Sparse system identification is the data-driven process of obtaining parsimonious differential
equations that describe the evolution of a dynamical system, balancing model complexity …

This paper documents the design and construction of MUSE, the world's first permanent
magnet (PM) stellarator and the first quasi-axisymmetric experiment. The purpose of MUSE …

Machine learning has had an enormous impact in many scientific disciplines. It has also
attracted significant interest in the field of low-temperature plasma (LTP) modeling and …

A number of scientific fields rely on placing permanent magnets in order to produce a
desired magnetic field. We have shown in recent work that the placement process can be …

Topology optimization, a technique to determine where material should be placed within a
predefined volume in order to minimize a physical objective, is used across a wide range of …

A common optimization problem in the areas of magnetized plasmas and fusion energy is
the design of magnets to produce a given three-dimensional magnetic field distribution to …

Designing magnets for three-dimensional plasma confinement is a key task for advancing
the stellarator as a fusion reactor concept. Stellarator magnets must produce an accurate …

Advanced stellarators are typically optimized in two stages. The plasma equilibrium is
optimized first, followed by the design of coils/permanent magnets. However, the …

In recent years, genetic algorithms have been applied in nuclear technology design, which
have been shown to produce optimized results more efficiently than traditional enumeration …

A novel sparse encoding algorithm is developed to detect and study plasma instabilities
automatically. This algorithm, called Elastic Random Mode Decomposition, is applied to the …