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Computing Optimal Experimental Designs via Interior Point Method
In this paper, we study optimal experimental design problems with a broad
class of smooth convex optimality criteria, including the classical A-, D- and
p th mean criterion. In particular, we propose an interior point (IP) method
for them and establish its global convergence. Furthermore, by exploiting the
structure of the Hessian matrix of the aforementioned optimality criteria, we
derive an explicit formula for computing its rank. Using this result, we then
show that the Newton direction arising in the IP method can be computed
efficiently via Sherman-Morrison-Woodbury formula when the size of the moment
matrix is small relative to the sample size. Finally, we compare our IP method
with the widely used multiplicative algorithm introduced by Silvey et al. [29].
The computational results show that the IP method generally outperforms the
multiplicative algorithm both in speed and solution quality
Diffraction of a pulse by a three-dimensional corner
Three dimensional diffraction of sonic booms by corners of structure
Progressive amorphization of GeSbTe phase-change material under electron beam irradiation
Fast and reversible phase transitions in chalcogenide phase-change materials
(PCMs), in particular, Ge-Sb-Te compounds, are not only of fundamental
interests, but also make PCMs based random access memory (PRAM) a leading
candidate for non-volatile memory and neuromorphic computing devices. To RESET
the memory cell, crystalline Ge-Sb-Te has to undergo phase transitions firstly
to a liquid state and then to an amorphous state, corresponding to an abrupt
change in electrical resistance. In this work, we demonstrate a progressive
amorphization process in GeSb2Te4 thin films under electron beam irradiation on
transmission electron microscope (TEM). Melting is shown to be completely
absent by the in situ TEM experiments. The progressive amorphization process
resembles closely the cumulative crystallization process that accompanies a
continuous change in electrical resistance. Our work suggests that if
displacement forces can be implemented properly, it should be possible to
emulate symmetric neuronal dynamics by using PCMs
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