The GoogLeNet-assisted Phase Transition Detectors

The GoogLeNet model can completely split the overlapped phase transitions in the superconducting nanowire arrays under Josephson interaction. In the presence of the phase fluctuations in superconducting nanowires array, the electrical resistance of the superconducting nanowires is always non-zero unless the system undergoes Berezinskii-Kosterlitz-Thouless (BKT) transition where the superconducting vortices and anti-vortices form pairs. The two-dimensional XY model can mimic the superconducting transition temperature T c and the BKT transition temperature T BKT by observing the heat capacity anomalies upon cooling. If the Josephson coupling across the nanowires is strong, the heat capacity anomalies almost overlap with each other so that the traditional curve-fitting techniques are difficult to completely distinguish between the T c and the T BKT . To solve this issue, we apply an artificial-intelligence technique to completely split the overlapped heat capacity anomalies. After the GoogLeNet-assisted phase transition detector is built, the GoogLeNet model can learn from the features of the phase transitions and then interpret the T c and T BKT in the ‘unseen’ system precisely. Our work opens a path for the GoogLeNet model to enter the world of superconductivity.