Probing the halo of Centaurus A: a merger dynamical model for the PN population

Photometry and kinematics of the giant elliptical galaxy NGC~5128 (Centaurus~A) based on planetary nebulae observations (Hui~\etal 1995) are used to build dynamical models which allow us to infer the presence of a dark matter halo. To this end, we apply a Quadratic Programming method. Constant mass-to-light ratio models fail to reproduce the major axis velocity dispersion measurements at large radii: the profile of this kind of models falls off too steeply when compared to the observations, clearly suggesting the necessity of including a dark component in the halo. By assuming a mass-to-light ratio which is increasing with radius, the model satisfactorily matches the observations. The total mass for the best fit model is $\sim4\times10^{11}M_\odot$ of which about 50\% is dark matter. However, models with different total masses and dark halos are also consistent with the data; we estimate that the total mass of Cen~A within 50~kpc may vary between $3\times10^{11}M_\odot$ and $5\times10^{11}M_\odot$. The best fit model consists of 75\% of stars rotating around the short axis $z$ and 25\% of stars rotating around the long axis $x$. Finally, the morphology of the projected velocity field is analyzed using Statler's classification criteria (Statler 1991). We find that the appearance of our velocity field is compatible with a type 'Nn' or 'Nd'.Comment: 13 pages, uuencoded compressed postscript, without figures. The full postscript version, including all 14 figures, is available via anonymous ftp at ftp://naos.rug.ac.be/pub/cena.ps.

A deep learning based approach to classification of CT brain images

This study explores the applicability of the state of the art of deep learning convolutional neural network (CNN) to the classification of CT brain images, aiming at bring images into clinical applications. Towards this end, three categories are clustered, which contains subjects’ data with either Alzheimer’s disease (AD) or lesion (e.g. tumour) or normal ageing. Specifically, due to the characteristics of CT brain images with larger thickness along depth (z) direction (~5mm), both 2D and 3D CNN are employed in this research. The fusion is therefore conducted based on both 2D CT images along axial direction and 3D segmented blocks with the accuracy rates are 88.8%, 76.7% and 95% for classes of AD, lesion and normal respectively, leading to an average of 86.8%

Entanglement reciprocation between atomic qubits and entangled coherent state

Introducing classical fields, we can transfer entanglement completely from discrete qubits into entangled coherent state. The entanglement also can be retrieved from the continuous-variable state of the cavities to the atomic qubits. Via postselection measure, atomic entangled state and entangled coherent state can be mutual transformed fully.Comment: 5 pages, 3 fighres. accepted by J Phys