Machine learning using large data sets is a computationally intensive process. One technique that offers an inexpensive opportunity to reduce the wall time for machine learning is to perform the learning in parallel. Raising the level of abstraction of the parallelization to the application level allows existing learning algorithms to be used without modification while providing the potential f...

We consider the trigonometric Felderhof model, of free fermions in an external field, on a finite lattice with domain wall boundary conditions. The vertex weights are functions of rapidities and external fields. We obtain a determinant expression for the partition function in the special case where the dependence on the rapidities is eliminated, but for general external field variables. This de...

The partition function of two hard spheres in a hard-wall pore is studied, appealing to a graph representation. The exact evaluation of the canonical partition function and the one-body distribution function in three different shaped pores are achieved. The analyzed simple geometries are the cuboidal, cylindrical, and ellipsoidal cavities. Results have been compared with two previously studied ...

In this article, we investigate the controllability of multi-agent systems with leaders as control inputs, where the interconnection is directed and weighted. We employ weight-balanced partition to classify the interconnection graphs, and study the controllable subspaces with given nontrivial weight-balanced partition. We also provide two necessary and sufficient graph conditions on structural ...

Physical and computational models are developed, used and benchmarked for studying the response of ITER tokamak plasma facing components to runaway electron impact following a plasma disruption. The energy deposition, temperature evolution and material melting thickness are calculated for a wide range of runaway electron parameters, namely, electron kinetic energy, magnetic field, energy partit...