Dynamical stability of entanglement between spin ensembles

We study the dynamical stability of the entanglement between the two spin ensembles in the presence of an environment. For a comparative study, we consider the two cases: a single spin ensemble, and two ensembles linearly coupled to a bath, respectively. In both circumstances, we assume the validity of the Markovian approximation for the bath. We examine the robustness of the state by means of the growth of the linear entropy which gives a measure of the purity of the system. We find out macroscopic entangled states of two spin ensembles can stably exist in a common bath. This result may be very useful to generate and detect macroscopic entanglement in a common noisy environment and even a stable macroscopic memory.Comment: 4 pages, 1 figur

Berry's phase with quantized field driving: effects of inter-subsystem coupling

The effect of inter-subsystem couplings on the Berry phase of a composite system as well as that of its subsystem is investigated in this paper. We analyze two coupled spin-$\frac 1 2$ particles with one driven by a quantized field as an example, the pure state geometric phase of the composite system as well as the mixed state geometric phase for the subsystem is calculated and discussed.Comment: 4 pages, 1 figur

Electronic Structures of Fe3−xV_{3-x}V_x$Si Probed by Photoemission Spectroscopy

The electronic structures of the Heusler type compounds Fe$_{3-x}V$_x$Si in the concentration range between x = 0 and x = 1 have been probed by photoemission spectroscopy (PES). The observed shift of Si 2p core- level and the main valence band structres indicate a chemical potential shift to higher energy with increasing x. It is also clarified that the density of state at Fermi edge is owing to the collaboration of V 3d and Fe 3d derived states. Besides the decrease of the spectral intensity near Fermi edge with increasing x suggests the formation of pseudo gap at large x.Comment: 4 pages, 5 figures, 5 reference

Deep Learning For Feature Tracking In Optically Complex Waters

PosterEnvironmental monitoring and early warning of water quality from space is now feasible at unprecedented spatial and temporal resolution following the latest generation of satellite sensors. The transformation of this data through classification into labelled, tracked event information is of critical importance to offer a searchable dataset. Advances in image recognition techniques through Deep Learning research have been successfully applied to satellite remote sensing data. Deep Learning approaches that leverage optical satellite data are now being developed for remotely sensed multi- and hyperspectral reflectance. The combination of spectral with spatial feature extracting Deep Learning networks promises a significant improvement in the accuracy of classifiers using remotely sensed data. This project aims to re-tool and optimise spectral-spatial Convolutional Neural Networks originally developed for land classification as a novel approach to identifying and labelling dynamic features in waterbodies, such as algal blooms and sediment plumes in high-resolution satellite sensors

Investigation for the puzzling abundance pattern of the neutron-capture elements in the ultra metal-poor star: CS 30322-023

The s-enhanced and very metal-poor star CS 30322-023 shows a puzzling abundance pattern of the neutron-capture elements, i.e. several neutron-capture elements such as Ba, Pb etc. show enhancement, but other neutron-capture elements such as Sr, Eu etc. exhibit deficient with respect to iron. The study to this sample star could make people gain a better understanding of s- and r-process nucleosynthesis at low metallicity. Using a parametric model, we find that the abundance pattern of the neutron-capture elements could be best explained by a star that was polluted by an AGB star and the CS 30322-023 binary system formed in a molecular cloud which had never been polluted by r-process material. The lack of r-process material also indicates that the AGB companion cannot have undergone a type-1.5 supernova, and thus must have had an initial mass below 4.0M$_\odot$, while the strong N overabundance and the absence of a strong C overabundance indicate that the companion's initial mass was larger than 2.0M$_\odot$. The smaller s-process component coefficient of this star illustrates that there is less accreted material of this star from the AGB companion, and the sample star should be formed in the binary system with larger initial orbital separation where the accretion-induced collapse (AIC) mechanism can not work.Comment: 13 pages, 2 figure