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Quantum Computing: Dissecting How, Why and When

Many students of high school biology learned about fruit flies: the tiny, winged creatures with red or white eyes that teach us about chromosomes, DNA, and dominant and recessive genes. It’s the study of genetics at a basic level. But to understand complex gene interactions — the kind of knowledge that leads to breakthrough drugs for infectious diseases, for instance — you need a lot more math, which humans and traditional computers can’t handle.

Sterling Thomas, Chief Scientist at the Government Accountability Office (GAO) and a trained geneticist, first used quantum computers about five years ago to explore how the technology might accelerate computations of things such as genetic mutations. But it was a little tricky, he said, and much of the work remains experimental.

“It’s not like we take [an algorithm] and recompile it, and it runs on a quantum computer,” he explained. “You actually have to rethink how the math will be implemented.”

It is true, Thomas said, that quantum technology today is only somewhat helpful. “When people talk about no one using it, there aren’t any use cases, they’re talking about the current state of quantum computing,” he said. “It’s just not fast enough [where] the advantages you get from it … outperform what you already have.”

But there is great potential in biotechnology, orbital space research and some other fields, and as quantum technology improves — and Thomas believes it will — new use cases will become clear.

Why Quantum?

With supercomputers, scientists today can run, for example, 50 iterations of the same calculation in parallel to see which one works best. But some problems you can’t break into pieces like that, Thomas explained. You have to perform the complex calculations all at once.

Supercomputers aren’t suited for it, but quantum technology is, he said. That’s because it opens up a new realm of math. Instead of computations based on either zero or one, quantum computing creates a third option: both zero and one. Thomas said that superstate “significantly expands and accelerates how you can store information and [perform] different types of calculations.”

What’s Holding It Back

One reason why today’s quantum computers are not faster than supercomputers, he said, is because the quantum technology must spend time identifying and correcting its errors. Superconductors used in quantum computing rely on brutally cold temperatures — around absolute zero — and anything above that introduces mistakes. Ion capture, another type of quantum technology, among several, requires less cold but uses magnets to move atoms around, which causes interference between qubits. People don’t realize that traditional computing requires error correction also: It just goes unnoticed because traditional systems have become so good at adjusting for mistakes, Thomas said.

 “Now we’re going through that process in the quantum world of [saying], ‘OK, if it’s too energetically expensive to make [the environment] absolutely cold, where we could have no error, then let’s come up with a way to correct that error,’” he said. Quantum’s energy use is truly a concern. Generative AI and other technologies consume tremendous electricity, Thomas noted, and “the hope was that quantum, because you have this third state, the superstate, you wouldn’t need quite as big [data] centers to do the computations.” But if it takes more energy to power smaller quantum computers, that benefit doesn’t exist.

The Encryption Issue

One way to protect sensitive data is through encryption, in which complex mathematical algorithms scramble the data into a secret code, and only the correct encryption key can transform it back. Right now, encryption is an effective, widely used cybersecurity tool.

Quantum computing threatens that because, as Thomas said, quantum can perform big calculations at once rather than individually. Using Shor’s algorithm, for instance, quantum might take days, not years, to identify the right key to crack an encryption code.

NIST is developing quantum-proof encryption, and Thomas said agencies should be aware of the challenges quantum poses and be ready to transition to new standards. But he believes the issue is not as dire as some people fear.

“I don’t think it’s Armageddon,” he said. “I think it’s just a matter of us developing technology that is safe within this new realm. And this won’t be the last time we have to do that.”

When to Expect It

Before joining GAO in October 2023, Thomas’ work — related to genetics as well as cybersecurity, machine learning, data science, material science and other fields — focused largely on national security. In his view, federal security agencies are the only government entities likely to have on-premises quantum technology — because of the cost and the nature of their work. Most quantum calculations will take place in the cloud, he believes.

It’s reasonable that in five to eight years, quantum will become available in a more reliable way, with systems that have larger and larger qubits. Just like other technology with relatively humble beginnings, quantum computers will improve, Thomas predicted, and society will find use cases it hadn’t envisioned.

It will come down to two simple questions, he said: “What uses do you have in your specific role where quantum might make sense, and how will you access it?”

This article appeared in our guide, “Quantum Computing 101: Getting Ready for Tomorrow’s Tech.” To learn more about this groundbreaking technology, including how and when it will impact you, download the guide here:

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