‘Classical’ beats quantum: Using conventional computing, two teams surpass IBM’s groundbreaking 127-qubit processor

There are records that remain unbeaten for decades… and there are others that last only a few seconds. This is the case of heptathlete Adrianna Sulek, who only achieved the world record with a time of 6.43 seconds. And, in the informal competition between classical and quantum computing, a similar short-lived victory occurred.

On June 14, an investigation was published in the magazine Nature claims to have achieved – with 127 qubits – the capacity already available in commercial quantum computers: results thought to be impossible in classical computing. Just two weeks later, papers from Caltech and New York University claimed to have achieved more precise resolution – and this time, they were done using classical computers. “This struggle between classical and quantum is very rich,” says David Pérez García, a researcher at the Institute of Mathematical Sciences (Icmat) and a professor at Madrid’s Complutense University.

Youngseok Kim, Andrew Eddins, and Abhinav Kadala, all IBM researchers, along with other authors, reported in Nature that they have shown how a quantum processor and analytical post-processing can reliably generate, manipulate and measure quantum states of such complexity that the properties of they cannot be accurately estimated by conventional approximations.

“No classical computer has enough memory to encode capabilities computed with 127 qubits,” the authors state. Göran Wendin and Jonas Bylander, researchers at Chalmers University of Technology, Sweden, support their view: “The fundamental quantum advantage here is scale, not speed: 127 qubits encode a the problem is that no classical computer has enough memory.”

However, it seems that the announcement of this record is just motivation to try to beat it. Researchers at the Flatiron Institute’s Center for Computational Quantum Physics rose to the challenge. In just 12 days, they published research on “accurate, memory- and time-efficient classical simulation” of the system reported in Nature. “By applying a tensor network approach, we can perform classical simulations that are significantly more accurate than results obtained with quantum devices,” Flatiron researchers assert. They emphasized that the simulation was performed with “modest computational resources.”

And just two days later, researchers from the California Institute of Technology revealed another project in which “a classical algorithm based on Pauli sparse dynamics can effectively simulate the studied quantum circuits in a recent experiment with 127 qubits of the IBM Eagle processor”. They also refer to the paper published by researchers from the Flatiron Institute: “The fact that both classical methods were successful illustrates the rich landscape of approximate classical algorithms that have yet to be discovered. discover. We believe that the method we describe here holds promise not only for quantum circuit simulations but also for more general simulation problems in quantum dynamics.”

Professor and researcher David Pérez García, an expert in tensor networks (the strategy developed in the first study as an alternative to the quantum advantage), considers the three investigations “surprising.”

“They are breathtaking. Different techniques that reproduce experimental results are even more valuable. The result is good. They are not just noise.”

The works replace the work published in Nature contradicts the conclusion that the same result cannot be achieved by other forms of calculation. “[The simulations] shows that [IBM] the experiment has not yet reached the point of confirming that it cannot be simulated by any classical method,” Pérez García noted. “But I don’t think quantum advantage is the main goal… [rather, it was] that you can get good results in large, complex systems without needing to correct errors, that’s the dream of quantum computing. Have [a middle ground] it’s about minimizing errors, [can also] yielded very interesting results.”

The techniques used were developed to simulate the behavior of quantum systems, but with classical computers. “The simulation itself [is very interesting] and can be used for other types of problems. This field is very dynamic. Difficulties remain and although the bells and whistles cannot yet announce that this technology has become a reality, very promising advances are being observed,” concludes Pérez García.

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