Reading Nanomagnetic Energy Minimizing Coprocessor

Nanomagnetic Models

The atomic-scale and mesoscopic physics of magnetic nanostructures is reviewed. Emphasis is on the description of magnetic phenomena and properties by analytical models, as contrasted to numerical approaches. Nanostructuring affects the magnetic properties on different length scales, from a few interatomic distances for intrinsic properties such as magnetization and anisotropy to more than 10 n...

Minimizing Calibration Time for Brain Reading

Machine learning is increasingly used to autonomously adapt brain-machine interfaces to user-specific brain patterns. In order to minimize the preparation time of the system, it is highly desirable to reduce the length of the calibration procedure, during which training data is acquired from the user, to a minimum. One recently proposed approach is to reuse models that have been trained in hist...

Geometric approach to optimal nonequilibrium control: Minimizing dissipation in nanomagnetic spin systems.

Optimal control of nanomagnets has become an urgent problem for the field of spintronics as technological tools approach thermodynamically determined limits of efficiency. In complex, fluctuating systems, such as nanomagnetic bits, finding optimal protocols is challenging, requiring detailed information about the dynamical fluctuations of the controlled system. We provide a physically transpare...

Minimizing energy among homotopic maps

Overtwisted Energy-minimizing Curl Eigenfields

We consider energy-minimizing divergence-free eigenfields of the curl operator in dimension three from the perspective of contact topology. We give a negative answer to a question of Etnyre and the first author by constructing curl eigenfields which minimize L energy on their co-adjoint orbit, yet are orthogonal to an OVERTWISTED contact structure. We conjecture that K-contact structures on S-b...