Diese Arbeit wird einer Weiterentwicklung der Dichtematrixtheorie und ihrer Anwendung zum Studium ultraschneller laserpulsinduzierter Dynamik in Molekularsystemen in Wechselwirkung mit einem thermischen Bad gewidmet. Zwei grosse Themenkomplexe werden behandelt. Zuerst werden die sogenannten Gedächtniseffekte diskutiert. Diese folgen aus einer reduzierten Beschreibung des Molekularsystems, in der die Umgebungsfreiheitsgrade eliminiert werden. Im zweiten Teil wird die Laserpulssteuerung der dissipativen Molekulardynamik untersucht. Die theoretische Beschreibung von offenen Quantensystemen führt zu einer zeitlich nicht-lokalen Bewegungsgleichung: Die Zeitentwicklung des Molekularsystems hängt von seiner Vergangenheit ab. In dieser Arbeit wird eine numerische Methode zur Lösung der zeitlich nicht-lokalen Bewegungsgleichung entwickelt und mit einem minimalen Modell eines polyatomaren Moleküls unter dissipativem Einfluss der Umgebung getestet. Eine analytische Lösung der Bewegungsgleichung für den speziellen Fall einer sehr langen Gedächtniszeit wurde hergeleitet. Zur Identifizierung solcher Gedächtniseffekte vergleichen wir diese analytische Lösung mit numerischen Rechnungen inklusive Gedächtnis und mit approximativen Rechnungen, die die zeitliche Nicht-Lokalität vernachlässigen. Für eine Anregung mit einem Laserpuls, der kürzer als die Gedächtniszeit des Systems ist, zeigt das Molekularsystem eine erkennbar unterschiedliche Dynamik als ohne Gedächtniss. Die Gedächtniseffekte werden mit abfallender Laserpulslänge deutlich ausgeprägter. Der zweite Teil der Arbeit konzentriert sich auf die Anwendung der Theorie der Optimalen Kontrolle, um die molekulare Dynamik zu steuern. Aus der Theorie der Optimalen Kontrolle erhält man Laserpulse, die bestimmte Aufgaben erfüllen, z.B. die Besetzung gewünschter vibronischer Niveaus des Molekularsystems oder die Platzierung eines Wellenpakets auf einer vorgegebenen Position auf der molekularen Potentialfläche. Als erstes Beispiel haben wir die Kontrolle des dissipativen fotoinduzierten Elektronentransfers in einem Donator-Brückenmolekül-Akzeptor System betrachtet, wobei wir das Gedächtniss vernachlässigt haben. Die Steuerbarkeit des Elektronentransfers wird diskutiert und der Mechanismus, mit dem sie möglich wird, wird identifiziert. Wir haben festgestellt, dass die Steuerung der Elektronentransferreaktionen selbst unter dem Einfluss von Dissipation möglich ist, obwohl die Kontrollausbeute mit steigender Dissipation drastisch abfällt. In Anwesenheit von Dissipation verändert sich auch der Mechanismus der Steuerung. Die experimentelle Ausführbarkeit der Herstellung des aus der Theorie der Optimalen Kontrolle resultierenden Kontrollpulses wird diskutiert und Methoden werden präsentiert, die die Abschätzung der Effizienz ermöglichen, mit der ein Flussigkristall--Laserpulsformer, wie er heute in Experimenten verwendet wird, den gewünschten Puls erzeugen kann. Um zwischen verschiedenen Kontrollaufgaben zu unterscheiden, wird ein quantitatives Mass eingeführt, das die Komplexität der Kontrollaufgabe charakterisiert. Die Theorie der Optimalen Kontrolle wird auch für Molekularsysteme formuliert, die statische Unordnung zeigen, und wird auf ein Ensemble von Molekülen mit zufälligen Orientierungen angewendet. Zum Schluss wird die Bedeutung der Gedächtnisseffekte für die Steuerung der dissipativen Dynamik diskutiert und die Theorie der Optimalen Kontrolle neu formuliert um eine zeitliche Nicht-Lokalität in der Bewegungsgleichung des Molekularsystems zu berücksichtigen. / This work is dedicated to a further development of the density matrix theory and its application to the study of ultrafast laser pulse induced dynamics in molecular systems interacting with a thermal environment. Two topics are considered, first the so-called memory effects are analyzed which result from a reduced description of the molecular system excluding the environmental degrees of freedom. And secondly, the laser pulse control of dissipative molecular dynamics is examined. The theoretical description of open quantum systems results in a time non-local equation of motion so that the evolution of the molecular system depends on its past. In this work a numerical method to solve the time non-local equations of motion has been developed and tested for a minimal model of a polyatomic molecule subject to the dissipative influence of an environment. An analytical solution of the equation of motion for the special case of very long standing memory is also achieved. To identify signatures of such memory effects in general case we compare this analytical solution with numerical calculations involving memory and with approximative computations ignoring time non-locality. For the excitation by a laser pulse shorter than the duration of the memory the molecular systems exhibit noticeably different dynamics than for the absence of the memory. The effects become significantly more pronounced with decreasing laser pulse durations. The second part of the work concentrates on the application of the optimal control theory to guide molecular dynamics. Optimal control theory provides laser pulses which are designed in such a manner to fulfill certain control tasks, e.g. the population of a desired vibrational level of the molecular system or the placement of a wavepacket on a prescribed position on the molecular potential energy surface. As a first example the control of the dissipative photo-induced electron transfer in a donor--bridge--acceptor systems has been particularly considered ignoring the memory. The controllability of the electron transfer has been discussed and the mechanism by which it becomes possible has been identified. We have found the control of electron transfer reactions feasible even under the influence of dissipation although the yield of the control decreases drastically with increasing dissipation. In the presence of dissipation mechanism of the control has been found to change. The feasibility of the reproduction of the control pulses resulting for the optimal control theory in the experiment has been discussed and methods have been presented how to check the efficiency of the reproduction of optimal control pulses by liquid crystal pulse shapers, prevailingly used in modern control experiments. To distinguish different control tasks a quantitative measure has been introduced characterizing complexity of the control task. The optimal control theory has also been formulated for molecular systems showing static disorder and applied on an ensemble of molecules exhibiting random orientations. Finally, the importance of memory effects for the control of dissipative dynamics has been discussed and the optimal control theory has been formulated to account for a time non-locality in the equation of motion for molecular systems.

Face recognition is a field of biometrics that deals with identification of subjects based on features present in the images of their faces. The factors that make face recognition popular and favorite as compared to other biometric methods are easier operation and ability to identify subjects without their knowledge. With these features, face recognition has become an integral part of the present day security systems, targeting a smart and secure world. There are various factors that de ne the performance of a face recognition system. The most important among them are recognition accuracy of algorithm used and time taken for recognition. Recognition accuracy of the face recognition algorithm gets affected by changes in pose, facial expression and illumination along with occlusions in the images. There have been a number of algorithms proposed to enable recognition under these ambient changes. However, it has been hard to and a single algorithm that can efficiently recognize faces in all the above mentioned conditions. Moreover, achieving real time performance for most of the complex face recognition algorithms on embedded platforms has been a challenge. Real-time performance is highly preferred in critical applications such as identification of crime suspects in public. As available software solutions for FR have significantly large latency in recognizing individuals, they are not suitable for such critical real-time applications. This thesis focuses on real-time aspect of FR, where acceleration of the algorithms is achieved by means of parallel hardware architectures. The major contributions of this work are as follows. We target to design a face recognition system that can identify at most 30 faces in each frame of video at 15 frames per second, which amounts to 450 recognitions per second. In addition, we target to achieve good recognition accuracy along with scalability in terms of database size and input image resolutions. To design a system with these specifications, as a first step, we explore algorithms in literature and come up with a hybrid face recognition algorithm. This hybrid algorithm shows good recognition accuracy on face images with changes in illumination, pose and expressions, and also with occlusions. In addition the computations in the algorithm are modular in nature which are suitable for real-time realizations through parallel processing. The face recognition system consists of a face detection module to detect faces in the input image, which is followed by a face recognition module to identify the detected faces. There are well established algorithms and architectures for face detection in literature which can perform detection at 15 frames per second on video frames. Detected faces of different sizes need to be scaled to the size specified by the face recognition module. To meet the real-time constraints, we propose a hardware architecture for real-time bi-cubic convolution interpolation with dynamic scaling factors. To recognize the resized faces in real-time, a scalable parallel pipelined architecture is designed for the hybrid algorithm which can perform 450 recognitions per second on a database containing grayscale images of at most 450 classes on Virtex 6 FPGA. To provide flexibility and programmability, we extend this design to REDEFINE, a multi-core massively parallel reconfigurable architecture. In this design, we come up with FR specific programmable cores termed Scalable Unit for Region Evaluation (SURE) capable of performing modular computations in the hybrid face recognition algorithm. We replicate SUREs in each tile of REDEFINE to construct a face recognition module termed REDEFINE for Face Recognition using SURE Homogeneous Cores (REFRESH). There is a need to learn new unseen faces on-line in practical face recognition systems. Considering this, for real-time on-line learning of unseen face images, we design tiny processors termed VOP, Processor for Vector Operations. VOPs function as coprocessors to process elements under each tile of REDEFINE to accelerate micro vector operations appearing in the synaptic weight computations. We also explore deep neural networks which operate similar to the processing in human brain and capable of working on very large face databases. We explore the field of Random matrix theory to come up with a solution for synaptic weight initialization in deep neural networks for better classification . In addition, we perform design space exploration of hardware architecture for deep convolution networks and conclude with directions for future work.

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