The effects of latent heat release on the waves with Ekman pumping

The problem of the effects of the latent heat release on the waves with both upper and lower boundary frictional effects is investigated. The influence of the vertical shear of the basic wind in these models will be investigated. These investigations will shed some light on the method of solution to the problem of including the effect of Ekman pumping on the moist baroclinic waves in the model of Tang and Fichtl

Magnetotransport and magnetocrystalline anisotropy in Ga1-xMnxAs epilayers

We present an analysis of the magnetic anisotropy in epitaxial Ga1-xMnxAs thin films through electrical transport measurements on multiterminal microdevices. The film magnetization is manipulated in 3D space by a three-axis vector magnet. Anomalous switching patterns are observed in both longitudinal and transverse resistance data. In transverse geometry in particular we observe strong interplay between the anomalous Hall effect and the giant planar Hall effect. This allows direct electrical characterization of magnetic transitions in the 3D space. These transitions reflect a competition between cubic magnetic anisotropy and an effective out-of-plane uniaxial anisotropy, with a reversal mechanism that is distinct from the in-plane magnetization. The uniaxial anisotropy field is directly calculated with high precision and compared with theoretical predictions

Cyclic cocycles on deformation quantizations and higher index theorems

We construct a nontrivial cyclic cocycle on the Weyl algebra of a symplectic vector space. Using this cyclic cocycle we construct an explicit, local, quasi-isomorphism from the complex of differential forms on a symplectic manifold to the complex of cyclic cochains of any formal deformation quantization thereof. We give a new proof of Nest-Tsygan's algebraic higher index theorem by computing the pairing between such cyclic cocycles and the $K$-theory of the formal deformation quantization. Furthermore, we extend this approach to derive an algebraic higher index theorem on a symplectic orbifold. As an application, we obtain the analytic higher index theorem of Connes--Moscovici and its extension to orbifolds.Comment: 59 pages, this is a major revision, orbifold analytic higher index is introduce

Transfer learning for radio galaxy classification

In the context of radio galaxy classification, most state-of-the-art neural network algorithms have been focused on single survey data. The question of whether these trained algorithms have cross-survey identification ability or can be adapted to develop classification networks for future surveys is still unclear. One possible solution to address this issue is transfer learning, which re-uses elements of existing machine learning models for different applications. Here we present radio galaxy classification based on a 13-layer Deep Convolutional Neural Network (DCNN) using transfer learning methods between different radio surveys. We find that our machine learning models trained from a random initialization achieve accuracies comparable to those found elsewhere in the literature. When using transfer learning methods, we find that inheriting model weights pre-trained on FIRST images can boost model performance when re-training on lower resolution NVSS data, but that inheriting pre-trained model weights from NVSS and re-training on FIRST data impairs the performance of the classifier. We consider the implication of these results in the context of future radio surveys planned for next-generation radio telescopes such as ASKAP, MeerKAT, and SKA1-MID