In 2019, Google proudly announced that it had achieved what quantum computing researchers had been seeking for years: proof that esoteric technique could outperform traditional ones. But this demonstration of “quantum supremacy” is being challenged by researchers who claim to have outdone Google in a relatively normal supercomputer.
To be clear, no one is saying that Google lied or misrepresented its work: the painstaking and groundbreaking research that led to the announcement of quantum supremacy in 2019 is still very important. But if this new paper is correct, the classical versus quantum computing competition remains anyone’s game.
You can read the full story of how Google brought quantum from theory to reality in the original article, but here’s the very short version. Quantum computers like Sycamore are no better than classical computers at anything yet, with the possible exception of one task: simulating a quantum computer.
It sounds like a dodge, but the point of quantum supremacy is to show the feasibility of the method by finding even one very specific and rare task that it can do better than even the fastest supercomputer. Because that puts the quantum foot in the door to expand that library of tasks. Perhaps 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, certain patterns of noise it emits) that appears to take a small fraction of the time estimated for classic. computation to do it in 2019.
Not being an expert in quantum computing or a professor of statistical physics, I can only give a general idea of the Zhang et al. use. They presented the problem as a large 3D network of tensors, with the 53 qubits in Sycamore 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 with its own set of interrelated vectors) were then computed using a pool of 512 GPUs.
In Google’s original 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, though to be clear, that was their estimate of 54 qubits doing 25 cycles; 53 qubits making 20 is considerably less complex, but would still take a few years by his 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 done in a few seconds, faster than Sycamore. His article will be published in the journal Physical Review Letters; You can read it here (PDF).
These results have yet to be fully scrutinized and replicated by experts in this sort of thing, but there’s no reason to think this is some kind of mistake or hoax. Google even admitted that the baton may be passed several times before supremacy is firmly established, since 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 his claims at first, but some are direct competitors.)
Google offered the following comment acknowledging the march of progress here:
In our 2019 article, we said that classical algorithms would get better (in fact, Google invented the method used here for random circuit simulation in 2017, and the methods for trading fidelity for computational costs in 2018 and 2019), but the key point is that quantum technology improves exponentially faster. Therefore, we 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, this isn’t a black eye for Google or a knockout blow for quantum in general by any means: “Google’s experiment did what it was supposed to.” what I should do, start this race.
Google may fight back with new claims of its own; He hasn’t been quiet either. But the fact that it’s even competitive is good news for everyone involved; this is an exciting area of computing and work like Google and Zhang’s continues to raise the bar for everyone.