Quantum computing is a fundamentally different approach to computation compared with the kinds of calculations that we do on today’s laptops, workstations, and mainframes. It won’t replace these devices, but by leveraging the principles of quantum physics it will solve specific, typically very complex problems of a statistical nature that are difficult for current computers.

Qubits versus bits

Classical computers are programmed with bits as data units (zeros and ones). Quantum computers use so-called qubits, which can represent a combination of both zero and one at the same time, based on a principle called superposition.

It’s this difference that gives quantum computers the potential to be exponentially faster than today’s mainframes and servers. Quantum computers can do multiple calculations with multiple inputs simultaneously. Today’s computers can handle only one set of inputs and one calculation at a time. Working with a certain number of qubits—let’s say n for our example—a quantum computer can conduct calculations on up to 2ⁿ inputs at once.

That sounds crystal clear. But when you dig into the details of how a quantum computer actually works, you start to understand that many existing challenges must be solved before quantum computers deliver on that potential. (For more, see sidebar, “Quantum computing versus classical computing.”)

Technical obstacles

Some of these obstacles are technical. Qubits, for example, are volatile. Every bit in today’s computers must be in a state of one or zero. A great deal of work goes into ensuring that one bit on a computer chip does not interfere with any other bit on that chip. Qubits, on the other hand, can represent any combination of zero and one. What’s more, they interact with other qubits. In fact, these interactions are what make it possible to conduct multiple calculations at once.

Controlling these interactions, however, is very complicated. The volatility of qubits can cause inputs to be lost or altered, which can throw off the accuracy of results. And creating a computer of meaningful scale would require hundreds of thousands or millions of qubits to be connected coherently. The few quantum computers that exist today can handle nowhere near that number.

Software and hardware companies—ranging from start-ups you’ve never heard of to research institutes to the likes of Google, IBM, and Microsoft—are trying to overcome these obstacles. They’re working on algorithms that bear little resemblance to the ones we use today, hardware that may well wind up looking very different from today’s gray boxes, and software to help translate existing data into a qubit-ready format. But they have a long way to go. Although quantum computing as a concept has been around since the early 1980s, the first real proof that quantum computers can handle problems too complicated for classical computers occurred only in late 2019, when Google announced that its quantum computer had solved such a calculation in just 200 seconds. But this was more of a mathematical exercise than anything that could be applied to business—the problem had no real-world use at all.

Ranges, rather than answers

The nature of quantum mechanics also presents obstacles to exponential speed gains. Today’s computers operate in a very straightforward fashion: they manipulate a limited set of data with an algorithm and give you an answer. Quantum computers are more complicated. After multiple units of data are input into qubits, the qubits are manipulated to interact with other qubits, allowing for a number of calculations to be done simultaneously. That’s where quantum computers are a lot faster than today’s machines. But those gains are mitigated by the fact that quantum computers don’t deliver one clear answer. Instead, users get a narrowed range of possible answers. In fact, they may find themselves conducting multiple runs of calculations to narrow the range even more, a process that can significantly lessen the speed gains of doing multiple calculations at once.

Getting a range rather than a single answer makes quantum computers sound less precise than today’s computers. That’s true for calculations that are limited in scope, which is one reason quantum computers won’t replace today’s systems. Instead, quantum computers will be used for different kinds of problems, incredibly complex ones in which eliminating an enormous range of possibilities will save an enormous amount of time.