Machine-learning researchers at Google Research have developed in collaboration with researchers at Tri Alpha Energy a new computer algorithm which has significantly speeded up the optimization of its C-2U plasma generator.
On 25 July, the researchers published a report in the journal Scientific Reports describing the “Optometrist Algorithm” , a machine-learning tool that aids in choosing parameters to hold hotter nuclear plasma for longer periods in fusion experiments, one of the keys to cracking the complex code of nuclear fusion.
Tri Alpha Energy is a nearly two-decade-old company that uses a nuclear fusion design that shoots beams of plasma into a vessel where it’s held in place, spinning, by a magnetic field. Its design shares some properties with particle accelerators.
A nuclear fusion experiment can have thousands of individual factors that can affect the outcome, and a computer on its own might optimize an experiment to make it unsafe. The inclusion of expert oversight in parameter exploration is especially important given a priori identification of safe operating regimes cannot always be made for all combinations of machine parameters.
“To increase the speed of learning and optimization of plasma, we developed the Optometrist Algorithm. Just as in a visit to an optometrist, the algorithm offers a pair of choices to a human, and asks which one is preferable. Given the choice, the algorithm proceeds to offer another choice”, write the researchers.
According to the authors, the tool is necessary to help with guiding experiments: “The highly nonlinear and temporally varying interaction between the plasma, its environment and external controls presents a considerable complexity in these experiments. A further difficulty arises from the fact that there is no single objective metric that fully captures both plasma quality and equipment constraints”, they write.
Finally, although initially the fusion field has exploited the Optometrist Algorithm, this one could be used to work on any type of complicated problem, not just energy.
Source: greentechmedia