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Google’s ‘quantum supremacy’ usurped by researchers using ordinary supercomputer – TechCrunch


In 2019, Google proudly announced that it had achieved what quantum computing researchers had been looking for for years: proof that esoteric technique could outperform traditional techniques. But this demonstration of “quantum supremacy” is disputed by researchers claiming to have beaten Google to a relatively normal supercomputer.

To be clear, no one is saying Google lied or misrepresented its work – the painstaking, groundbreaking research that led to the announcement of Quantum Supremacy in 2019 is still hugely important. But if this new article is correct, the competition between classical computing and quantum computing is still a game for everyone.

You can read the full story of how Google took quantum from theory to reality in the original article, but here’s the very short version. Quantum computers like Sycamore are not yet better than classical computers, except perhaps for one task: simulating a quantum computer.

It sounds like a loophole, but the point of quantum supremacy is to show the viability of the method by finding even one very specific, weird task that it can do better than even the fastest supercomputer. Because it puts the quantum foot in the door to expand that library of tasks. Maybe in the end all tasks will be quantum faster, but for Google’s purposes in 2019 only one was, and they showed how and why in great detail.

Now, a team from the Chinese Academy of Sciences led by Pan Zhang has published a paper describing a new technique for simulating a quantum computer (specifically, some of the noise patterns it emits) that appears to take a tiny fraction of the estimated time for the classic calculation to do so in 2019.

Not being an expert in quantum computing or a professor of statistical physics myself, I can only give a general idea of ​​the technique of Zhang et al. used. They presented the problem as a large 3D tensor network, with Sycamore’s 53 qubits represented by a grid of nodes, extruded 20 times to represent the 20 cycles the Sycamore gates went through in the simulated process. The mathematical relationships between these tensors (each its own set of interdependent vectors) were then calculated using a cluster of 512 GPUs.

An illustration of Zhang’s paper showing a visual representation of the 3D tensor network they used to simulate Sycamore’s quantum operations. Picture credits: Pan Zhang et al.

In the original Google article, it was estimated that running this simulation scale on the most powerful supercomputer available at the time (Summit at Oak Ridge National Laboratory) would take around 10,000 years – although to be clear, this was their estimate for 54 qubits doing 25 cycles; 53 qubits by making 20 is considerably less complex but would still take on the order of a few years according to their estimate.

Zhang’s group claims to have done it in 15 hours. And if they had access to a proper supercomputer like Summit, it could be accomplished in seconds – faster than Sycamore. Their paper will be published in the journal Physical Review Letters; you can read it here (PDF).

These results have yet to be fully verified and replicated by those knowledgeable about these things, but there’s no reason to think this is some kind of error or hoax. Google even admitted that the baton could be passed several times before supremacy is firmly established, because it is incredibly difficult to build and program quantum computers while classical computers and their software are constantly being improved. (Others in the quantum world were skeptical of their claims initially, but some are direct competitors.)

Google offered the following comment acknowledging progress here:

In our 2019 article, we said that classical algorithms would improve (in fact, Google invented the method used here for simulating random circuits in 2017, and the methods of trading fidelity for computational costs in 2018 and 2019) – but the key point is that quantum technology is improving exponentially faster. We therefore do not believe that this classical approach can keep pace with quantum circuits in 2022 and beyond, despite significant improvements in recent years.

As University of Maryland quantum scientist Dominik Hangleiter told Science, it’s not a black eye for Google or a punch for quantum in general: “The Google experiment has what she was supposed to do, start this race.”

Google may well retaliate with its own claims – it hasn’t stood still either. But the fact that it’s even competitive is good news for everyone involved; it’s an exciting area of ​​computing, and work like Google and Zhang’s continues to raise the bar for everyone.

Tech

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