Numerische Integration, angewandt bei der Inferenz in Zustandsraummodellen

In dieser Arbeit werden neuere methodische Entwicklungen aus dem Bereich der Numerischen Integration für die näherungsweise Berechnung von Zustandraummodellen erprobt. Die resultierenden Algorithmen werden bzgl. ihrer Approximationsgüte mit den populären simulationsbasierten Näherungsverfahren verglichen.

Lernen mit einer Hybride aus Lernendem Klassifizierendem System und Selbstorganisierender Karte

Im Forschungsgebiet der Künstlichen Intelligenz, insbesondere im Bereich des maschinellen Lernens, hat sich eine ganze Reihe von Verfahren etabliert, die von biologischen Vorbildern inspiriert sind. Die prominentesten Vertreter derartiger Verfahren sind zum einen Evolutionäre Algorithmen, zum anderen Künstliche Neuronale Netze. Die vorliegende Arbeit befasst sich mit der Entwicklung eines Systems zum maschinellen Lernen, das Charakteristika beider Paradigmen in sich vereint: Das Hybride Lernende Klassifizierende System (HCS) wird basierend auf dem reellwertig kodierten eXtended Learning Classifier System (XCS), das als Lernmechanismus einen Genetischen Algorithmus enthält, und dem Wachsenden Neuralen Gas (GNG) entwickelt. Wie das XCS evolviert auch das HCS mit Hilfe eines Genetischen Algorithmus eine Population von Klassifizierern - das sind Regeln der Form [WENN Bedingung DANN Aktion], wobei die Bedingung angibt, in welchem Bereich des Zustandsraumes eines Lernproblems ein Klassifizierer anwendbar ist. Beim XCS spezifiziert die Bedingung in der Regel einen achsenparallelen Hyperquader, was oftmals keine angemessene Unterteilung des Zustandsraumes erlaubt. Beim HCS hingegen werden die Bedingungen der Klassifizierer durch Gewichtsvektoren beschrieben, wie die Neuronen des GNG sie besitzen. Jeder Klassifizierer ist anwendbar in seiner Zelle der durch die Population des HCS induzierten Voronoizerlegung des Zustandsraumes, dieser kann also flexibler unterteilt werden als beim XCS. Die Verwendung von Gewichtsvektoren ermöglicht ferner, einen vom Neuronenadaptationsverfahren des GNG abgeleiteten Mechanismus als zweites Lernverfahren neben dem Genetischen Algorithmus einzusetzen. Während das Lernen beim XCS rein evolutionär erfolgt, also nur durch Erzeugen neuer Klassifizierer, ermöglicht dies dem HCS, bereits vorhandene Klassifizierer anzupassen und zu verbessern. Zur Evaluation des HCS werden mit diesem verschiedene Lern-Experimente durchgeführt. Die Leistungsfähigkeit des Ansatzes wird in einer Reihe von Lernproblemen aus den Bereichen der Klassifikation, der Funktionsapproximation und des Lernens von Aktionen in einer interaktiven Lernumgebung unter Beweis gestellt.

Chemical composition measurements of cloud condensation nuclei and ice nuclei by aerosol mass spectrometry

In this study the Aerodyne Aerosol Mass Spectrometer (AMS) was used during three laboratory measurement campaigns, FROST1, FROST2 and ACI-03. The FROST campaigns took place at the Leipzig Aerosol Cloud Interaction Simulator (LACIS) at the IfT in Leipzig and the ACI-03 campaign was conducted at the AIDA facility at the Karlsruhe Institute of Technology (KIT). In all three campaigns, the effect of coatings on mineral dust ice nuclei (IN) was investigated. During the FROST campaigns, Arizona Test Dust (ATD) particles of 200, 300 and 400 nm diameter were coated with thin coatings (< 7 nm) of sulphuric acid. At these very thin coatings, the AMS was operated close to its detection limits. Up to now it was not possible to accurately determine AMS detection limits during regular measurements. Therefore, the mathematical tools to analyse the detection limits of the AMS have been improved in this work. It is now possible to calculate detection limits of the AMS under operating conditions, without losing precious time by sampling through a particle filter. The instrument was characterised in more detail to enable correct quantification of the sulphate loadings on the ATD particle surfaces. Correction factors for the instrument inlet transmission, the collection efficiency, and the relative ionisation efficiency have been determined. With these corrections it was possible to quantify the sulphate mass per particle on the ATD after the condensation of sulphuric acid on its surface. The AMS results have been combined with the ice nucleus counter results. This revealed that the IN-efficiency of ATD is reduced when it is coated with sulphuric acid. The reason for this reduction is a chemical reaction of sulphuric acid with the particle's surface. These reactions are increasingly taking place when the aerosol is humidified or heated after the coating with sulphuric acid. A detailed analysis of the solubility and the evaporation temperature of the surface reaction products revealed that most likely aluminium sulphate is produced in these reactions.

Stationary in-situ measurements of aerosols, gaseous pollutants and meteorology : chemical and physical characterization of natural and anthropogenic sources

Natural and anthropogenic emissions of gaseous and particulate matter affect the chemical composition of the atmosphere, impact visibility, air quality, clouds and climate. Concerning climate, a comprehensive characterization of the emergence, composition and transformation of aerosol particles is relevant as their influence on the radiation budget is still rarely understood. Regarding air quality and therefore human health, the formation of atmospheric aerosol particles is of particular importance as freshly formed, small particles penetrate into the human alveolar region and can deposit. Additionally, due to the long residence times of aerosol particles in the atmosphere it is crucial to examine their chemical and physical characteristics.This cumulative dissertation deals with stationary measurements of particles, trace gases and meteorological parameters during the DOMINO (Diel Oxidant Mechanism In relation to Nitrogen Oxide) campaign at the southwest coast of Spain in November/December 2008 and the ship emission campaign on the banks of the Elbe in Freiburg/Elbe in April 2011. Measurements were performed using the Mobile research Laboratory “MoLa” which is equipped with state-of-the-art aerosol particle and trace gas instruments as well as a meteorological station.

New path integral simulation algorithms and their application to creep in the quantum sine-Gordon chain

A path integral simulation algorithm which includes a higher-order Trotter approximation (HOA)is analyzed and compared to an approach which includes the correct quantum mechanical pair interaction (effective Propagator (EPr)). It is found that the HOA algorithmconverges to the quantum limit with increasing Trotter number P as P^{-4}, while the EPr algorithm converges as P^{-2}.The convergence rate of the HOA algorithm is analyzed for various physical systemssuch as a harmonic chain,a particle in a double-well potential, gaseous argon, gaseous helium and crystalline argon. A new expression for the estimator for the pair correlation function in the HOA algorithm is derived. A new path integral algorithm, the hybrid algorithm, is developed.It combines an exact treatment of the quadratic part of the Hamiltonian and thehigher-order Trotter expansion techniques.For the discrete quantum sine-Gordon chain (DQSGC), it is shown that this algorithm works more efficiently than all other improved path integral algorithms discussed in this work. The new simulation techniques developed in this work allow the analysis of theDQSGC and disordered model systems in the highly quantum mechanical regime using path integral molecular dynamics (PIMD)and adiabatic centroid path integral molecular dynamics (ACPIMD).The ground state phonon dispersion relation is calculated for the DQSGC by the ACPIMD method.It is found that the excitation gap at zero wave vector is reduced by quantum fluctuations. Two different phases exist: One phase with a finite excitation gap at zero wave vector, and a gapless phase where the excitation gap vanishes.The reaction of the DQSGC to an external driving force is analyzed at T=0.In the gapless phase the system creeps if a small force is applied, and in the phase with a gap the system is pinned. At a critical force, the systems undergo a depinning transition in both phases and flow is induced. The analysis of the DQSGC is extended to models with disordered substrate potentials. Three different cases are analyzed: Disordered substrate potentials with roughness exponent H=0, H=1/2,and a model with disordered bond length. For all models, the ground state phonon dispersion relation is calculated.