8 resultados para Dynamical Models
em AMS Tesi di Dottorato - Alm@DL - Università di Bologna
Resumo:
The aim of this Thesis is to investigate (i) how common the bimodal Blue Straggler Stars (BSS) radial distribution is in stellar clusters and (ii) which are the physical processes that can produce this bimodality. We discuss possible relations between the properties of the BSS radial distribution and the dynamical state of the hosting clusters by making use of dynamical models and simulations. When relevant, we also discuss the possible links with some cluster "anomalies" and the effects of a massive object (like Imtermediate Mass Black Hole) in the cluster center. To this purpose we present the observational multiwavelength studies of the BSS populations and their radial distributions in 5 GGCs: M5, M55, M2, NGC 2419 and NGC 6388.
Resumo:
Dynamical models of galaxies are a powerful tool to study and understand several astrophysical problems related to galaxy formation and evolution. This thesis is focussed on a particular type of dynamical models, that are widely used in literature, and are based on the solution of the Jeans equations. By means of a numerical Jeans solver code, developed on purpose and able to build state-of-the-art advanced axisymmetric galaxy models, two of the main currently investigated issues in the field of research of early-type galaxies (ETGs) are addressed. The first topic concerns the hot and X-ray emitting gaseous coronae that surround ETGs. The main goal is to explain why flat and rotating galaxies generally exhibit haloes with lower gas temperatures and luminosities with respect to rounder and velocity dispersion supported systems. The second astrophysical problem addressed concerns instead the stellar initial mass function (IMF) of ETGs. Nowadays, this is a very controversial issue due to a growing number of works on ETGs, based on different and independent techniques, that show evidences of a systematic variation of the IMF normalization as a function of galaxy velocity dispersion or mass. These studies are changing the previous opinion that the IMF of ETGs was the same as that of spiral galaxies, and hence universal throughout the whole large family of galaxies.
Resumo:
The way mass is distributed in galaxies plays a major role in shaping their evolution across cosmic time. The galaxy's total mass is usually determined by tracing the motion of stars in its potential, which can be probed observationally by measuring stellar spectra at different distances from the galactic centre, whose kinematics is used to constrain dynamical models. A class of such models, commonly used to accurately determine the distribution of luminous and dark matter in galaxies, is that of equilibrium models. In this Thesis, a novel approach to the design of equilibrium dynamical models, in which the distribution function is an analytic function of the action integrals, is presented. Axisymmetric and rotating models are used to explain observations of a sample of nearby early-type galaxies in the Calar Alto Legacy Integral Field Area survey. Photometric and spectroscopic data for round and flattened galaxies are well fitted by the models, which are then used to get the galaxies' total mass distribution and orbital anisotropy. The time evolution of massive early-type galaxies is also investigated with numerical models. Their structural properties (mass, size, velocity dispersion) are observed to evolve, on average, with redshift. In particular, they appear to be significantly more compact at higher redshift, at fixed stellar mass, so it is interesting to investigate what drives such evolution. This Thesis focuses on the role played by dark-matter haloes: their mass-size and mass-velocity dispersion correlations evolve similarly to the analogous correlations of ellipticals; at fixed halo mass, the haloes are more compact at higher redshift, similarly to massive galaxies; a simple model, in which all the galaxy's size and velocity-dispersion evolution is due to the cosmological evolution of the underlying halo population, reproduces the observed size and velocity-dispersion of massive compact early-type galaxies up to redshift of about 2.
Resumo:
Dynamical models of stellar systems represent a powerful tool to study their internal structure and dynamics, to interpret the observed morphological and kinematical fields, and also to support numerical simulations of their evolution. We present a method especially designed to build axisymmetric Jeans models of galaxies, assumed as stationary and collisionless stellar systems. The aim is the development of a rigorous and flexible modelling procedure of multicomponent galaxies, composed of different stellar and dark matter distributions, and a central supermassive black hole. The stellar components, in particular, are intended to represent different galaxy structures, such as discs, bulges, halos, and can then have different structural (density profile, flattening, mass, scale-length), dynamical (rotation, velocity dispersion anisotropy), and population (age, metallicity, initial mass function, mass-to-light ratio) properties. The theoretical framework supporting the modelling procedure is presented, with the introduction of a suitable nomenclature, and its numerical implementation is discussed, with particular reference to the numerical code JASMINE2, developed for this purpose. We propose an approach for efficiently scaling the contributions in mass, luminosity, and rotational support, of the different matter components, allowing for fast and flexible explorations of the model parameter space. We also offer different methods of the computation of the gravitational potentials associated of the density components, especially convenient for their easier numerical tractability. A few galaxy models are studied, showing internal, and projected, structural and dynamical properties of multicomponent galaxies, with a focus on axisymmetric early-type galaxies with complex kinematical morphologies. The application of galaxy models to the study of initial conditions for hydro-dynamical and $N$-body simulations of galaxy evolution is also addressed, allowing in particular to investigate the large number of interesting combinations of the parameters which determine the structure and dynamics of complex multicomponent stellar systems.
Resumo:
The Assimilation in the Unstable Subspace (AUS) was introduced by Trevisan and Uboldi in 2004, and developed by Trevisan, Uboldi and Carrassi, to minimize the analysis and forecast errors by exploiting the flow-dependent instabilities of the forecast-analysis cycle system, which may be thought of as a system forced by observations. In the AUS scheme the assimilation is obtained by confining the analysis increment in the unstable subspace of the forecast-analysis cycle system so that it will have the same structure of the dominant instabilities of the system. The unstable subspace is estimated by Breeding on the Data Assimilation System (BDAS). AUS- BDAS has already been tested in realistic models and observational configurations, including a Quasi-Geostrophicmodel and a high dimensional, primitive equation ocean model; the experiments include both fixed and“adaptive”observations. In these contexts, the AUS-BDAS approach greatly reduces the analysis error, with reasonable computational costs for data assimilation with respect, for example, to a prohibitive full Extended Kalman Filter. This is a follow-up study in which we revisit the AUS-BDAS approach in the more basic, highly nonlinear Lorenz 1963 convective model. We run observation system simulation experiments in a perfect model setting, and with two types of model error as well: random and systematic. In the different configurations examined, and in a perfect model setting, AUS once again shows better efficiency than other advanced data assimilation schemes. In the present study, we develop an iterative scheme that leads to a significant improvement of the overall assimilation performance with respect also to standard AUS. In particular, it boosts the efficiency of regime’s changes tracking, with a low computational cost. Other data assimilation schemes need estimates of ad hoc parameters, which have to be tuned for the specific model at hand. In Numerical Weather Prediction models, tuning of parameters — and in particular an estimate of the model error covariance matrix — may turn out to be quite difficult. Our proposed approach, instead, may be easier to implement in operational models.
Resumo:
The motivation for the work presented in this thesis is to retrieve profile information for the atmospheric trace constituents nitrogen dioxide (NO2) and ozone (O3) in the lower troposphere from remote sensing measurements. The remote sensing technique used, referred to as Multiple AXis Differential Optical Absorption Spectroscopy (MAX-DOAS), is a recent technique that represents a significant advance on the well-established DOAS, especially for what it concerns the study of tropospheric trace consituents. NO2 is an important trace gas in the lower troposphere due to the fact that it is involved in the production of tropospheric ozone; ozone and nitrogen dioxide are key factors in determining the quality of air with consequences, for example, on human health and the growth of vegetation. To understand the NO2 and ozone chemistry in more detail not only the concentrations at ground but also the acquisition of the vertical distribution is necessary. In fact, the budget of nitrogen oxides and ozone in the atmosphere is determined both by local emissions and non-local chemical and dynamical processes (i.e. diffusion and transport at various scales) that greatly impact on their vertical and temporal distribution: thus a tool to resolve the vertical profile information is really important. Useful measurement techniques for atmospheric trace species should fulfill at least two main requirements. First, they must be sufficiently sensitive to detect the species under consideration at their ambient concentration levels. Second, they must be specific, which means that the results of the measurement of a particular species must be neither positively nor negatively influenced by any other trace species simultaneously present in the probed volume of air. Air monitoring by spectroscopic techniques has proven to be a very useful tool to fulfill these desirable requirements as well as a number of other important properties. During the last decades, many such instruments have been developed which are based on the absorption properties of the constituents in various regions of the electromagnetic spectrum, ranging from the far infrared to the ultraviolet. Among them, Differential Optical Absorption Spectroscopy (DOAS) has played an important role. DOAS is an established remote sensing technique for atmospheric trace gases probing, which identifies and quantifies the trace gases in the atmosphere taking advantage of their molecular absorption structures in the near UV and visible wavelengths of the electromagnetic spectrum (from 0.25 μm to 0.75 μm). Passive DOAS, in particular, can detect the presence of a trace gas in terms of its integrated concentration over the atmospheric path from the sun to the receiver (the so called slant column density). The receiver can be located at ground, as well as on board an aircraft or a satellite platform. Passive DOAS has, therefore, a flexible measurement configuration that allows multiple applications. The ability to properly interpret passive DOAS measurements of atmospheric constituents depends crucially on how well the optical path of light collected by the system is understood. This is because the final product of DOAS is the concentration of a particular species integrated along the path that radiation covers in the atmosphere. This path is not known a priori and can only be evaluated by Radiative Transfer Models (RTMs). These models are used to calculate the so called vertical column density of a given trace gas, which is obtained by dividing the measured slant column density to the so called air mass factor, which is used to quantify the enhancement of the light path length within the absorber layers. In the case of the standard DOAS set-up, in which radiation is collected along the vertical direction (zenith-sky DOAS), calculations of the air mass factor have been made using “simple” single scattering radiative transfer models. This configuration has its highest sensitivity in the stratosphere, in particular during twilight. This is the result of the large enhancement in stratospheric light path at dawn and dusk combined with a relatively short tropospheric path. In order to increase the sensitivity of the instrument towards tropospheric signals, measurements with the telescope pointing the horizon (offaxis DOAS) have to be performed. In this circumstances, the light path in the lower layers can become very long and necessitate the use of radiative transfer models including multiple scattering, the full treatment of atmospheric sphericity and refraction. In this thesis, a recent development in the well-established DOAS technique is described, referred to as Multiple AXis Differential Optical Absorption Spectroscopy (MAX-DOAS). The MAX-DOAS consists in the simultaneous use of several off-axis directions near the horizon: using this configuration, not only the sensitivity to tropospheric trace gases is greatly improved, but vertical profile information can also be retrieved by combining the simultaneous off-axis measurements with sophisticated RTM calculations and inversion techniques. In particular there is a need for a RTM which is capable of dealing with all the processes intervening along the light path, supporting all DOAS geometries used, and treating multiple scattering events with varying phase functions involved. To achieve these multiple goals a statistical approach based on the Monte Carlo technique should be used. A Monte Carlo RTM generates an ensemble of random photon paths between the light source and the detector, and uses these paths to reconstruct a remote sensing measurement. Within the present study, the Monte Carlo radiative transfer model PROMSAR (PROcessing of Multi-Scattered Atmospheric Radiation) has been developed and used to correctly interpret the slant column densities obtained from MAX-DOAS measurements. In order to derive the vertical concentration profile of a trace gas from its slant column measurement, the AMF is only one part in the quantitative retrieval process. One indispensable requirement is a robust approach to invert the measurements and obtain the unknown concentrations, the air mass factors being known. For this purpose, in the present thesis, we have used the Chahine relaxation method. Ground-based Multiple AXis DOAS, combined with appropriate radiative transfer models and inversion techniques, is a promising tool for atmospheric studies in the lower troposphere and boundary layer, including the retrieval of profile information with a good degree of vertical resolution. This thesis has presented an application of this powerful comprehensive tool for the study of a preserved natural Mediterranean area (the Castel Porziano Estate, located 20 km South-West of Rome) where pollution is transported from remote sources. Application of this tool in densely populated or industrial areas is beginning to look particularly fruitful and represents an important subject for future studies.
Resumo:
The research field of my PhD concerns mathematical modeling and numerical simulation, applied to the cardiac electrophysiology analysis at a single cell level. This is possible thanks to the development of mathematical descriptions of single cellular components, ionic channels, pumps, exchangers and subcellular compartments. Due to the difficulties of vivo experiments on human cells, most of the measurements are acquired in vitro using animal models (e.g. guinea pig, dog, rabbit). Moreover, to study the cardiac action potential and all its features, it is necessary to acquire more specific knowledge about single ionic currents that contribute to the cardiac activity. Electrophysiological models of the heart have become very accurate in recent years giving rise to extremely complicated systems of differential equations. Although describing the behavior of cardiac cells quite well, the models are computationally demanding for numerical simulations and are very difficult to analyze from a mathematical (dynamical-systems) viewpoint. Simplified mathematical models that capture the underlying dynamics to a certain extent are therefore frequently used. The results presented in this thesis have confirmed that a close integration of computational modeling and experimental recordings in real myocytes, as performed by dynamic clamp, is a useful tool in enhancing our understanding of various components of normal cardiac electrophysiology, but also arrhythmogenic mechanisms in a pathological condition, especially when fully integrated with experimental data.
Resumo:
The present manuscript focuses on out of equilibrium physics in two dimensional models. It has the purpose of presenting some results obtained as part of out of equilibrium dynamics in its non perturbative aspects. This can be understood in two different ways: the former is related to integrability, which is non perturbative by nature; the latter is related to emergence of phenomena in the out of equilibirum dynamics of non integrable models that are not accessible by standard perturbative techniques. In the study of out of equilibirum dynamics, two different protocols are used througout this work: the bipartitioning protocol, within the Generalised Hydrodynamics (GHD) framework, and the quantum quench protocol. With GHD machinery we study the Staircase Model, highlighting how the hydrodynamic picture sheds new light into the physics of Integrable Quantum Field Theories; with quench protocols we analyse different setups where a non-perturbative description is needed and various dynamical phenomena emerge, such as the manifistation of a dynamical Gibbs effect, confinement and the emergence of Bloch oscillations preventing thermalisation.