(Phys.org) Russian researchers from the Moscow Institute of Physics and Technology, Valiev Institute of Physics and Technology and ITMO University have created a neural network that learned to predict the behavior of a quantum system by analyzing its network structure. Researchers need tools for predicting whether a given quantum device will have a quantum advantage. The neural network autonomously finds solutions that are well-adapted to quantum advantage demonstrations. This will aid researchers in developing new efficient quantum computers.
The Russian researchers did is train an AI model to distinguish between networks and determine if a given network have a quantum advantage. This pinpoints the networks that are good candidates for building a quantum computer. The team used a neural network geared toward image recognition. An adjacency matrix served as the input data, along with the numbers of the input and output nodes. The neural network returned a prediction of whether the classical or the quantum walk between the given nodes would be faster.

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