Classical defeats quantum: two teams surpass IBM’s achievement with 127 qubits with conventional computing

There are records that remain unbeaten for decades and others that only last seconds, such as that of the heptathlon athlete Adrianna Sulek, who only enjoyed her world record of 6.43 seconds. In the informal competition between classical and quantum computing it also happens. On June 14, an investigation published in Nature He claimed to have achieved with 127 qubits, a capacity already present in commercial quantum computers, results impossible in classical computing. Just two weeks later, papers from Caltech and New York University claimed to have achieved more precise resolutions with classical computing. “This struggle between the classical and the quantum is very enriching,” says David Pérez García, a researcher at the Institute of Mathematical Sciences (Icmat) and professor at the Complutense University of Madrid.

Youngseok Kim, Andrew Eddins, and Abhinav Kadala, IBM researchers, along with other authors, stated in Nature have shown that a quantum processor and post-analysis processing can reliably generate, manipulate, and measure quantum states so complex that their properties could not be accurately estimated by conventional approximations.

“No classical computer has enough memory to encode the possibilities calculated by the 127 qubits,” the authors stated. Göran Wendin and Jonas Bylander, researchers at Chalmers University of Technology, Sweden, backed him up: “The fundamental quantum advantage here is scale rather than speed: the 127 qubits encode a problem for which no classical computer has enough. memory”.

“modest resources”

However, this record was only an incentive to try to beat it. Researchers at the Flatiron Institute Center for Computational Quantum Physics accepted the challenge and, in just 12 days, published research with a “precise, memory- and time-efficient, classical simulation” of the system released in Nature. “By adopting a tensor network approach, we can perform a classical simulation that is significantly more accurate than the results obtained by the quantum device,” say the authors, who stress that it has been done with “modest computational resources.”

Just two days later, researchers from Caltech (California Institute of Technology) showed another work in which “a classical algorithm based on Pauli sparse dynamics can efficiently simulate the quantum circuits studied in the recent experiment with the 127 qubits of the processor IBM Eagle.

The researchers refer to the paper published just two days earlier to state: “The fact that both classical approaches are successful illustrates the rich landscape of approximate classical algorithms that have yet to be explored. 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.”

They’re all good

Professor and researcher David Pérez García, an expert in tensor networks (the strategy developed in the first of the alternative works to that of quantum advantage), considers the three investigations “surprising”: “They are spectacular. That different techniques reproduce the results of the experiment gives even more value. The results are good. They are not noise.”

What does contradict the alternative works to the one published in Nature is the conclusion that it is impossible to achieve the same results with other forms of computation. “They show that the experiment [de IBM] it is not at the point of affirming that it cannot be simulated with any classical method”, concludes Pérez García.

“But I don’t think that the quantum advantage was the main goal, but that you can get good results in large, complex systems, without having to go to error correction, which is the dream of quantum computing. There is a middle term that is the mitigation of errors and that can provide very interesting results”, adds the Spanish researcher.

The techniques used were developed to simulate the behavior of quantum systems with classical computers. “The simulation itself shows that these ideas that they are using are interesting and can be used for other types of problems. The field is very dynamic. The difficulties are there and, although bells and whistles cannot yet be launched to say that this technology is already a reality, very promising advances are being observed”, highlights Pérez García.

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