Before every tokamak startup, a device where superheated gas is held by magnetic fields, operators spend hours calculating how the plasma will behave. Mistakes are too costly: one wrong parameter can ruin the experiment. Now a neural network comes to the rescue, learning from past runs and delivering a prediction faster than you can blink.
The model works like an experienced chef: knowing the recipe (current in the coils, heating power, gas density), it predicts what the dish will turn out like — how hot and stable the plasma will be. Instead of hours of supercomputer calculations, the answer comes in 0.1 seconds. For training, data from 550 discharges of the WEST tokamak in France were used.
Such speed opens new possibilities: you can quickly run through launch scenarios, discard dangerous options, and even adjust parameters in real time during the discharge. Fusion energy is like a complex dance where every step must be precise. The neural network becomes a partner that hints at the next move a moment before the music.
The WEST tokamak is named after the English word "west" because it is the Western European branch of the international ITER project.