Dissertations / Theses on the topic 'Semi-analytic models'

The chemical compositions of the stars and gas in galaxies play a significant role in all their key evolutionary processes, from gas cooling, through star formation, to the production of new heavy elements that are released back into the gas as stars die in supernova explosions. A theoretical explanation of the production of elements heavier than helium (known simply as `metals' in astrophysics) in stars and its distribution throughout galaxies has been developing since the first postulation of stellar nucleosynthesis in the 1920s. However, there are still a number of unanswered questions in the field of galactic chemical evolution (GCE). For example, what is the most accurate way to measure the metallicities in galaxies? What are the relative contributions to GCE from different types of stars? How is this metal-rich material circulated throughout the various components of a galaxy? And how can we explain the seemingly incompatible chemical properties observed in different galaxies in the local Universe? This thesis provides an investigation into the chemical enrichment of galaxies, by utilising both observations of nearby galaxies and sophisticated GCE models within a semi-analytic model of galaxy evolution. Its core aims are a) to better quantify the chemical properties seen in low-redshift galaxies and explain there likely causes, and b) to develop an improved GCE model that can simultaneously reproduce the diverse chemical properties seen in different types of galaxies in the local Universe. With these aims in mind, Chapter 1 outlines the key background knowledge required for such an investigation. It discusses the different methods used for measuring the metallicity of real galaxies, and their various shortcomings. It also describes simple, analytic GCE models, and the sophisticated semi-analytic model, L-Galaxies, that is used to simulate galaxy evolution in detail. In Chapters 2 and 3, I provide an investigation into the relation between stellar mass (M*), star formation rate (SFR), and gas-phase metallicity (Zg) in galaxies. It is shown that the L-Galaxies model reproduces the positive correlation between SFR and Zg in massive galaxies that is seen when using sophisticated, theoretical metallicity diagnostics. This lends support to the use of such diagnostics over simpler, emission-line ratios. It is further shown that, in the semi-analytic model, this SFR-Zg correlation is due to the gradual dilution of the gas in low-SFR, elliptical galaxies, after a gas-rich merger event. A number of signatures of this particular evolution can be seen in these model galaxies at redshift zero, including low gas fractions and low values of (Zg-Z*). Crucially, all of these properties are also seen in nearby elliptical galaxies in the Sloan Digital Sky Survey (SDSS), providing indirect evidence that such an evolutionary process is also occurring in the elliptical galaxy population in the real Universe. In Chapter 4, I present a new, sophisticated GCE model implemented into L-Galaxies, that significantly improves on the previous scheme. It does this by accounting for the delayed enrichment of many chemical elements from stars, of various initial masses and metallicities, via stellar winds and supernovae. This new scheme enables a much more detailed study of the chemical evolution of galaxies, and enables a comparison with a larger range of observational data. In Chapter 5, I demonstrate that this new model is able to simultaneously reproduce the chemical properties observed in a) the gas of local, star-forming galaxies, b) the photospheres of G dwarfs in the Milky Way disc, and c) the integrated stellar populations of nearby elliptical galaxies. Furthermore, the model is able to do this without any significant deviation from the standard framework of galaxy formation in the canonical paradigm of hierarchical structure formation. This can be seen as a significant achievement, which has allowed us to form a much more comprehensive view of GCE than was possible before.
In den entscheidenden Entstehungsprozessen von Galaxien spielt die chemische Zusammensetzung von Sternen und Gas eine bedeutende Rolle: Von der Gaskühlung über die Sternentstehung bis hin zur Produktion neuer schwerer Elemente, die ins Gas zurückgegeben werden, wenn Sterne in Supernovae-Explosionen sterben. Eine theoretische Erklärung der Produktion von schwerer Elementen in Sternen sowie deren Verteilung in Galaxien wurde seit der ersten Erklärung der stellaren Nukleosynthese in den 1920ern entwickelt. Dennoch gibt es immer noch eine Reihe offener Fragen auf dem Gebiet der chemischen Galaxienentwicklung (galactic chemical evolution - GCE). Zum Beispiel: Was ist die genaueste Methode um die Metallizität von Galaxien zu messen? Welches sind die verhältnismäßigen Anteile der GCE bei unterschiedlichen Sternarten? Wie ist das metallreiche Material innerhalb der verschiedenen Teile einer Galaxie verteilt? Wie können wir die scheinbar inkompatiblen chemischen Eigenschaften erklären, die in verschiedenen Galaxien der kosmischen Nachbarschaft beobachtet werden? Diese Doktorarbeit untersucht die chemische Anreicherung von Galaxien in zweierlei Hinsicht: Es werden sowohl Beobachtungen naher Galaxien, als auch differenzierte GCE-Modelle im Rahmen eines semi-analytischen Galaxienentwicklungsmodells verwendet. Folgende Ziele hat die Arbeit: a) Sie soll die chemischen Eigenschaften von Galaxien mit niedriger Rotverschiebung quantifizierbar machen und mögliche Ursachen erklären. b) Es soll ein verbessertes GCE-Modell entwickelt werden, das die verschiedenen chemischen Eigenschaften abbildet, die in den Galaxien der kosmischen Nachbarschaft beobachtet werden können. Aufbauend auf dieser Zielsetzung wird in Kapitel 1 das nötige Hintergrundwissen erläutert, das für das Verständnis der Untersuchung wichtig ist. Dabei geht es um die verschiedenen Messmethoden zur Feststellung der Metallizität echter Galaxien sowie deren Schwächen. Neben einfachen analytischen GCE-Modellen werden auch die semi-analytischen Modelle, L-Galaxies beschrieben. In den Kapiteln 2 und 3 erläutere ich den Zusammenhang von stellar mass (M*), star formation rate (SFR) und der gas-phase metallicity (Zg) in Galaxien. Es zeigt sich, dass das L-Galaxies-Modell den positiven Zusammenhang zwischen SFR und Zg in massiven Galaxien abbildet. Dieser wird auch deutlich, wenn theoretische Metallizitätsdiagnosen zur Anwendung kommen statt einfacherer Diagnosen. Außerdem wird gezeigt, dass im semi-analytischen Modell die Wechselwirkung von SFR-Zg auf eine allmähliche Verdünnung des Gas in elliptischen Galaxien zurückzuführen ist, die nach dem Verschmelzen zweier gas-reicher Galaxien SFR-arm sind. Einige Merkmale dieser besonderen Entstehung, wie beispielsweise eine niedrige Gasfraktion und niedrige (Zg-Z*), können auch in den besagten Modellgalaxien gesehen werden. Entscheidend ist außerdem, dass all diese Eigenschaften auch im Rahmen der Sloan Digital Sky Survey (SDSS) in nahe gelegenen elliptischen Galaxien beobachtet werden. Das ist ein indirekter Beweis dafür, dass es diese Art von evolutionärem Entstehungsprozess tatsächlich in den elliptischen Galaxien unseres Universums gibt. In Kapitel 4 stelle ich ein neues, differenziertes GCE-Modell vor, das in L-Galaxies implementiert wurde. Es ist besser als sein Vorgänger, da es die durch Sternenwinde und Supernoven verzögerte Anreicherung vieler chemischer Elemente von verschiedenen Sternen berücksichtigt. Das neue Modell erlaubt also zum einen eine detailliertere Betrachtung der chemischen Entstehung von Galaxien und zum anderen macht es den Vergleich einer größeren Bandbreite von Beobachtungsdaten möglich. In Kapitel 5 erläutere ich schließlich, dass das neue Modell gleichzeitig die chemischen Eigenschaften reproduzieren kann, die an folgenden Stellen beobachtet werden: a) im Gas lokaler, sternbildender Galaxien. b) in den Photosphären von G-Zwergen auf der Milchstraßen . c) den integrierten Sternenpopulationen elliptischer Galaxien in der Nachbarschaft. Hinzu kommt, dass es das Modell ermöglicht, all dies zu tun, ohne dabei vom Standardrahmen abzuweichen, den unser kanonisches Verständnis der Galaxienentwicklung bildet. Diese bedeutende Errungenschaft macht es uns jetzt möglich, GCE in einem wesentlich umfassenderen Rahmen zu betrachten.

The formation and evolution of galaxies is an interesting subject to study because it incorporates astrophysics from all scales, from the initial perturbations in the early universe creating the large scale structures that produce galaxies, right down to the evolution of stellar populations and their manipulation of the host galaxy. Simulations of galaxy formation allow us to test the various physical recipes against that which is observed in order to build a true and proper picture of what is happening in the real universe. L-Galaxies is a semi-analytic model of galaxy formation built on top of the merger trees from the Millennium dark matter simulation, and is constrained to match certain key observations at low redshift by applying a Monte Carlo Markov Chain (MCMC) method to constrain the free parameters. In using the model to make high redshift predictions of the stellar mass function, UV luminosity function and star formation rate distribution function we found that the model starts to deviate from observational constraints at the highest redshifts, particularly in high mass galaxies. In the case of the UV luminosity function, this is because the current dust model is calibrated at low redshift and lacks sophistication in that it only depends on the cold gas mass and the density of metals. To improve on this we implement a physically motivated dust model that traces the formation of dust from stellar sources, such as in the stellar winds of AGB stars and in the supernovae remnants of massive stars, the growth of dust inside molecular clouds, and the destruction of dust due to supernovae explosions. The model is fully integrated into L-Galaxies such that the evolution of dust is included in all the recipes relevant to the formation and evolution of galaxies, including: star formation; radiative feedback; cooling and reheating; and both major and minor mergers. Our results show a good fit to observations of the dust mass in galaxies both in the local universe and out to high redshift and we note a similar conclusion as in the literature that dust growth inside molecular clouds is not only necessary but the dominant source of the dust mass in these galaxies. However, stellar sources of dust can not be neglected as molecular clouds must first be seeded by dust grains in order for accretion to occur. This could be important in the very early universe, perhaps for the first galaxies that will hopefully be observed by JWST in the future, because these galaxies may not have had sufficient time to seed their molecular clouds and as such the dust produced by these stellar sources would be important for calculating the galaxies true observed luminosity. We finish by discussing the limitations of the model and discuss areas for possible improvement as well as the next steps in using this to better predict the luminosity of galaxies in future models.

We introduce a statistical exploration of the parameter space of the Munich semi-analytic model built upon the Millennium dark matter simulation. This is achieved by applying a Monte Carlo Markov Chain (MCMC) method to constrain the 6 free parameters that define the stellar mass function at redshift zero. The model is tested against three different observational data sets, including the galaxy K-band luminosity function, B −V colours, and the black hole-bulge mass relation, to obtain mean values, confidence limits and likelihood contours for the best fit model. We discuss how the model parameters affect each galaxy property and find that there are strong correlations between them. We analyze to what extent these are simply reflections of the observational constraints, or whether they can lead to improved understanding of the physics of galaxy formation. When all the observations are combined, the need to suppress dwarf galaxies requires the strength of the supernova feedback to be significantly higher in our best-fit solution than in previous work. We interpret this fact as an indication of the need to improve the treatment of low mass objects. As a possible solution, we introduce the process of satellite disruption, caused by tidal forces exerted by central galaxies on their merging companions. We apply similar MCMC sampling techniques to the new model, which allows us to discuss the impact of disruption on the basic physics of the model. The new best fit model has a likelihood four times better than before, reproducing reasonably all the observational constraints, as well as the metallicity of galaxies and predicting intra-cluster light. We interpret this as an indication of the need to include the new recipe. We point out the remaining limitations of the semi-analytic model and discuss possible improvements that might increase its predictive power in the future.

Stellar halos give insight into the initial conditions that existed when a host galaxy first formed and provide details on disrupted satellites via their different stellar populations. An algorithm that is computationally inexpensive compared to hydrodynamic simulations is necessary in order to theoretically study the structure and formation of galactic stellar halos in sufficient detail to probe substructure. CoSANG (Coupling Semi-Analytic/N-body Galaxies) is a new computational method that we are developing which couples pure dark matter N-body simulations with a semi-analytic galaxy formation model. At each timestep, results from the N-body simulation feed into the semi-analytic code, whose results feed back into the N-body code making the evolution of the dark matter and baryonic matter dependent on one another. CoSANG will enable a variety of galaxy formation science, including analysis of stellar populations, halo merging, satellite accretion, supermassive black holes, and indirect and direct dark matter detection.

In this dissertation, I will describe the new simulation code CoSANG. The results from the extensive testing phase on CoSANG will be presented which indicate CoSANG is properly simulating feedback from galaxies within a dark matter halo. I used this validated code to analyze a CoSANG zoom simulation of a 10¹²M solar masses dark matter halo. Results showed a flatter inner halo near the disk and a more spherical outer halo which is expected when a galaxy exists at the center of a dark matter halo. A comparison is made with a simulation run with the same initial conditions, but with the baryonic component simulated using a hydrodynamic algorithm. The semi-analytic model predicted galaxy types better than the hydrodynamic simulation leading to the conclusion that the CoSANG halo is more accurate. I also present a dark matter direct detection analysis on the CoSANG zoom halo to measure the dark matter velocity distributions and modulation amplitudes. The CoSANG results show that the dark matter velocity distribution does not fit well to a Maxwell Boltzmann distribution and the modulation amplitudes derived indicate an anisotropic dark matter velocity distribution. Future work will include tagging dark matter particles with stellar properties to build and evolve a stellar halo.

A study was carried out to determine how well the L-Galaxies 2020 semi-analytic model simulates the stellar halos of galaxies and the intracluster stellar (ICS) components of galaxy clusters. Two galaxy disruption models were tested, namely instantaneous disruption and gradual disruption. Furthermore, two stellar halo profiles were applied to the simulation results: a power-law profile with slope γ = −3.5 and a Navarro-Frenk-White (NFW) profile. In the latter case, the stellar halo stars follow the distribution of the galaxy's dark matter. It was found that a combination of an NFW profile and gradual disruption provided the best results across the widest range of literature data, namely measurements of stellar halo mass, total stellar mass, stellar mass fractions, and stellar halo iron abundances. Gradual disruption of satellite galaxies also resulted in the central galaxies having more massive stellar halos in comparison to instantaneous disruption. Additional stellar halo formation mechanisms, such as in-situ star formation, were not needed, as the stellar halo masses seen in observations can be obtained in L-Galaxies by considering only tidal disruption of infalling satellite galaxies. The number of high mass accretions into the halos of Milky Way-mass galaxies in the gradual disruption model agreed well with simulation literature. It was found that while central galaxies can induce many disruptions of satellite galaxies (over a thousand in some cases), the majority of the Milky Way-sized stellar halos in L-Galaxies are formed by the disruption of one to fourteen satellite galaxies, in good agreement with simulation literature. A population of galaxies with unexpectedly low stellar halo iron abundances was found. These were determined to be a result of disruptions of high mass, low metallicity satellite galaxies. Furthermore, rather than iron or oxygen, carbon was found to be the dominant element produced by stellar halo stars for the majority of redshifts in most high mass central and satellite galaxies, due mainly to asymptotic giant branch stars. The relative contribution of stellar halo stars was found to be minor, however, with circumgalactic medium enrichment from halo stars in comparison to outflows from galactic stars being on average . 1%. For clusters with virial masses exceeding 1.6 × 1014M, the brightest central galaxy and ICS (BCG+ICS) stars contained 42.44% of the total cluster stellar iron content, while the fraction MICS MBCG+MICS was found to be 82.50%, both results being in good agreement with observation.

Several hundred million years after the Big Bang, the Epoch of Reionisation(EoR) started as the photons from the first objects ionised neutral baryons in the Universe. The observations such as the Gunn-Peterson troughs in quasar absorption spectra and the linear polarisation of the cosmic microwave background (CMB) impose strong constraints on reionisation models of the EoR. Recent data provide the rest-frame ultraviolet luminosity of galaxies up to redshift 10. However, the observation of star formations in low mass galaxies is still not practicable. Their star formations are expected to be suppressed by the increase of ionised baryons and greatly affect the reionisation models. We develop a flexible pipeline which utilises the Munich Semi-Analytic Model of galaxy formation, L-Galaxies, and a semi-numerical modelling of cosmic reionisation. This combination allows us to create a self-consistent reionisation simulation in computational models of galaxy formation. We use this pipeline on a high resolution cosmological Nbody simulation to produce the redshift evolution of the star forming galaxies during the EoR. Comparisons of the properties of mock galaxies and the growth of ionised hydrogen bubbles suggest that the reionisation history heavily depends on the suppression models used in the modeling of dwarf galaxy formation. During this research, some numerical flaws of merger tree generation algorithms were identified. We investigated the origins of these problems and present suggestions for solving them.

One of the most fundamental probes of the physics that underpins galaxy evolution is the star formation rate (SFR) as a function of cosmic time. In addition, the statistical prop- erties of galaxy populations are another important key to understand how the universe has been evolving. It is known that the far-infrared emission from galaxies is strongly correlated with obscured star formation and forms a significant part of cosmic infrared background. We thus investigate the variation of the SFR of galaxies over time by com- paring predictions of the L-Galaxies semi-analytic model with observations of the far infrared (FIR) luminosity and number counts. In the first part of this thesis, we follow the star formation histories (SFHs) of galaxies and use these to construct stellar spectra in post-processing. We then contrast model SFHs from the Millennium Simulation with observed ones from the VESPA algorithm as applied to the SDSS-7 catalogue when this has been characterized by mass and colour of galaxies. In order to investigate the SAM model prediction, I extend L-galaxies to predict far infrared fluxes and construct mock catalogues which are fed into SMAP in order to provide simulated maps. LFs have also been estimated for model galaxies at different redshifts. The results are compared with observations from Herschel. To conclude, our model under- estimates the number density of galaxies at bright sources (e.g fluxes above 0.02 Jy) also does not produce high luminosity objects especially at higher redshifts (e.g z > 1) . We show that by fitting the simulated IR luminosity function to observed LIR, our model is able to produce more bright sources at high redshifts and match reasonably well to the observed number counts.

Les préoccupations environnementales actuelles nous amènent à envisager des solutions alternatives, telles que la pile à combustible. Cette dernière malgré ses avantages présente des faiblesses qui ralentissent sa diffusion au sein de l'industrie, entre autres, sa trop courte durée de vie. Face à cette considération, nous proposons d'appliquer le PHM à la PEMFC. Il faut donc développer le pronostic puis considérer son insertion au sein d'un système industriel. Nous choisissons de baser l'approche proposée sur un modèle de comportement, tout en proposant de combler le manque de connaissance concernant le vieillissement de la pile par les données, ce qui nous permet amène à développer une approche hybride. Dans ces travaux, le modèle comportemental est étudié sur des durées de plus en plus grandes pour enfin proposer une prédiction de l'ordre du millier d'heure. Afin de prendre en compte une implantation au sein d'un système réel, une étude sur la généricité et applicabilité de l'approche est réalisée. Ainsi, ces travaux proposent une approche de pronostic hybride basée sur un modèle de comportement et étudie son insertion au sein d'un système réel
The current environmental concerns lead us to consider alternative solutions. The fuel cell can be one of them with numerous advantages, it presents however weaknesses, especially, its life duration which is too short. Face to this issue, we offer to apply the PHM to the PEMFC. For that, it is necessary to develop the prognostics for this application and the possibility of the on-line implementation on an industrial system. It was chosen to base the approach on a behavioral model in which the knowledge gaps are completed with the use of data. So, the approach proposed here, is hybrid. In this work, the behavioral model is studied on laps of time longer in order to finally introduce a prediction of a thousand of hours. Then, the online implementation on a real system is considered with a genericity and an applicability study. This work proposes a hybrid prognostics approach based on a behavioral model and study its implementation on an industrial system

A free water surface finite element model was developed. The method was implemented with the Galerkin approach to solve the Laplace equation in the saturated region. It was developed in the object oriented Visual C ++ computer language to permit easy update and drawing of the adaptive mesh. For each time step, the new water table position was calculated based on flux across the water table, a Brooks-Corey equation mass balance for the unsaturated region, and an equation that calculates water table position for the saturated region. An equation was developed to calculate a drainage transfer coefficient, alpha, based on percentage of perforated area in the drain tube wall. The drainage transfer coefficient was incorporated into the finite element model as a Fourier boundary condition. To validate the finite element model, its results were compared with the Kirkham equation results for steady state recharge of three subsurface drainage systems. The finite element model was used to calibrate a semi-analytical frozen stream tube model for subsurface drainage of heterogeneous soils. The first step in the calibration procedure is to run the finite element model for steady state recharge and calculate the water table height divided by recharge rate (the stream tube resistance to flow) as a function of distance between drains. Least squares regression is used to fit a polynomial logarithmic equation, called the resistance function, to the stream tube resistance to flow vs. distance from the drain curve. A differential equation based on the principle of conservation of mass and application of Darcy's law to the frozen stream tube was solved to obtain an equation that calculates stream tube flow rate and final water table elevation as a function of the resistance function and initial water table elevation. An example was developed for a non-homogeneous subsurface drainage system to illustrate the use of the semi-analytical model to predict water table fall and discharge.

Les progrès réalisés dans les processus de fabrication ont mené vers un contrôle accru des dimensions et de la composition chimique des nanostructures, permettant l’émergence de nouveaux dispositifs appelés Nanosystèmes ElectroMécaniques ou NEMS. Outre leurs propriétés physiques originales, leurs dimensions réduites leurs confèrent un fonctionnement peu coûteux en énergie Ainsi, l’utilisation de l’environnement de tels dispositifs comme source d’énergie est possible. Afin de préserver les avantages liés aux dimensions des NEMS, le système de récupération d’énergie doit présenter un volume réduit. Dans ce contexte, nous étudions les nanoffis de ZnO comme éléments actifs de micro et nanosystèmes de récupération d’énergie à travers deux modèles physiques de nanofils. L’originalité de ces deux modèles vient de la prise en compte du couplage entre les propriétés piezoélectriques et les propriétés semiconductrices du ZnO et de ses effets dans la conversion électromécanique de l’énergie
Recent progresses in manufacturing processes allow a better control of dimensions and chemical composition of nanostructures, This leads to the emergence of a new family of devices known as Nano ElectroMechanical Systems or NEMS. These devices show novel physical properties and functional characteristics due to their reduced size. Besides, their operating power consumption are tiny, making the use of their environment as energy source highly attractive. The design of a generator that scavenge the surrounding energy of the NEMS is quite a challenge; indeed, such a microharvester should be small enough to ensure that the dimensions of the whole autonomous device are still acceptable. in that context, we investigate ZnO nanowires as active elements of piezoelectric nano and microgenerator. We have specially developed two models of nanowire that take into account of the piezoelectric-semiconducting coupling to appreciate its effects on the electromechanical conversion of energy

Magister Scientiae - MSc
We investigate the modelling of radio galaxies within a semi-analytic framework in the Millennium Simulation of the Virgo Consortium. The aim is to assess the radio sources contamination of Sunyaev-Zeldovich (SZ) signatures of clusters of galaxies in Cosmic Microwave Background (CMB) experiments. The modelling is also relevant to the Karoo Array Telescope (MeerKAT) and the Square Kilometre Array (SKA) science. The semi-analytical model consists of N-body simulation, the Millennium Run to trace the merger history of dark matter haloes within the Λ Cold Dark Matter (ΛCDM) cosmology and a follow up of the black hole accretion history and Active Galactic Nuclei (AGN) evolution. We study the growth of the supermassive black hole (SMBH) in galaxy centres and determine the black hole mass accretion conversion into radiation. We identify a model which matches observed radio luminosity function. We describe a model of observed sample of radio surveys at a given frequency and a flux density limit to obtain a model of radio luminosity function (space density of radio sources as a function of redshift) that we compare with our simulated data. We determine the redshift distribution of radio galaxies (FRI), blazars and radio quasars (FRII) in the simulation. We focus the modelling on flat spectrum population of blazars since their jets are collimated towards us and thus constitute the most potential contaminants of the CMB. We determine the spatial and density distribution of radio sources in clusters with a virial mass Mvir 2 1014h−1M and then compute the temperature fluctuations and fluxes produced by these cluster radio sources. Our main results include: the model provides a reasonable match within uncertainties with the model obtained by Dunlop & Peacock (1990) [39] using their best fit of radio luminosity function at redshift z . 0:3. The model underestimates the number of radio sources at high redshift z & 1. Radio sources are concentrated around the centre of clusters with a maximum density at r . 0:1r200 where r200 is the radius within which the density is 200 times the critical density. Radio sources are more concentrated in low mass clusters. The model predicts a surface density profile of radio sources with luminosity P 1023 W.Hz−1 at 1.4 GHz (z . 0:06) in agreement with that of Lin & Mohr (2007) [58] at r . 0:1r200 but underestimates the density in the outskirts of the clusters. BL Lacs and FRI radio galaxies produce non negligible contamination at redshift z . 0:1. They produce a mean temperature fluctuation 4:5 K at redshift z 0:01 which can be at the same level as the kinetic SZE signal produced by the cluster. Blazars constitute potential contaminant of the thermal SZ effect at redshift z 1:0 and z 1:5 at 145 GHz where they produce a mean temperature 300 K - 350 K for an average mass of the cluster.
South Africa

Aim of this thesis is that to furnish some methodologies for the accurate evaluation of the electromagnetic characteristics of a microstrip. This results particularly useful for the extraction of equivalent circuital parameters, needed from circuit simulators to study more complex structures. From an analysis of the available models in literature, it is possible to find that some approximations are usually assumed to simplify the treatment. It can be observed that it is usual to neglect the conductive losses, that nevertheless result more and more remarkable with the increase of the density of the circuits. Besides, the existing models for the analysis of microstrips don't generally take into account the thickness of the structure, if not in a perturbative way. This thesis has the objective to propose some models that try to eliminate or however to reduce the approximation around the finite conductivity and the finite thickness of a microstrip. In the first chapter, general aspects of the microstrips are introduced, shortly examining its uses and the constructive aspects. In the second chapter a lossless microstrip of infinitesimal thickness is examined. Different kinds of sources are examined. The aim of the chapter is to introduce the method that will be used in future. In the third chapter, a microstrip of infinitesimal thickness and finite conductibility is examined. Then the method is generalized to the case of an arbitrary number of coupled microstrips. In the fourth chapter, it is shortly presented a variation of the method previously exposed, studying the problem of a thick strip in the free space. Then, a microstrip of finite thickness is examined. In the thesis, also the computational aspects related to the convergence of the method and to the numerical treatment of the integrals.

It is believed that a wide range of physical processes conspire to shape the observed galaxy population but it remains unsure of their detailed interactions. The semi-analytic model (SAM) of galaxy formation uses multi-dimensional parameterizations of the physical processes of galaxy formation and provides a tool to constrain these underlying physical interactions. Because of the high dimensionality and large uncertainties in the model, the parametric problem of galaxy formation can be profitably tackled with a Bayesian-inference based approach, which allows one to constrain theory with data in a statistically rigorous way. In this thesis, I present a newly developed method to build SAM upon the framework of Bayesian inference. I show that, aided by advanced Markov-Chain Monte-Carlo algorithms, the method has the power to efficiently combine information from diverse data sources, rigorously establish confidence bounds on model parameters, and provide powerful probability-based methods for hypothesis test. Using various data sets (stellar mass function, conditional stellar mass function, K-band luminosity function, and cold gas mass functions) of galaxies in the local Universe, I carry out a series of Bayesian model inferences. The results show that SAM contains huge degeneracies among its parameters, indicating that some of the conclusions drawn previously with the conventional approach may not be truly valid but need to be revisited by the Bayesian approach. Second, some of the degeneracy of the model can be broken by adopting multiple data sets that constrain different aspects of the galaxy population. Third, the inferences reveal that model has challenge to simultaneously explain some important observational results, suggesting that some key physics governing the evolution of star formation and feedback may still be missing from the model. These analyses show clearly that the Bayesian inference based SAM can be used to perform systematic and statistically rigorous investigation of galaxy formation based on various observations and help to design new observations that can effectively discriminate theoretical models.

The human body has antenna characteristics that are not explored in detail to explain some phenomena involving the interaction of electromagnetic fields and the human body. Moreover, the characterization of the human body as antenna unlocks new applications in body area networks for low-power wireless communications by utilizing the human body itself as an antenna. This thesis presents a new theory for explaining the antenna characteristics of the human body in transmission and reception mode. The theory is applied to two areas of study, namely, Human Body Communication (HBC) and whole-body radio-frequency (RF) dosimetry. Based on this, the thesis proposes a new concept where the human body is utilized as an antenna for wireless implant communication.