Discerning the “Fine Line” Between Quantum and Classical Computing
AI method determines quantum advantage for advanced computing
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+ 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. 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 findings are reported in the New Journal of Physics.
“It was not obvious this approach would work, but it did. We have been quite successful in training the computer to make autonomous predictions of whether a complex network has a quantum advantage,” said Associate Professor Leonid Fedichkin of the theoretical physics department at MIPT.
+ What 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.
One of the ways to implement quantum computations is quantum walks. In simplified terms, the method can be visualized as a particle traveling in a certain network that underlies a quantum circuit. 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.
+ Compared with architectures based on qubits and gates, quantum walks are expected to offer an easier way to implement the quantum calculation of natural phenomena. The reason for this is that the walks themselves are a natural physical process.
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