Polarization and correlation phenomena in the radiative electron capture by bare highly-charged ions

In dieser Arbeit wird die Wechselwirkung zwischen einem Photon und einem Elektron im starken Coulombfeld eines Atomkerns am Beispiel des radiativen Elektroneneinfangs beim Stoß hochgeladener Teilchen untersucht. In den letzten Jahren wurde dieser Ladungsaustauschprozess insbesondere für relativistische Ion–Atom–Stöße sowohl experimentell als auch theoretisch ausführlich erforscht. In Zentrum standen dabei haupsächlich die totalen und differentiellen Wirkungsquerschnitte. In neuerer Zeit werden vermehrt Spin– und Polarisationseffekte sowie Korrelationseffekte bei diesen Stoßprozessen diskutiert. Man erwartet, dass diese sehr empfindlich auf relativistische Effekte im Stoß reagieren und man deshalb eine hervorragende Methode zu deren Bestimmung erhält. Darüber hinaus könnten diese Messungen auch indirekt dazu führen, dass man die Polarisation des Ionenstrahls bestimmen kann. Damit würden sich neue experimentelle Möglichkeiten sowohl in der Atom– als auch der Kernphysik ergeben. In dieser Dissertation werden zunächst diese ersten Untersuchungen zu den Spin–, Polarisations– und Korrelationseffekten systematisch zusammengefasst. Die Dichtematrixtheorie liefert hierzu die geeignete Methode. Mit dieser Methode werden dann die allgemeinen Gleichungen für die Zweistufen–Rekombination hergeleitet. In diesem Prozess wird ein Elektron zunächst radiativ in einen angeregten Zustand eingefangen, der dann im zweiten Schritt unter Emission des zweiten (charakteristischen) Photons in den Grundzustand übergeht. Diese Gleichungen können natürlich auf beliebige Mehrstufen– sowie Einstufen–Prozesse erweitert werden. Im direkten Elektroneneinfang in den Grundzustand wurde die ”lineare” Polarisation der Rekombinationsphotonen untersucht. Es wurde gezeigt, dass man damit eine Möglichkeit zur Bestimmung der Polarisation der Teilchen im Eingangskanal des Schwerionenstoßes hat. Rechnungen zur Rekombination bei nackten U92+ Projektilen zeigen z. B., dass die Spinpolarisation der einfallenden Elektronen zu einer Drehung der linearen Polarisation der emittierten Photonen aus der Streuebene heraus führt. Diese Polarisationdrehung kann mit neu entwickelten orts– und polarisationsempfindlichen Festkörperdetektoren gemessen werden. Damit erhält man eine Methode zur Messung der Polarisation der einfallenden Elektronen und des Ionenstrahls. Die K–Schalen–Rekombination ist ein einfaches Beispiel eines Ein–Stufen–Prozesses. Das am besten bekannte Beispiel der Zwei–Stufen–Rekombination ist der Elektroneneinfang in den 2p3/2–Zustand des nackten Ions und anschließendem Lyman–1–Zerfall (2p3/2 ! 1s1/2). Im Rahmen der Dichte–Matrix–Theorie wurden sowohl die Winkelverteilung als auch die lineare Polarisation der charakteristischen Photonen untersucht. Beide (messbaren) Größen werden beträchtlich durch die Interferenz des E1–Kanals (elektrischer Dipol) mit dem viel schwächeren M2–Kanal (magnetischer Quadrupol) beeinflusst. Für die Winkelverteilung des Lyman–1 Zerfalls im Wasserstoff–ähnlichen Uran führt diese E1–M2–Mischung zu einem 30%–Effekt. Die Berücksichtigung dieser Interferenz behebt die bisher vorhandene Diskrepanz von Theorie und Experiment beim Alignment des 2p3/2–Zustands. Neben diesen Ein–Teichen–Querschnitten (Messung des Einfangphotons oder des charakteristischen Photons) wurde auch die Korrelation zwischen den beiden berechnet. Diese Korrelationen sollten in X–X–Koinzidenz–Messungen beobbachtbar sein. Der Schwerpunkt dieser Untersuchungen lag bei der Photon–Photon–Winkelkorrelation, die experimentell am einfachsten zu messen ist. In dieser Arbeit wurden ausführliche Berechnungen der koinzidenten X–X–Winkelverteilungen beim Elektroneneinfang in den 2p3/2–Zustand des nackten Uranions und beim anschließenden Lyman–1–Übergang durchgeführt. Wie bereits erwähnt, hängt die Winkelverteilung des charakteristischen Photons nicht nur vom Winkel des Rekombinationsphotons, sondern auch stark von der Spin–Polarisation der einfallenden Teilchen ab. Damit eröffnet sich eine zweite Möglichkeit zur Messung der Polaristion des einfallenden Ionenstrahls bzw. der einfallenden Elektronen.

Effect of nuclear motion on the energy eigenvalues in muonic atoms

I have investigated the effect of the nuclear motion on the energy eigenvalues in muonic atoms. In addition to the usually used reduced-mass correction, I have calculated the relativistic influences including the magnetic and retardation interaction between the nucleus and the muon for the inner orbitals of muonic atoms.

Femtosecond time-resolved wave packet motion in molecular multiphoton ionization and fragmentation

The dynamics of molecular multiphoton ionization and fragmentation of a diatomic molecule (Na_2) have been studied in molecular beam experiments. Femtosecond laser pulses from an amplified colliding-pulse mode-locked (CPM) ring dye laser are employed to induce and probe the molecular transitions. The final continuum states are analyzed by photoelectron spectroscopy, by ion mass spectrometry and by measuring the kinetic energy of the formed ionic fragments. Pump-probe spectra employing 70-fs laser pulses have been measured to study the time dependence of molecular multiphoton ionization and fragmentation. The oscillatory structure of the transient spectra showing the dynamics on the femtosecond time scale can best be understood in terms of the motion of wave packets in bound molecular potentials. The transient Na_2^+ ionization and the transient Na^+ fragmentation spectra show that contributions from direct photoionization of a singly excited electronic state and from excitation and autoionization of a bound doubly excited molecular state determine the time evolution of molecular multiphoton ionization.

Generating Compliant Motion of Objects with an Articulated Hand

The flexibility of the robot is the key to its success as a viable aid to production. Flexibility of a robot can be explained in two directions. The first is to increase the physical generality of the robot such that it can be easily reconfigured to handle a wide variety of tasks. The second direction is to increase the ability of the robot to interact with its environment such that tasks can still be successfully completed in the presence of uncertainties. The use of articulated hands are capable of adapting to a wide variety of grasp shapes, hence reducing the need for special tooling. The availability of low mass, high bandwidth points close to the manipulated object also offers significant improvements I the control of fine motions. This thesis provides a framework for using articulated hands to perform local manipulation of objects. N particular, it addresses the issues in effecting compliant motions of objects in Cartesian space. The Stanford/JPL hand is used as an example to illustrate a number of concepts. The examples provide a unified methodology for controlling articulated hands grasping with point contacts. We also present a high-level hand programming system based on the methodologies developed in this thesis. Compliant motion of grasped objects and dexterous manipulations can be easily described in the LISP-based hand programming language.

Three-Dimensional Motion Estimation Using Shading Information in Multiple Frames

A new formulation for recovering the structure and motion parameters of a moving patch using both motion and shading information is presented. It is based on a new differential constraint equation (FICE) that links the spatiotemporal gradients of irradiance to the motion and structure parameters and the temporal variations of the surface shading. The FICE separates the contribution to the irradiance spatiotemporal gradients of the gradients due to texture from those due to shading and allows the FICE to be used for textured and textureless surface. The new approach, combining motion and shading information, leads directly to two different contributions: it can compensate for the effects of shading variations in recovering the shape and motion; and it can exploit the shading/illumination effects to recover motion and shape when they cannot be recovered without it. The FICE formulation is also extended to multiple frames.

Robot Motion Vision by Fixation

In many motion-vision scenarios, a camera (mounted on a moving vehicle) takes images of an environment to find the "motion'' and shape. We introduce a direct-method called fixation for solving this motion-vision problem in its general case. Fixation uses neither feature-correspondence nor optical-flow. Instead, spatio-temporal brightness gradients are used directly. In contrast to previous direct methods, fixation does not restrict the motion or the environment. Moreover, fixation method neither requires tracked images as its input nor uses mechanical tracking for obtaining fixated images. The experimental results on real images are presented and the implementation issues and techniques are discussed.

The Design of Shape from Motion Constraints

This report presents a set of representations methodologies and tools for the purpose of visualizing, analyzing and designing functional shapes in terms of constraints on motion. The core of the research is an interactive computational environment that provides an explicit visual representation of motion constraints produced by shape interactions, and a series of tools that allow for the manipulation of motion constraints and their underlying shapes for the purpose of design.

Reciprocal Interactions Between Motion and Form Perception

The processes underlying the perceptual analysis of visual form are believed to have minimal interaction with those subserving the perception of visual motion (Livingstone and Hubel, 1987; Victor and Conte, 1990). Recent reports of functionally and anatomically segregated parallel streams in the primate visual cortex seem to support this hypothesis (Ungerlieder and Mishkin, 1982; VanEssen and Maunsell, 1983; Shipp and Zeki, 1985; Zeki and Shipp, 1988; De Yoe et al., 1994). Here we present perceptual evidence that is at odds with this view and instead suggests strong symmetric interactions between the form and motion processes. In one direction, we show that the introduction of specific static figural elements, say 'F', in a simple motion sequence biases an observer to perceive a particular motion field, say 'M'. In the reverse direction, the imposition of the same motion field 'M' on the original sequence leads the observer to perceive illusory static figural elements 'F'. A specific implication of these findings concerns the possible existence of (what we call) motion end-stopped units in the primate visual system. Such units might constitute part of a mechanism for signalling subjective occluding contours based on motion-field discontinuities.

Slow and Smooth: A Bayesian Theory for the Combination of Local Motion Signals in Human Vision

In order to estimate the motion of an object, the visual system needs to combine multiple local measurements, each of which carries some degree of ambiguity. We present a model of motion perception whereby measurements from different image regions are combined according to a Bayesian estimator --- the estimated motion maximizes the posterior probability assuming a prior favoring slow and smooth velocities. In reviewing a large number of previously published phenomena we find that the Bayesian estimator predicts a wide range of psychophysical results. This suggests that the seemingly complex set of illusions arise from a single computational strategy that is optimal under reasonable assumptions.

Biologically Plausible Neural Model for the Recognition of Biological Motion and Actions

The visual recognition of complex movements and actions is crucial for communication and survival in many species. Remarkable sensitivity and robustness of biological motion perception have been demonstrated in psychophysical experiments. In recent years, neurons and cortical areas involved in action recognition have been identified in neurophysiological and imaging studies. However, the detailed neural mechanisms that underlie the recognition of such complex movement patterns remain largely unknown. This paper reviews the experimental results and summarizes them in terms of a biologically plausible neural model. The model is based on the key assumption that action recognition is based on learned prototypical patterns and exploits information from the ventral and the dorsal pathway. The model makes specific predictions that motivate new experiments.

Estimating the motion of an underwater robot from a monocular image sequence

When underwater vehicles perform navigation close to the ocean floor, computer vision techniques can be applied to obtain quite accurate motion estimates. The most crucial step in the vision-based estimation of the vehicle motion consists on detecting matchings between image pairs. Here we propose the extensive use of texture analysis as a tool to ameliorate the correspondence problem in underwater images. Once a robust set of correspondences has been found, the three-dimensional motion of the vehicle can be computed with respect to the bed of the sea. Finally, motion estimates allow the construction of a map that could aid to the navigation of the robot

A Motion compensated filtering approach to remove sunlight flicker in shallow water images

A common problem in video surveys in very shallow waters is the presence of strong light fluctuations, due to sun light refraction. Refracted sunlight casts fast moving patterns, which can significantly degrade the quality of the acquired data. Motivated by the growing need to improve the quality of shallow water imagery, we propose a method to remove sunlight patterns in video sequences. The method exploits the fact that video sequences allow several observations of the same area of the sea floor, over time. It is based on computing the image difference between a given reference frame and the temporal median of a registered set of neighboring images. A key observation is that this difference will have two components with separable spectral content. One is related to the illumination field (lower spatial frequencies) and the other to the registration error (higher frequencies). The illumination field, recovered by lowpass filtering, is used to correct the reference image. In addition to removing the sunflickering patterns, an important advantage of the approach is the ability to preserve the sharpness in corrected image, even in the presence of registration inaccuracies. The effectiveness of the method is illustrated in image sets acquired under strong camera motion containing non-rigid benthic structures. The results testify the good performance and generality of the approach

Proposal of a parallel architecture for a motion detection algorithm

This paper proposes a parallel architecture for estimation of the motion of an underwater robot. It is well known that image processing requires a huge amount of computation, mainly at low-level processing where the algorithms are dealing with a great number of data. In a motion estimation algorithm, correspondences between two images have to be solved at the low level. In the underwater imaging, normalised correlation can be a solution in the presence of non-uniform illumination. Due to its regular processing scheme, parallel implementation of the correspondence problem can be an adequate approach to reduce the computation time. Taking into consideration the complexity of the normalised correlation criteria, a new approach using parallel organisation of every processor from the architecture is proposed

Recovering Euclidean deformable models from stereo-motion

In this paper we present a novel structure from motion (SfM) approach able to infer 3D deformable models from uncalibrated stereo images. Using a stereo setup dramatically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach first calibrates the stereo system automatically and then computes a single metric rigid structure for each frame. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points on the object which have remained rigid throughout the sequence without deforming. The selected rigid points are then used to compute frame-wise shape registration and to extract the motion parameters robustly from frame to frame. Finally, all this information is used in a global optimization stage with bundle adjustment which allows to refine the frame-wise initial solution and also to recover the non-rigid 3D model. We show results on synthetic and real data that prove the performance of the proposed method even when there is no rigid motion in the original sequence

Online Robust 3D Mapping Using Structure from Motion Cues

This paper presents a complete solution for creating accurate 3D textured models from monocular video sequences. The methods are developed within the framework of sequential structure from motion, where a 3D model of the environment is maintained and updated as new visual information becomes available. The camera position is recovered by directly associating the 3D scene model with local image observations. Compared to standard structure from motion techniques, this approach decreases the error accumulation while increasing the robustness to scene occlusions and feature association failures. The obtained 3D information is used to generate high quality, composite visual maps of the scene (mosaics). The visual maps are used to create texture-mapped, realistic views of the scene