Atomic and molecular ions in intense ultra-fast laser fields

The interaction of a 60 fs 790 nm laser pulse with beams of Ar+, C+, H2+, HD+ and D2+ are discussed. Intensities up to 10^16 Wcm-2 are employed. An experimental z-scanning technique is used to resolve the intensity dependent processes in the confocal volume.

Fast-beam study of H2+ ions in an intense femtosecond laser field

A fast beam of H-2(+) ions, produced from a low energy ion accelerator, has been used for the first time in intense laser field experiments. The technique has enabled neutral dissociation products to be analysed and detected for the first time in such studies. Energy spectra of neutral and ionized fragments, product yields as a function of focused laser intensity and angular distributions of neutral dissociation products have been measured. Significant differences are observed between the present results and those obtained from experiments involving neutral H-2 molecules. These differences are indicative of the precursor H-2 molecule playing an important and hitherto neglected formative role in the laser-induced fragmentation processes.

Observation of fast hydrogen atoms formed by ion bombarding of surfaces

We report on the observation of fast hydrogen atoms in a capacitively coupled RF reactor by optical emission spectroscopy. For the analysis we use the prominent H-alpha emission line of atomic hydrogen in combination with other lines from molecular hydrogen and argon. Several chaxacteristic emission structures can be identified. One of these structures is related to fast hydrogen atoms traveling from the surface of the powered electrode to the plasma bulk. From the appearance time within the RF period we conclude that this feature originates from ion bombardment of the electrode surface. Measured pressure dependencies and a simple model for the ion dynamics support this assumption.

Fast model based feature matching technique applied to airport lighting

The use of image processing techniques to assess the performance of airport landing lighting using images of it collected from an aircraft-mounted camera is documented. In order to assess the performance of the lighting, it is necessary to uniquely identify each luminaire within an image and then track the luminaires through the entire sequence and store the relevant information for each luminaire, that is, the total number of pixels that each luminaire covers and the total grey level of these pixels. This pixel grey level can then be used for performance assessment. The authors propose a robust model-based (MB) featurematching technique by which the performance is assessed. The development of this matching technique is the key to the automated performance assessment of airport lighting. The MB matching technique utilises projective geometry in addition to accurate template of the 3D model of a landing-lighting system. The template is projected onto the image data and an optimum match found, using nonlinear least-squares optimisation. The MB matching software is compared with standard feature extraction and tracking techniques known within the community, these being the Kanade–Lucus–Tomasi (KLT) and scaleinvariant feature transform (SIFT) techniques. The new MB matching technique compares favourably with the SIFT and KLT feature-tracking alternatives. As such, it provides a solid foundation to achieve the central aim of this research which is to automatically assess the performance of airport lighting.

Process monitoring approach using fast moving window PCA

This paper introduces a fast algorithm for moving window principal component analysis (MWPCA) which will adapt a principal component model. This incorporates the concept of recursive adaptation within a moving window to (i) adapt the mean and variance of the process variables, (ii) adapt the correlation matrix, and (iii) adjust the PCA model by recomputing the decomposition. This paper shows that the new algorithm is computationally faster than conventional moving window techniques, if the window size exceeds 3 times the number of variables, and is not affected by the window size. A further contribution is the introduction of an N-step-ahead horizon into the process monitoring. This implies that the PCA model, identified N-steps earlier, is used to analyze the current observation. For monitoring complex chemical systems, this work shows that the use of the horizon improves the ability to detect slowly developing drifts.