Consistency between the radio and MIR faint source counts using the radio-MIR correlation

We show from the recent extrapolation of the radio-FIR correlation to the MIR that the 20 cm and 15 um differential source counts are likely to come from the same parent population.Comment: 2 pages, 2 figures, to appear in proceedings of 'Multi-wavelength AGN surveys', Cozumel, 200

Revisiting direct neuralisation of first-order logic

There is a long history of direct translation of propositional Horn-clause logic programs into neural networks. The possibility of translating first-order logical syntax in the same way has been largely overlooked, perhaps due to a “propositional fixation” fixation! We briefly revise the possibility and advantage of translating existentially and universally quantified clauses into a neural form that follows the first-order syntax in a natural wa

Customizing kernel functions for SVM-based hyperspectral image classification

Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available algorithms. However, few efforts have been made to extend SVMs to cover the specific requirements of hyperspectral image classification, for example, by building tailor-made kernels. Observation of real-life spectral imagery from the AVIRIS hyperspectral sensor shows that the useful information for classification is not equally distributed across bands, which provides potential to enhance the SVM's performance through exploring different kernel functions. Spectrally weighted kernels are, therefore, proposed, and a set of particular weights is chosen by either optimizing an estimate of generalization error or evaluating each band's utility level. To assess the effectiveness of the proposed method, experiments are carried out on the publicly available 92AV3C dataset collected from the 220-dimensional AVIRIS hyperspectral sensor. Results indicate that the method is generally effective in improving performance: spectral weighting based on learning weights by gradient descent is found to be slightly better than an alternative method based on estimating ";relevance"; between band information and ground trut

Trapping effects on inflation

We develop a Lagrangian approach based on the influence functional method so as to derive self-consistently the Langevin equation for the inflaton field in the presence of trapping points along the inflaton trajectory. The Langevin equation exhibits the backreaction and the fluctuation-dissipation relation of the trapping. The fluctuation is induced by a multiplicative colored noise that can be identified as the the particle number density fluctuations and the dissipation is a new effect that may play a role in the trapping with a strong coupling. In the weak coupling regime, we calculate the power spectrum of the noise-driven inflaton fluctuations for a single trapping point and studied its variation with the trapping location. We also consider a case with closely spaced trapping points and find that the resulting power spectrum is blue.Comment: 13 pages, 2 figure

Exact vortex nucleation and cooperative vortex tunneling in dilute BECs

With the imminent advent of mesoscopic rotating BECs in the lowest Landau level (LLL) regime, we explore LLL vortex nucleation. An exact many-body analysis is presented in a weakly elliptical trap for up to 400 particles. Striking non-mean field features are exposed at filling factors >>1 . Eg near the critical rotation frequency pairs of energy levels approach each other with exponential accuracy. A physical interpretation is provided by requantising a mean field theory, where 1/N plays the role of Planck's constant, revealing two vortices cooperatively tunneling between classically degenerate energy minima. The tunnel splitting variation is described in terms of frequency, particle number and ellipticity.Comment: 4 pages,4 figure