AI reduces quantum physics problem from 100,000 to just 4 equations

AI reduces quantum physics problem from 100,000 to just 4 equations
AI reduces quantum physics problem from 100,000 to just 4 equations

A group of physicists managed, using artificial intelligence, to synthesize an almost insoluble quantum problem, which until now required solving 100,000 equations, in a task of just four equations. THE How much Magazine explains that everything was done ensuring the absolute accuracy of the results.

And what implications can this discovery have on our daily lives? It could revolutionize the way in which systems containing many particles interacting with each other are investigated – if it can be transferred to other problems, some of them much larger, the approach, using the so-called neural network, could help design materials with predefined properties, such as superconductivity, or the ability to generate clean energy more efficiently.

“We started with a huge object, with all these distinct equations associated with it. And what we do next is use machine learning to turn it into a calculation so small you can count it on your fingers,” said Domenico Di Sante, from the University of Bologna, Italy.

Scientists study the behavior of electrons and how there are different phases of matter, such as superconductivity, in which electrons flow through a material without resistance. Hubbard’s model also serves as a testing ground for new methods before being applied to more complex quantum systems.

Even for a small number of electrons, the problem requires heavy computation because when they interact with each other, their fates can cross and two electrons can no longer be treated individually, which makes the challenge exponentially more difficult.

The program’s output captured the physics of the Hubbard model, originally around 100,000 equations, with just four equations. “It’s essentially a machine that has the power to discover hidden patterns,” Di Sante said.

Now that they have their program trained, the researchers intend to adapt it to work on other problems without having to start from scratch. And, as artificial intelligence algorithms remain something of a black box, the team is also investigating what the machine is actually “learning” about the system, which will provide additional information.

Source: How much Magazine

The article is in Portuguese

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