First Look at 'Sycamore,' Google's Quantum Computer

From Gizmodo.com (Oct. 23, 2019):

Between the mountainous and coastal vistas of Goleta, California, sits an unassuming office on the side of a building next to the freeway. It could belong to any Southern California company; workers sit in gray cubicles beneath fluorescent lights, and there’s a rack to hold employees’ bikes and surfboards. But at those desks are physicists and computer scientists developing a computer like none you’ve ever seen before. Behind a set of double doors, cylindrical machines hold computer chips at temperatures colder than the vacuum of space.

Here, Google’s scientists have been toiling to create a computer processor that can solve a problem that’s too hard for the world’s best supercomputers. Today, they announced they’d succeeded: Their Sycamore quantum computer was able to complete a problem in 200 seconds that a supercomputer would need 10,000- years to solve, according to their estimates. It’s a single, contrived problem, and the chip would fail in a race with a supercomputer to add two and two together. But Google’s scientists think they’ve achieved a historical computing milestone.

“One criticism we’ve heard a lot is that we cooked up this contrived benchmark problem—[Sycamore] doesn’t do anything useful yet,” Hartmut Neven, a Google engineering director dressed in a puffy silver coat reminiscent of a space suit, told journalists at a press event today. “That’s why we like to compare it to a Sputnik moment. Sputnik didn’t do much either. All it did was circle Earth. Yet it was the start of the Space Age.”

Today, Google gave journalists a first look at the device and how it was able to complete the experiment.

While classical computers use transistors to represent data in zeroes and ones, quantum computers represent data using artificial atoms, called qubits. Rather than simply using the rules of logic, these qubits interact via the weird mathematics of quantum mechanics. They take on zero or one and produce long strings of binary code just like classical computers do, but during the calculation, they can take on states between zero and one, which determine how likely you are to get zero or one on the final measurement. [read more]