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

Approximate gauge symmetry of composite vector bosons

It can be shown in a solvable field theory model that the couplings of the composite vector bosons made of a fermion pair approach the gauge couplings in the limit of strong binding. Although this phenomenon may appear accidental and special to the vector boson made of a fermion pair, we extend it to the case of bosons being constituents and find that the same phenomenon occurs in more an intriguing way. The functional formalism not only facilitates computation but also provides us with a better insight into the generating mechanism of approximate gauge symmetry, in particular, how the strong binding and global current conservation conspire to generate such an approximate symmetry. Remarks are made on its possible relevance or irrelevance to electroweak and higher symmetries.Comment: Correction of typos. The published versio