An application of the shortest path algorithm for the identification of weak MHD mode

The identification of magnetohydrodynamic (MHD) modes is a crucial issue in the control of magnetically confined plasmas. This paper proposes a novel method for identifying the evolution of MHD modes from a signal with a low signal-to-noise ratio. The proposed method generates a weighted directed graph from the time-frequency spectrum and calculates the evolution of the mode frequency by solving the shortest path. This method addresses the limitations posed by the lack of data channels and the disturbance of noise in the estimation of mode frequency and yields much better results compared to traditional methods. It is demonstrated that, using this method, the evolution of an unlocked tearing mode was more accurately calculated on the J-TEXT tokamak. This method remains feasible even with a low signal-to-noise ratio of 0.5, as shown by its uncertainty. Furthermore, with appropriate parameters, this method can be applied to not only signals with MHD modes, but also to general signals with continuous modes.