Non-Markovian stochastic processes and their applications: from anomalous diffusion to time series analysis

This work provides a forward step in the study and comprehension of the relationships between stochastic processes and a certain class of integral-partial differential equation, which can be used in order to model anomalous diffusion and transport in statistical physics. In the first part, we brought the reader through the fundamental notions of probability and stochastic processes, stochastic integration and stochastic differential equations as well. In particular, within the study of H-sssi processes, we focused on fractional Brownian motion (fBm) and its discrete-time increment process, the fractional Gaussian noise (fGn), which provide examples of non-Markovian Gaussian processes. The fGn, together with stationary FARIMA processes, is widely used in the modeling and estimation of long-memory, or long-range dependence (LRD). Time series manifesting long-range dependence, are often observed in nature especially in physics, meteorology, climatology, but also in hydrology, geophysics, economy and many others. We deepely studied LRD, giving many real data examples, providing statistical analysis and introducing parametric methods of estimation. Then, we introduced the theory of fractional integrals and derivatives, which indeed turns out to be very appropriate for studying and modeling systems with long-memory properties. After having introduced the basics concepts, we provided many examples and applications. For instance, we investigated the relaxation equation with distributed order time-fractional derivatives, which describes models characterized by a strong memory component and can be used to model relaxation in complex systems, which deviates from the classical exponential Debye pattern. Then, we focused in the study of generalizations of the standard diffusion equation, by passing through the preliminary study of the fractional forward drift equation. Such generalizations have been obtained by using fractional integrals and derivatives of distributed orders. In order to find a connection between the anomalous diffusion described by these equations and the long-range dependence, we introduced and studied the generalized grey Brownian motion (ggBm), which is actually a parametric class of H-sssi processes, which have indeed marginal probability density function evolving in time according to a partial integro-differential equation of fractional type. The ggBm is of course Non-Markovian. All around the work, we have remarked many times that, starting from a master equation of a probability density function f(x,t), it is always possible to define an equivalence class of stochastic processes with the same marginal density function f(x,t). All these processes provide suitable stochastic models for the starting equation. Studying the ggBm, we just focused on a subclass made up of processes with stationary increments. The ggBm has been defined canonically in the so called grey noise space. However, we have been able to provide a characterization notwithstanding the underline probability space. We also pointed out that that the generalized grey Brownian motion is a direct generalization of a Gaussian process and in particular it generalizes Brownain motion and fractional Brownain motion as well. Finally, we introduced and analyzed a more general class of diffusion type equations related to certain non-Markovian stochastic processes. We started from the forward drift equation, which have been made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation has been interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time-evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the same memory kernel K(t). We developed several applications and derived the exact solutions. Moreover, we considered different stochastic models for the given equations, providing path simulations.

Measurement of the ZZ production cross section and limits on anomalous neutral triple gauge couplings with ATLAS

The main work of this thesis concerns the measurement of the production cross section using LHC 2011 data collected at a center-of-mass energy equal to 7 TeV by the ATLAS detector and resulting in a total integrated luminosity of 4.6 inverse fb. The ZZ total cross section is finally compared with the NLO prediction calculated with modern Monte Carlo generators. In addition, the three differential distributions (∆φ(l,l), ZpT and M4l) are shown unfolded back to the underlying distributions using a Bayesian iterative algorithm. Finally, the transverse momentum of the leading Z is used to provide limits on anoumalus triple gauge couplings forbidden in the Standard Model.

Physico-chemical and microstructural properties of food dispersions

The macroscopic properties of oily food dispersions, such as rheology, mechanical strength, sensory attributes (e.g. mouth feel, texture and even flavour release) and as well as engineering properties are strongly determined by their microstructure, that is considered a key parameter in the understanding of the foods behaviour . In particular the rheological properties of these matrices are largely influenced by their processing techniques, particle size distribution and composition of ingredients. During chocolate manufacturing, mixtures of sugar, cocoa and fat are heated, cooled, pressurized and refined. These steps not only affect particle size reduction, but also break agglomerates and distribute lipid and lecithin-coated particles through the continuous phase, this considerably modify the microstructure of final chocolate. The interactions between the suspended particles and the continuous phase provide information about the existing network and consequently can be associated to the properties and characteristics of the final dispersions. Moreover since the macroscopic properties of food materials, are strongly determined by their microstructure, the evaluation and study of the microstructural characteristics, can be very important for a through understanding of the food matrices characteristics and to get detailed information on their complexity. The aim of this study was investigate the influence of formulation and each process step on the microstructural properties of: chocolate type model systems, dark milk and white chocolate types, and cocoa creams. At the same time the relationships between microstructural changes and the resulting physico-chemical properties of: chocolate type dispersions model systems dark milk and white chocolate were investigated.