A neural network built by Russian researchers has learned to model the behavior, in a manner that you have certainly not previously heard. It only allows the predictions by looking at the network structure of the quantum system and provides autonomously sophisticated solutions that demonstrate a quantum advantage–the ability of quantum computers to outperform conventional computers.
Alexey Melnikov from ITMO University states in a MIPT report: “There is often a misunderstanding between quantum and classical behavior. The hallmark attribute is the resultant machine vision which is specially designed to distinguish this fine line of communication in the network region.
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Classical computing relies on bits that can have a definite value of either 0 or 1. Whereas quantum computing is based on qubits that have the ability to exists as both values at the same time because of superposition. Quantum computing offers a wide range of advantages over conventional data, including much more rapid speeds at a subatomic level.
Quantum device technology is costly. So, it will generally be dependent on quantum walks to test if the developed quantum network will have a quantum advantage. “Quantum walks are the core of modern quantum technologies” are the researchers in their paper.
Quantum Walk is a graphical view of the particle path in a particular quantum network that is the foundation of a quantum circuit. The velocity of the particles is contrasted to classic computing counterparts, enabling specialists to explain the network’s quantum gain.
The researchers have trained experts in an artificial intelligence tool. The AI Tool will research the diagrams of quantum walks by image recognition and autonomously determine whether or not a quantum computer has any quantum gain. The scientists have shown the ability to develop quantum walking algorithms.
“It wasn’t obvious that this approach would work but it did,” Leonid Fédichkin of Moscow Institute for Physics and Technology (MIPT) said. We were quite effective in teaching the machine to determine independently whether a complex network has a quantum gain.
