A copy of the paper seen by New Scientist contains details of a quantum processor called Sycamore that contains 54 superconducting quantum bits, or qubits. It claims that Sycamore has achieved quantum supremacy. The paper identifies only one author: John Martinis at the University of California, Santa Barbara, who is known to have partnered with Google to build the hardware for a quantum computer.
“This dramatic speedup relative to all known classical algorithms provides an experimental realization of quantum supremacy on a computational task and heralds the advent of a much-anticipated computing paradigm,” the paper says.
Google appears to have partnered with NASA to help test its quantum computer. In 2018, the two organisations made an agreement to do this, so the news isn’t entirely unexpected.
The paper describes how Google’s quantum processor tackled a random sampling problem – that is, checking that a set of numbers has a truly random distribution. This is very difficult for a traditional computer when there are a lot of numbers involved.
But Sycamore does things differently. Although one of its qubits didn’t work, the remaining 53 were quantum entangled with one another and used to generate a set of binary digits and check their distribution was truly random. The paper calculates the task would have taken Summit, the world’s best supercomputer, 10,000 years – but Sycamore did it in 3 minutes and 20 seconds.
This benchmarking task isn’t particularly useful beyond producing truly random numbers – it was a proof of concept. But in the future, the quantum chip may be useful in the fields of machine learning, materials science and chemistry, says the paper. For example, when trying to model a chemical reaction or visualise the ways a new molecule may connect to others, quantum computers can handle the vast amount of variables to create an accurate simulation.
“Google’s recent update on the achievement of quantum supremacy is a notable mile marker as we continue to advance the potential of quantum computing,” said Jim Clarke at Intel Labs in a statement.
Yet we are still at “mile one of this marathon”, Clarke said. This demonstration is a proof of concept, but it isn’t free of errors within the processor. Better and bigger processors will continue to be built and used to do more useful calculations.
At the same time, classical computing isn’t giving up the fight. Over the past few years, as quantum computing took steps towards supremacy, classical computing moved the goal posts as researchers showed it was able to simulate ever more complex systems. It is likely that this back-and-forth will continue.
“We expect that lower simulation costs than reported here will eventually be achieved, but we also expect they will be consistently outpaced by hardware improvements on larger quantum processors,” says the Google paper.