Quantum computing prototypes – built by IBM, Google, IonQ, Rigetti and others – are far from perfect but their commercial potential is boundless
In June, an IBM computing executive claimed quantum computers were entering the “utility” phase, in which high-tech experimental devices become useful. In September, Australia’s Chief Scientist Cathy Foley went so far as to declare “the dawn of the quantum era.”
This week, Australian physicist Michelle Simmons won the nation’s top science award for her work on developing silicon-based quantum computers.
Obviously, quantum computers are having a moment. But – to step back a little – what exactly are they? One way to think about computers is in terms of the kinds of numbers they work with.
The digital computers we use every day rely on whole numbers (or integers), representing information as strings of zeroes and ones which they rearrange according to complicated rules. There are also analog computers, which represent information as continuously varying numbers (or real numbers), manipulated via electrical circuits or spinning rotors or moving fluids.
In the 16th century, the Italian mathematician Girolamo Cardano invented another kind of number called complex numbers to solve seemingly impossible tasks such as finding the square root of a negative number. In the 20th century, with the advent of quantum physics, it turned out complex numbers also naturally describe the fine details of light and matter.
In the 1990s, physics and computer science collided when it was discovered that some problems could be solved much faster with algorithms that work directly with complex numbers as encoded in quantum physics.
The next logical step was to build devices that work with light and matter to do those calculations for us automatically. This was the birth of quantum computing.
We usually think of the things our computers do in terms that mean something to us — balance my spreadsheet, transmit my live video, find my ride to the airport. However, all of these are ultimately computational problems, phrased in mathematical language.
