wrong in experimentally. It would demonstrate that there really are computer problems for which a supercomputer wouldn’t be the most efficient way to calculate them, and for which a computer based on a different architecture, a quantum computer, would be.


Quantum supremacy, from a scientific perspective, is meant to give scientists a concrete way to determine what a quantum computers will and will not be useful for, and to compare them against classical computers. Up until the early 1990s, theoretical computer scientists devised contrived problems for quantum computers, and useful tasks, like Shor’s algorithm, came later. “Instead of saying ‘you guys are spending billions of dollars to implement this contrived problem,’ the answer is that we have to first build the foundations,” Fefferman said.

It’s also not inherently useless, as the experiment could make quantum computers useful random number generators, which find applications in cryptography, gambling, simulations, and elsewhere.

But how do you actually hit that milestone? Google has enlisted the help of NASA in its quest to be first, MIT Technology Review reported last year. The team is building and testing a chip with what they hope will be enough good qubits to demonstrate quantum supremacy. There are researchers studying these same quantum supremacy problems on classical computers to compare, as well as working on computational theory to ensure rigorous proof that supremacy was achieved.

With the considerable resources and minds of NASA, Google, IBM, and other organizations on the case, you might wonder what’s taking so long. For now, the largest commercial quantum devices have around 20 qubits, though IBM, Google, and IonQ are testing 50-, 72-, and even 160-qubit devices, respectively. But every step of building and operating a quantum computer is hard. Instead of silicon transistors on microchips, scientists must create their devices either out of lasers that trap individual atoms, superconducting material that conducts current without resistance that demonstrates manipulatable quantum properties, or other potential architectures. This often requires holding the processor at nearly absolute zero—the temperature at which particles have the minimum possible heat. Controlling this system proves incredibly difficult, since a modicum of energy from the outside environment could cause the qubits to collapse into very expensive, very regular bits.

On these limited systems, researchers can only perform a handful of quantum operations, or “gates,” before the quantum state collapses. Entangling too many qubits will make the system collapse. Each additional qubit makes the machine twice as complex. Electromagnetic pulses that control the system must be perfectly engineered.


At the same time, quantum computer scientists aren’t just trying to beat classical computers simulating quantum computers. They’re trying to beat any possible workaround that someone programming a classical computer can come up with, which is harder to prove. And researchers will need to somehow verify the result that the quantum computer calculated, even though they would have just performed a calculation that a non-quantum computer can’t do.

“I bet someone is going to declare [quantum supremacy] soon,” Graeme Smith, assistant professor at the University of Colorado, Boulder, told Gizmodo, “But there will be questions about whether they achieved it because of the fact that it’s hard to verify.”

Perhaps you’re noticing a pattern here. No one has achieved quantum supremacy yet because it’s hard.

IBM’s scientists are working on a perhaps easier-to-achieve task. They’re trying to demonstrate “quantum advantage.” The difference is subtle. Quantum supremacy means that a quantum computer can perform calculations that a classical computer cannot in a reasonable amount of time. Quantum advantage just means that the quantum computer can beat the classical computer at some calculation, even if it’s just a little better. Some researchers have devised mathematical proofs of cases where quantum computers are always better than classical computers running the same algorithm. But in this case, the classical computer was given a similar limitation to one of the core present-day quantum computer limitations: it could only perform a few operations at a time, like a qubit, which can only perform a few operations until it collapses.

Quantum advantage has one leg over quantum supremacy, though. Quantum supremacy is a high bar to achieve, but if the industry is solely looking for a faster algorithm, then these quantum advantages might find quantum computers a more general use in industry sooner.

For companies like Google and IBM, these terms are tossed around with a heavy does of PR. “They’re both trying to build programmable quantum computers,” Aram Harrow, associate professor of physics at MIT, told Gizmodo. “Google will say that the goal is supremacy, IBM will say that the goal is advantage. That’s not going to lead to a big difference in the hardware that gets built.”


Ultimately, when a company building a quantum computer inevitably announces that it has achieved “quantum supremacy” or “quantum advantage,” it won’t be a sea change for the industry. They’ll still be referring to relatively small, error-prone devices—what researchers call NISQ, or “noisy intermediate-scale quantum” machines. These machines will still face the same limitations they did before a supremacy or advantage device existed, such as the short amount of time qubits can stay quantum or lower number of calculations a qubit can do before losing its quantum nature.

“Quantum supremacy is a stepping stone for us to move forward in order to solve more interesting problems,” Mekena Metcalf, postdoctoral researcher at Lawrence Berkeley National Laboratory, told Gizmodo. But for quantum computers to become the code-cracking, molecule-simulating devices of the future, there are specific goals on the horizon. “It requires orders of magnitude more qubits and long gate depth,” she explained—qubits that can do more calculations before losing their quantum behavior.

Reaching that state will require better hardware, including more precise optics for quantum computers based on laser-trapped atoms, Sara Mouradian, postdoctoral researcher at UC Berkeley, told Gizmodo. Those working on superconducting quantum computers are hoping to see improvements to the system’s wires and better control overall. Both systems will need to find ways to vastly increase in scale and size, which is not as easy as adding more bricks to a Lego tower. Quantum computers will also require error correction, or storing the information from a single qubit across multiple entangled physical qubits in order to correct for possible errors.

The NISQ-era devices are still boundary-pushing tools for studying quantum physics, and perhaps they’ll find useful applications in the near term, whether they demonstrate “quantum supremacy,” “quantum advantage,” or even just “quantum usefulness.” There are plenty of other quantum devices in the works as well, like sensors and cryptographic tools, that might find applications sooner.

But, for startup funding’s sake, hopefully scientists and technologist demonstrate quantum supremacy (or advantage) and find useful quantum computer applications soon.

“What looms over the field, particularly on the commercial side, is all of these companies investing and building systems—but if they can’t come up with a useful application in 10 years, what happens then?” Preskill said. “Is there going to be a quantum crash because people felt that the potential wasn’t realized?” At least for now, the U.S. government has passed a bill injecting money into this sector in order to train more scientists and transfer knowledge to the industry.


Quantum supremacy is on the horizon, and the pursuit of it is continuing to push scientific progress in fundamental and profound ways. But proving quantum supremacy for one problem won’t bring quantum computers much closer to your own desk. It’s crucial that we continue to emphasize the uncertainties in the field, especially when it comes to near-term potential.

Quantum computers highlight that science and technology have different goals, and provide two very different lenses through which to understand quantum supremacy. Technology can feel like an endless march toward some better product. But science is slower, unpredictable, and often more rigorous—it requires that people cover all the bases in order to understand how these groundbreaking new devices actually work before we can claim that quantum computers are actually superior.

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