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New AI Tool Predicts Behaviour Of Quantum System By Simply ‘Looking: Research

Russian researchers have created an Artificial Intelligence (AI)-based tool that has learned to predict the behaviour of a quantum system by “looking” at its network structure.

The neural network autonomously finds solutions that are well-adapted toward quantum advantage demonstrations, according to a study published in the New Journal of Physics. This is expected to aid researchers in developing new efficient quantum computers.

“We have been quite successful in training the computer to make autonomous predictions of whether a complex network has a quantum advantage,” said Leonid Fedichkin, Associate Professor at the Moscow Institute of Physics and Technology (MIPT).

What The Researchers Did?

  • What the Russian researchers did is they replaced the experts with AI. They trained the machine to distinguish between networks and tell if a given network will deliver quantum advantage.
  • A wide range of problems in modern science are solved through quantum mechanical calculations. Some of the examples are research into chemical reactions and the search for stable molecular structures for medicine, pharmaceutics, and other industries.
  • The quantum nature of the problems involved makes quantum computations better-suited to them. Classical computations, by contrast, tend to return only bulky approximate solutions. Creating quantum computers is costly and time-consuming, and the resulting devices are not guaranteed to exhibit any quantum advantage – that is, operate faster than a conventional computer.
  • So researchers need tools for predicting whether a given quantum device will have a quantum advantage. One of the ways to implement quantum computations is quantum walks. In simplified terms, the method can be visualized as a particle travelling in a certain network, which underlies a quantum circuit. The team used a neural network geared toward AI image recognition.
  • If a particle’s quantum walk from one network node to another happens faster than its classical analogue, a device based on that circuit will have a quantum advantage. The search for such superior networks is an important task tackled by quantum walk experts.

The researchers created a tool that simplifies the development of computational circuits based on quantum algorithms. The resulting devices will be of interest in biophotonics research and materials science.

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