[Science] Google claims it has finally reached quantum supremacy – AI

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[Science] Google claims it has finally reached quantum supremacy – AI


By Chelsea Whyte The demonstration reportedly involved checking a series of binary numbers were truly randomiStock / Getty Images Plus This could be the dawn of a new era in computing. Google has claimed that its quantum computer performed a calculation that would be practically impossible for even the best supercomputer – in other words, it has attained quantum supremacy. If this is true, it is big news. Quantum computers have the potential to change the way we design new materials, work out logistics, build artificial intelligence and break encryption. That is why firms like Google, Intel and IBM – along with plenty of startups – have all been racing to reach this crucial milestone. The development at Google is, however, shrouded in intrigue. A paper containing details of the work was posted to a NASA server last week, before being quickly removed. Several media outlets reported on the rumors, but Google has not commented on them. Advertisement Read more: Revealed: Google’s plan for quantum computer supremacy 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 so as to help test their 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 have a truly random distribution This is very difficult for a traditional computer when there are a lot of numbers involved. Totally random But Sycamore works differently. Although one of its qubits didn’t work, but 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 papers 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 is not 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, the paper says. 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’re still at “mile one of this marathon,” Clarke said. This demonstration is a proof-of-concept, but it’s not free of errors within the processor. Better and bigger processors will continue to be built and used to do more useful calculations. Read more: Google’s quantum computing plans threatened by IBM curveball At the same time, classical computing isn’t going anywhere. Over the last few years, as quantum computing took steps towards supremacy, classical computing moved the goal posts as researchers showed they were able to simulate ever more complex systems. It’s likely that 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 Google paper. More on these topics: quantum computing

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