Generating of Plasma Discharge Video by Generative Adversarial Network

During the experiment of nuclear fusion, a lot of videos containing plasma discharge are recorded inside Large Helical Device. An observation of the recorded videos of plasma light emission can lead to a new discovery or help to optimize the operation parameter of the experiment. An unusual plasma discharge which may cause a damage on the device, is expected to be foreseen through a prediction method. Due to the shortage of videos having such unusual emission, it is required to generate more videos having similar phenomenon. However, video generation is very challenging as the generated video should have not only similarity in features with the real one but also a plausibility in frame-by-frame transition, especially in the case of plasma discharge videos. Thus, this paper proposes a method to generate a plasma emission video by using Generative Adversarial Network (GAN). It has been confirmed that the proposed generative model can produce a new video having plasma emission phenomenon with a very smooth changing of frames.