In the competition between AI and quantum computing, classical computers are the underdogs

In the “AI versus quantum” match, the surprise could come from an outsider, who has built up a lot of muscle in recent years and intends to win the day: the good old computer powered by classical algorithms.

“Betting” is a very fundamental physics and chemistry problem, called the “N-body problem,” which refers to systems with many interacting particles. For example, a hundred electrons to describe a molecule and some of its properties, or 10²³ electrons for a material. “The direct approach quickly shows its limits. For a system whose particles each have only two states, for example, all of the current storage devices on Earth could only be used to represent 80 of these particles.describes Antoine Georges, professor of condensed matter physics at the Collège de France.

To overcome these limits, several tips have been found in recent years. One of them made a notable breakthrough in the 1990s. “It was crazy! This made it possible to solve almost all situations of the one-dimensional N-body problem.remembers Antoine Tilloy, professor at the School of Mines in Paris. In 1992, physicist Steve White (University of California at Irvine) invented tensor networks, a method analogous to data compression, considerably reducing the amount of information to be processed. Simulations that could not run, because they were overwhelmed by the number of possibilities to explore, become executable on classical computers – not even “supercomputers”.

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