A novel functional renormalization group framework for gauge theories and gravity

In this thesis we develop further the functional renormalization group (RG) approach to quantum field theory (QFT) based on the effective average action (EAA) and on the exact flow equation that it satisfies. The EAA is a generalization of the standard effective action that interpolates smoothly between the bare action for krightarrowinfty and the standard effective action rnfor krightarrow0. In this way, the problem of performing the functional integral is converted into the problem of integrating the exact flow of the EAA from the UV to the IR. The EAA formalism deals naturally with several different aspects of a QFT. One aspect is related to the discovery of non-Gaussian fixed points of the RG flow that can be used to construct continuum limits. In particular, the EAA framework is a useful setting to search for Asymptotically Safe theories, i.e. theories valid up to arbitrarily high energies. A second aspect in which the EAA reveals its usefulness are non-perturbative calculations. In fact, the exact flow that it satisfies is a valuable starting point for devising new approximation schemes. In the first part of this thesis we review and extend the formalism, in particular we derive the exact RG flow equation for the EAA and the related hierarchy of coupled flow equations for the proper-vertices. We show how standard perturbation theory emerges as a particular way to iteratively solve the flow equation, if the starting point is the bare action. Next, we explore both technical and conceptual issues by means of three different applications of the formalism, to QED, to general non-linear sigma models (NLsigmaM) and to matter fields on curved spacetimes. In the main part of this thesis we construct the EAA for non-abelian gauge theories and for quantum Einstein gravity (QEG), using the background field method to implement the coarse-graining procedure in a gauge invariant way. We propose a new truncation scheme where the EAA is expanded in powers of the curvature or field strength. Crucial to the practical use of this expansion is the development of new techniques to manage functional traces such as the algorithm proposed in this thesis. This allows to project the flow of all terms in the EAA which are analytic in the fields. As an application we show how the low energy effective action for quantum gravity emerges as the result of integrating the RG flow. In any treatment of theories with local symmetries that introduces a reference scale, the question of preserving gauge invariance along the flow emerges as predominant. In the EAA framework this problem is dealt with the use of the background field formalism. This comes at the cost of enlarging the theory space where the EAA lives to the space of functionals of both fluctuation and background fields. In this thesis, we study how the identities dictated by the symmetries are modified by the introduction of the cutoff and we study so called bimetric truncations of the EAA that contain both fluctuation and background couplings. In particular, we confirm the existence of a non-Gaussian fixed point for QEG, that is at the heart of the Asymptotic Safety scenario in quantum gravity; in the enlarged bimetric theory space where the running of the cosmological constant and of Newton's constant is influenced by fluctuation couplings.

Kinetic modeling and experiments on gas uptake and chemical transformation of organic aerosol in the atmosphere

Aerosolpartikel beeinflussen das Klima durch Streuung und Absorption von Strahlung sowie als Nukleations-Kerne für Wolkentröpfchen und Eiskristalle. Darüber hinaus haben Aerosole einen starken Einfluss auf die Luftverschmutzung und die öffentliche Gesundheit. Gas-Partikel-Wechselwirkunge sind wichtige Prozesse, weil sie die physikalischen und chemischen Eigenschaften von Aerosolen wie Toxizität, Reaktivität, Hygroskopizität und optische Eigenschaften beeinflussen. Durch einen Mangel an experimentellen Daten und universellen Modellformalismen sind jedoch die Mechanismen und die Kinetik der Gasaufnahme und der chemischen Transformation organischer Aerosolpartikel unzureichend erfasst. Sowohl die chemische Transformation als auch die negativen gesundheitlichen Auswirkungen von toxischen und allergenen Aerosolpartikeln, wie Ruß, polyzyklische aromatische Kohlenwasserstoffe (PAK) und Proteine, sind bislang nicht gut verstanden.rn Kinetische Fluss-Modelle für Aerosoloberflächen- und Partikelbulk-Chemie wurden auf Basis des Pöschl-Rudich-Ammann-Formalismus für Gas-Partikel-Wechselwirkungen entwickelt. Zunächst wurde das kinetische Doppelschicht-Oberflächenmodell K2-SURF entwickelt, welches den Abbau von PAK auf Aerosolpartikeln in Gegenwart von Ozon, Stickstoffdioxid, Wasserdampf, Hydroxyl- und Nitrat-Radikalen beschreibt. Kompetitive Adsorption und chemische Transformation der Oberfläche führen zu einer stark nicht-linearen Abhängigkeit der Ozon-Aufnahme bezüglich Gaszusammensetzung. Unter atmosphärischen Bedingungen reicht die chemische Lebensdauer von PAK von wenigen Minuten auf Ruß, über mehrere Stunden auf organischen und anorganischen Feststoffen bis hin zu Tagen auf flüssigen Partikeln. rn Anschließend wurde das kinetische Mehrschichtenmodell KM-SUB entwickelt um die chemische Transformation organischer Aerosolpartikel zu beschreiben. KM-SUB ist in der Lage, Transportprozesse und chemische Reaktionen an der Oberfläche und im Bulk von Aerosol-partikeln explizit aufzulösen. Es erforder im Gegensatz zu früheren Modellen keine vereinfachenden Annahmen über stationäre Zustände und radiale Durchmischung. In Kombination mit Literaturdaten und neuen experimentellen Ergebnissen wurde KM-SUB eingesetzt, um die Effekte von Grenzflächen- und Bulk-Transportprozessen auf die Ozonolyse und Nitrierung von Protein-Makromolekülen, Ölsäure, und verwandten organischen Ver¬bin-dungen aufzuklären. Die in dieser Studie entwickelten kinetischen Modelle sollen als Basis für die Entwicklung eines detaillierten Mechanismus für Aerosolchemie dienen sowie für das Herleiten von vereinfachten, jedoch realistischen Parametrisierungen für großskalige globale Atmosphären- und Klima-Modelle. rn Die in dieser Studie durchgeführten Experimente und Modellrechnungen liefern Beweise für die Bildung langlebiger reaktiver Sauerstoff-Intermediate (ROI) in der heterogenen Reaktion von Ozon mit Aerosolpartikeln. Die chemische Lebensdauer dieser Zwischenformen beträgt mehr als 100 s, deutlich länger als die Oberflächen-Verweilzeit von molekularem O3 (~10-9 s). Die ROIs erklären scheinbare Diskrepanzen zwischen früheren quantenmechanischen Berechnungen und kinetischen Experimenten. Sie spielen eine Schlüsselrolle in der chemischen Transformation sowie in den negativen Gesundheitseffekten von toxischen und allergenen Feinstaubkomponenten, wie Ruß, PAK und Proteine. ROIs sind vermutlich auch an der Zersetzung von Ozon auf mineralischem Staub und an der Bildung sowie am Wachstum von sekundären organischen Aerosolen beteiligt. Darüber hinaus bilden ROIs eine Verbindung zwischen atmosphärischen und biosphärischen Mehrphasenprozessen (chemische und biologische Alterung).rn Organische Verbindungen können als amorpher Feststoff oder in einem halbfesten Zustand vorliegen, der die Geschwindigkeit von heterogenen Reaktionenen und Mehrphasenprozessen in Aerosolen beeinflusst. Strömungsrohr-Experimente zeigen, dass die Ozonaufnahme und die oxidative Alterung von amorphen Proteinen durch Bulk-Diffusion kinetisch limitiert sind. Die reaktive Gasaufnahme zeigt eine deutliche Zunahme mit zunehmender Luftfeuchte, was durch eine Verringerung der Viskosität zu erklären ist, bedingt durch einen Phasenübergang der amorphen organischen Matrix von einem glasartigen zu einem halbfesten Zustand (feuchtigkeitsinduzierter Phasenübergang). Die chemische Lebensdauer reaktiver Verbindungen in organischen Partikeln kann von Sekunden bis zu Tagen ansteigen, da die Diffusionsrate in der halbfesten Phase bei niedriger Temperatur oder geringer Luftfeuchte um Größenordnungen absinken kann. Die Ergebnisse dieser Studie zeigen wie halbfeste Phasen die Auswirkung organischeer Aerosole auf Luftqualität, Gesundheit und Klima beeinflussen können. rn

Mean curvature flow in SE (2) and applications to visual perception

Our goal in this thesis is to provide a result of existence of the degenerate non-linear, non-divergence PDE which describes the mean curvature flow in the Lie group SE(2) equipped with a sub-Riemannian metric. The research is motivated by problems of visual completion and models of the visual cortex.

Numerical modelling of fluid-structure interaction with application in hemodynamics

The thesis deals with numerical algorithms for fluid-structure interaction problems with application in blood flow modelling. It starts with a short introduction on the mathematical description of incompressible viscous flow with non-Newtonian viscosity and a moving linear viscoelastic structure. The mathematical model consists of the generalized Navier-Stokes equation used for the description of fluid flow and the generalized string model for structure movement. The arbitrary Lagrangian-Eulerian approach is used in order to take into account moving computational domain. A part of the thesis is devoted to the discussion on the non-Newtonian behaviour of shear-thinning fluids, which is in our case blood, and derivation of two non-Newtonian models frequently used in the blood flow modelling. Further we give a brief overview on recent fluid-structure interaction schemes with discussion about the difficulties arising in numerical modelling of blood flow. Our main contribution lies in numerical and experimental study of a new loosely-coupled partitioned scheme called the kinematic splitting fluid-structure interaction algorithm. We present stability analysis for a coupled problem of non-Newtonian shear-dependent fluids in moving domains with viscoelastic boundaries. Here, we assume both, the nonlinearity in convective as well is diffusive term. We analyse the convergence of proposed numerical scheme for a simplified fluid model of the Oseen type. Moreover, we present series of experiments including numerical error analysis, comparison of hemodynamic parameters for the Newtonian and non-Newtonian fluids and comparison of several physiologically relevant computational geometries in terms of wall displacement and wall shear stress. Numerical analysis and extensive experimental study for several standard geometries confirm reliability and accuracy of the proposed kinematic splitting scheme in order to approximate fluid-structure interaction problems.

Modelling the dynamic response of rockfall protection barriers

Mountainous areas are prone to natural hazards like rockfalls. Among the many countermeasures, rockfall protection barriers represent an effective solution to mitigate the risk. They are metallic structures designed to intercept rocks falling from unstable slopes, thus dissipating the energy deriving from the impact. This study aims at providing a better understanding of the response of several rockfall barrier types, through the development of rather sophisticated three-dimensional numerical finite elements models which take into account for the highly dynamic and non-linear conditions of such events. The models are built considering the actual geometrical and mechanical properties of real systems. Particular attention is given to the connecting details between the structural components and to their interactions. The importance of the work lies in being able to support a wide experimental activity with appropriate numerical modelling. The data of several full-scale tests carried out on barrier prototypes, as well as on their structural components, are combined with results of numerical simulations. Though the models are designed with relatively simple solutions in order to obtain a low computational cost of the simulations, they are able to reproduce with great accuracy the test results, thus validating the reliability of the numerical strategy proposed for the design of these structures. The developed models have shown to be readily applied to predict the barrier performance under different possible scenarios, by varying the initial configuration of the structures and/or of the impact conditions. Furthermore, the numerical models enable to optimize the design of these structures and to evaluate the benefit of possible solutions. Finally it is shown they can be also used as a valuable supporting tool for the operators within a rockfall risk assessment procedure, to gain crucial understanding of the performance of existing barriers in working conditions.

Gravitational Lensing as a Tool on Galactic and Cosmological Scales

This work considers the reconstruction of strong gravitational lenses from their observed effects on the light distribution of background sources. After reviewing the formalism of gravitational lensing and the most common and relevant lens models, new analytical results on the elliptical power law lens are presented, including new expressions for the deflection, potential, shear and magnification, which naturally lead to a fast numerical scheme for practical calculation. The main part of the thesis investigates lens reconstruction with extended sources by means of the forward reconstruction method, in which the lenses and sources are given by parametric models. The numerical realities of the problem make it necessary to find targeted optimisations for the forward method, in order to make it feasible for general applications to modern, high resolution images. The result of these optimisations is presented in the \textsc{Lensed} algorithm. Subsequently, a number of tests for general forward reconstruction methods are created to decouple the influence of sourced from lens reconstructions, in order to objectively demonstrate the constraining power of the reconstruction. The final chapters on lens reconstruction contain two sample applications of the forward method. One is the analysis of images from a strong lensing survey. Such surveys today contain $\sim 100$ strong lenses, and much larger sample sizes are expected in the future, making it necessary to quickly and reliably analyse catalogues of lenses with a fixed model. The second application deals with the opposite situation of a single observation that is to be confronted with different lens models, where the forward method allows for natural model-building. This is demonstrated using an example reconstruction of the ``Cosmic Horseshoe''. An appendix presents an independent work on the use of weak gravitational lensing to investigate theories of modified gravity which exhibit screening in the non-linear regime of structure formation.

2D and 3D numerical modelling of multilayer detachment folding and salt tectonics

Numerical modelling was performed to study the dynamics of multilayer detachment folding and salt tectonics. In the case of multilayer detachment folding, analytically derived diagrams show several folding modes, half of which are applicable to crustal scale folding. 3D numerical simulations are in agreement with 2D predictions, yet fold interactions result in complex fold patterns. Pre-existing salt diapirs change folding patterns as they localize the initial deformation. If diapir spacing is much smaller than the dominant folding wavelength, diapirs appear in fold synclines or limbs.rnNumerical models of 3D down-building diapirism show that sedimentation rate controls whether diapirs will form and influences the overall patterns of diapirism. Numerical codes were used to retrodeform modelled salt diapirs. Reverse modelling can retrieve the initial geometries of a 2D Rayleigh-Taylor instability with non-linear rheologies. Although intermediate geometries of down-built diapirs are retrieved, forward and reverse modelling solutions deviate. rnFinally, the dynamics of fold-and-thrusts belts formed over a tilted viscous detachment is studied and it is demonstrated that mechanical stratigraphy has an impact on the deformation style, switching from thrust- to folding-dominated. The basal angle of the detachment controls the deformation sequence of the fold-and-thrust belt and results are consistent with critical wedge theory.rn

Microwave breast imaging reconstruction

In this thesis I analyzed the microwave tomography method to recognize breast can- cer. I study how identify the dielectric permittivity, the Helmoltz equation parameter used to model the real physic problem. Through a non linear least squares method I solve a problem of parameters identification; I show the theoric approach and the devel- opment to reach the results. I use the Levenberg-Marquardt algorithm, applied on COMSOL software to multiphysic models; so I do numerical proofs on semplified test problems compared to the specific real problem to solve.

Screening and prediction of erosive potential

The literature on the erosive potential of drinks and other products is summarised, and aspects of the conduct of screening tests as well as possible correlations of the erosive potential with various solution parameters are discussed. The solution parameters that have been suggested as important include pH, acid concentration (with respect to buffer capacity and concentration of undissociated acid), degree of saturation, calcium and phosphate concentrations, and inhibitors of erosion. Based on the available data, it is concluded that the dominant factor in erosion is pH. The effect of buffer capacity seems to be pH dependent. The degree of saturation probably has a non-linear relationship with erosion. While calcium at elevated concentrations is known to reduce erosion effectively, it is not known whether it is important at naturally occurring concentrations. Fluoride at naturally occurring concentrations is inversely correlated with erosive potential, but phosphate is probably not. Natural plant gums, notably pectin, do not inhibit erosion, so they are unlikely to interfere with the prediction of erosive potential. The non-linearity of some solution factors and interactions with pH need to be taken into account when developing multivariate models for predicting the erosive potential of different solutions. Finally, the erosive potential of solutions towards enamel and dentine might differ.

Molybdenum isotope fractionation in pelagic euxinia: Evidence from the modern Black and Baltic Seas

Here we present stable isotope data for vertical profiles of dissolved molybdenum of the modern euxinic water columns of the Black Sea and two deeps of the Baltic Sea. Dissolved molybdenum in all water samples is depleted in salinity-normalized concentration and enriched in the heavy isotope (δ98Mo values up to + 2.9‰) compared to previously published isotope data of sedimentary molybdenum from the same range of water depths. Furthermore, δ98Mo values of all water samples from the Black Sea and anoxic deeps of the Baltic Sea are heavier than open ocean water. The observed isotope fractionation between sediments and the anoxic water column of the Black Sea are in line with the model of thiomolybdates that scavenge to particles under reducing conditions. An extrapolation to a theoretical pure MoS42− solution indicates a fractionation constant between MoS42− and authigenic solid Mo of 0.5 ± 0.3‰. Measured waters with all thiomolybdates coexisting in various proportions show larger but non-linear fractionation. The best explanation for our field observations is Mo scavenging by the thiomolybdates, dominantly — but not exclusively — present in the form of MoS42−. The Mo isotopic compositions of samples from the sediments and anoxic water column of the Baltic Sea are in overall agreement with those of the Black Sea at intermediate depth and corresponding sulphide concentrations. The more dynamic changes of redox conditions in the Baltic deeps complicate the Black Sea-derived relationship between thiomolybdates and Mo isotopic composition. In particular, the occasional flushing/mixing, of the deep waters, affects the corresponding water column and sedimentary data. δ98Mo values of the upper oxic waters of both basins are higher than predicted by mixing models based on salinity variations. The results can be explained by non-conservative behaviour of Mo under suboxic to anoxic conditions in the shallow bottom parts of the basin, most pronounced on the NW shelf of the Black Sea.

Modeling of red blood cell life-spans in hematologically normal populations

Despite the impact of red blood cell (RBC) Life-spans in some disease areas such as diabetes or anemia of chronic kidney disease, there is no consensus on how to quantitatively best describe the process. Several models have been proposed to explain the elimination process of RBCs: random destruction process, homogeneous life-span model, or a series of 4-transit compartment model. The aim of this work was to explore the different models that have been proposed in literature, and modifications to those. The impact of choosing the right model on future outcomes prediction--in the above mentioned areas--was also investigated. Both data from indirect (clinical data) and direct life-span measurement (biotin-labeled data) methods were analyzed using non-linear mixed effects models. Analysis showed that: (1) predictions from non-steady state data will depend on the RBC model chosen; (2) the transit compartment model, which considers variation in life-span in the RBC population, better describes RBC survival data than the random destruction or homogenous life-span models; and (3) the additional incorporation of random destruction patterns, although improving the description of the RBC survival data, does not appear to provide a marked improvement when describing clinical data.

A Functional-Based Distribution Diagnostic for a Linear Model with Correlated Outcomes: Technical Report

Despite the widespread popularity of linear models for correlated outcomes (e.g. linear mixed modesl and time series models), distribution diagnostic methodology remains relatively underdeveloped in this context. In this paper we present an easy-to-implement approach that lends itself to graphical displays of model fit. Our approach involves multiplying the estimated marginal residual vector by the Cholesky decomposition of the inverse of the estimated marginal variance matrix. Linear functions or the resulting "rotated" residuals are used to construct an empirical cumulative distribution function (ECDF), whose stochastic limit is characterized. We describe a resampling technique that serves as a computationally efficient parametric bootstrap for generating representatives of the stochastic limit of the ECDF. Through functionals, such representatives are used to construct global tests for the hypothesis of normal margional errors. In addition, we demonstrate that the ECDF of the predicted random effects, as described by Lange and Ryan (1989), can be formulated as a special case of our approach. Thus, our method supports both omnibus and directed tests. Our method works well in a variety of circumstances, including models having independent units of sampling (clustered data) and models for which all observations are correlated (e.g., a single time series).

Cholesky Residuals for Assessing Normal Errors in a Linear Model with Correlated Outcomes: Technical Report

Despite the widespread popularity of linear models for correlated outcomes (e.g. linear mixed models and time series models), distribution diagnostic methodology remains relatively underdeveloped in this context. In this paper we present an easy-to-implement approach that lends itself to graphical displays of model fit. Our approach involves multiplying the estimated margional residual vector by the Cholesky decomposition of the inverse of the estimated margional variance matrix. The resulting "rotated" residuals are used to construct an empirical cumulative distribution function and pointwise standard errors. The theoretical framework, including conditions and asymptotic properties, involves technical details that are motivated by Lange and Ryan (1989), Pierce (1982), and Randles (1982). Our method appears to work well in a variety of circumstances, including models having independent units of sampling (clustered data) and models for which all observations are correlated (e.g., a single time series). Our methods can produce satisfactory results even for models that do not satisfy all of the technical conditions stated in our theory.

Underestimation of Standard Errors in Multi-Site Time Series Studies

Multi-site time series studies of air pollution and mortality and morbidity have figured prominently in the literature as comprehensive approaches for estimating acute effects of air pollution on health. Hierarchical models are generally used to combine site-specific information and estimate pooled air pollution effects taking into account both within-site statistical uncertainty, and across-site heterogeneity. Within a site, characteristics of time series data of air pollution and health (small pollution effects, missing data, highly correlated predictors, non linear confounding etc.) make modelling all sources of uncertainty challenging. One potential consequence is underestimation of the statistical variance of the site-specific effects to be combined. In this paper we investigate the impact of variance underestimation on the pooled relative rate estimate. We focus on two-stage normal-normal hierarchical models and on under- estimation of the statistical variance at the first stage. By mathematical considerations and simulation studies, we found that variance underestimation does not affect the pooled estimate substantially. However, some sensitivity of the pooled estimate to variance underestimation is observed when the number of sites is small and underestimation is severe. These simulation results are applicable to any two-stage normal-normal hierarchical model for combining information of site-specific results, and they can be easily extended to more general hierarchical formulations. We also examined the impact of variance underestimation on the national average relative rate estimate from the National Morbidity Mortality Air Pollution Study and we found that variance underestimation as much as 40% has little effect on the national average.

COVARIATE-ADJUSTED NONPARAMETRIC ANALYSIS OF MAGNETIC RESONANCE IMAGES USING MARKOV CHAIN MONTE CARLO

Permutation tests are useful for drawing inferences from imaging data because of their flexibility and ability to capture features of the brain that are difficult to capture parametrically. However, most implementations of permutation tests ignore important confounding covariates. To employ covariate control in a nonparametric setting we have developed a Markov chain Monte Carlo (MCMC) algorithm for conditional permutation testing using propensity scores. We present the first use of this methodology for imaging data. Our MCMC algorithm is an extension of algorithms developed to approximate exact conditional probabilities in contingency tables, logit, and log-linear models. An application of our non-parametric method to remove potential bias due to the observed covariates is presented.