Permanent-Magnet Optimization for Stellarators as Sparse Regression

Though permanent magnets are ubiquitous in science and everyday society, we still lack a systematic analysis of how to optimally place orient large set them (much larger) possible locations. This study reformulates the problem terms sparse regression, offers an algorithm that can effectively solve for nonconvex systems with over 10${}^{6}$ optimizable variables constraints. The authors then obtain high-performance designs class familiar fusion-power devices called stellarators. Because their addresses problems appear across many scientific domains, it should prove extremely impactful.