An optimal estimator for the correlation of CMB anisotropies with Large Scale Structures and its application to WMAP-7year and NVSS

In the thesis we present the implementation of the quadratic maximum likelihood (QML) method, ideal to estimate the angular power spectrum of the cross-correlation between cosmic microwave background (CMB) and large scale structure (LSS) maps as well as their individual auto-spectra. Such a tool is an optimal method (unbiased and with minimum variance) in pixel space and goes beyond all the previous harmonic analysis present in the literature. We describe the implementation of the QML method in the {\it BolISW} code and demonstrate its accuracy on simulated maps throughout a Monte Carlo. We apply this optimal estimator to WMAP 7-year and NRAO VLA Sky Survey (NVSS) data and explore the robustness of the angular power spectrum estimates obtained by the QML method. Taking into account the shot noise and one of the systematics (declination correction) in NVSS, we can safely use most of the information contained in this survey. On the contrary we neglect the noise in temperature since WMAP is already cosmic variance dominated on the large scales. Because of a discrepancy in the galaxy auto spectrum between the estimates and the theoretical model, we use two different galaxy distributions: the first one with a constant bias $b$ and the second one with a redshift dependent bias $b(z)$. Finally, we make use of the angular power spectrum estimates obtained by the QML method to derive constraints on the dark energy critical density in a flat $\Lambda$CDM model by different likelihood prescriptions. When using just the cross-correlation between WMAP7 and NVSS maps with 1.8° resolution, we show that $\Omega_\Lambda$ is about the 70\% of the total energy density, disfavouring an Einstein-de Sitter Universe at more than 2 $\sigma$ CL (confidence level).

Constraining mass and shape of galaxy clusters through large scale structures

The mass estimation of galaxy clusters is a crucial point for modern cosmology, and can be obtained by several different techniques. In this work we discuss a new method to measure the mass of galaxy clusters connecting the gravitational potential of the cluster with the kinematical properties of its surroundings. We explore the dynamics of the structures located in the region outside virialized cluster, We identify groups of galaxies, as sheets or filaments, in the cluster outer region, and model how the cluster gravitational potential perturbs the motion of these structures from the Hubble fow. This identification is done in the redshift space where we look for overdensities with a filamentary shape. Then we use a radial mean velocity profile that has been found as a quite universal trend in simulations, and we fit the radial infall velocity profile of the overdensities found. The method has been tested on several cluster-size haloes from cosmological N-body simulations giving results in very good agreement with the true values of virial masses of the haloes and orientation of the sheets. We then applied the method to the Coma cluster and even in this case we found a good correspondence with previous. It is possible to notice a mass discrepancy between sheets with different alignments respect to the center of the cluster. This difference can be used to reproduce the shape of the cluster, and to demonstrate that the spherical symmetry is not always a valid assumption. In fact, if the cluster is not spherical, sheets oriented along different axes should feel a slightly different gravitational potential, and so give different masses as result of the analysis described before. Even this estimation has been tested on cosmological simulations and then applied to Coma, showing the actual non-sphericity of this cluster.

The J1030 field: a new window on early large scale structures and faint radio-galaxy populations

The correlations between the evolution of the Super Massive Black Holes (SMBHs) and their host galaxies suggests that the SMBH accretion on sub-pc scales (active galactice nuclei, AGN) is linked to the building of the galaxy over kpc scales, through the so called AGN feedback. Most of the galaxy assembly occurs in overdense large scale structures (LSSs). AGN residing in powerful sources in LSSs, such as the proto-brightest cluster galaxies (BCGs), can affect the evolution of the surrounding intra-cluster medium (ICM) and nearby galaxies. Among distant AGN, high-redshift radio-galaxies (HzRGs) are found to be excellent BCG progenitor candidates. In this Thesis we analyze novel interferometric observations of the so-called "J1030" field centered around the z = 6.3 SDSS Quasar J1030+0524, carried out with the Atacama large (sub-)millimetre array (ALMA) and the Jansky very large array (JVLA). This field host a LSS assembling around a powerful HzRG at z = 1.7 that shows evidence of positive AGN feedback in heating the surrounding ICM and promoting star-formation in multiple galaxies at hundreds kpc distances. We report the detection of gas-rich members of the LSS, including the HzRG. We showed that the LSS is going to evolve into a local massive cluster and the HzRG is the proto-BCG. we unveiled signatures of the proto-BCG's interaction with the surrounding ICM, strengthening the positive AGN feedback scenario. From the JVLA observations of the "J1030" we extracted one of the deepest extra-galactic radio surveys to date (~12.5 uJy at 5 sigma). Exploiting the synergy with the X-ray deep survey (~500 ks) we investigated the relation of the X-ray/radio emission of a X-ray-selected sample, unveiling that the radio emission is powered by different processes (star-formation and AGN), and that AGN-driven sample is mostly composed by radio-quiet objects that display a significant X-ray/radio correlation.

Climate oscillations and species interactions: large-scale congruence but regional differences in the phylogeographic structures of an alpine plant and its monophagous insect

Aim. To predict the fate of alpine interactions involving specialized species, using a monophagous beetle and its host-plant as a case study. Location. The Alps. Methods. We investigated genetic structuring of the herbivorous beetle Oreina gloriosa and its specific host-plant Peucedanum ostruthium. We used genome fingerprinting (in the insect and the plant) and sequence data (in the insect) to compare the distribution of the main gene pools in the two associated species and to estimate divergence time in the insect, a proxy for the temporal origin of the interaction. We quantified the similarity in spatial genetic structures by performing a Procrustes analysis, a tool from the shape theory. Finally, we simulated recolonization of an empty space analogous to the deglaciated Alps just after ice retreat by two lineages from two species showing unbalanced dependence, to examine how timing of the recolonization process, as well as dispersal capacities of associated species, could explain the observed pattern. Results. Contrasting with expectations based on their asymmetrical dependence, patterns in the beetle and plant were congruent at a large scale. Exceptions occurred at a regional scale in areas of admixture, matching known suture zones in Alpine plants. Simulations using a lattice-based model suggested these empirical patterns arose during or soon after recolonization, long after the estimated origin of the interaction c. 0.5 million years ago. Main conclusions. Species-specific interactions are scarce in alpine habitats because glacial cycles have limited opportunities for coevolution. Their fate, however, remains uncertain under climate change. Here we show that whereas most dispersal routes are paralleled at large scale, regional incongruence implies that the destinies of the species might differ under changing climate. This may be a consequence of the host-dependence of the beetle that locally limits the establishment of dispersing insects.

Preferred structures in large-scale circulation and the effect of doubling greenhouse gas concentration in HadCM3

Preferred structures in the surface pressure variability are investigated in and compared between two 100-year simulations of the Hadley Centre climate model HadCM3. In the first (control) simulation, the model is forced with pre-industrial carbon dioxide concentration (1×CO2) and in the second simulation the model is forced with doubled CO2 concentration (2×CO2). Daily winter (December-January-February) surface pressures over the Northern Hemisphere are analysed. The identification of preferred patterns is addressed using multivariate mixture models. For the control simulation, two significant flow regimes are obtained at 5% and 2.5% significance levels within the state space spanned by the leading two principal components. They show a high pressure centre over the North Pacific/Aleutian Islands associated with a low pressure centre over the North Atlantic, and its reverse. For the 2×CO2 simulation, no such behaviour is obtained. At higher-dimensional state space, flow patterns are obtained from both simulations. They are found to be significant at the 1% level for the control simulation and at the 2.5% level for the 2×CO2 simulation. Hence under CO2 doubling, regime behaviour in the large-scale wave dynamics weakens. Doubling greenhouse gas concentration affects both the frequency of occurrence of regimes and also the pattern structures. The less frequent regime becomes amplified and the more frequent regime weakens. The largest change is observed over the Pacific where a significant deepening of the Aleutian low is obtained under CO2 doubling.

Probing large-scale wind structures in Vela X–1 using off-states with INTEGRAL

Vela X–1 is the prototype of the class of wind-fed accreting pulsars in high-mass X-ray binaries hosting a supergiant donor. We have analysed in a systematic way 10 years of INTEGRAL data of Vela X–1 (22–50 keV) and we found that when outside the X-ray eclipse, the source undergoes several luminosity drops where the hard X-rays luminosity goes below ∼3 × 1035 erg s−1, becoming undetected by INTEGRAL. These drops in the X-ray flux are usually referred to as ‘off-states’ in the literature. We have investigated the distribution of these off-states along the Vela X–1 ∼ 8.9 d orbit, finding that their orbital occurrence displays an asymmetric distribution, with a higher probability to observe an off-state near the pre-eclipse than during the post-eclipse. This asymmetry can be explained by scattering of hard X-rays in a region of ionized wind, able to reduce the source hard X-ray brightness preferentially near eclipse ingress. We associate this ionized large-scale wind structure with the photoionization wake produced by the interaction of the supergiant wind with the X-ray emission from the neutron star. We emphasize that this observational result could be obtained thanks to the accumulation of a decade of INTEGRAL data, with observations covering the whole orbit several times, allowing us to detect an asymmetric pattern in the orbital distribution of off-states in Vela X–1.

Large-scale velocity structures in the Horologium-Reticulum supercluster

We present 547 optical redshifts obtained for galaxies in the region of the Horologium-Reticulum supercluster (HRS) using the 6 degrees field (6dF) multifiber spectrograph on the UK Schmidt Telescope at the Anglo-Australian Observatory. The HRS covers an area of more than 12 degrees x 12 degrees on the sky centered at approximately alpha = 03(h)19(m), delta = 50 degrees 02'. Our 6dF observations concentrate on the intercluster regions of the HRS, from which we describe four primary results. First, the HRS spans at least the redshift range from 17,000 to 22,500 km s(-1). Second, the overdensity of galaxies in the intercluster regions of the HRS in this redshift range is estimated to be 2.4, or delta rho/(rho) over bar similar to 1: 4. Third, we find a systematic trend of increasing redshift along a southeast-northwest spatial axis in the HRS, in that the mean redshift of HRS members increases by more than 1500 km s(-1) from southeast to northwest over a 12 degrees region. Fourth, the HRS is bimodal in redshift with a separation of similar to 2500 km s(-1) (35 Mpc) between the higher and lower redshift peaks. This fact is particularly evident if the above spatial-redshift trend is fitted and removed. In short, the HRS appears to consist of two components in redshift space, each one exhibiting a similar systematic spatial-redshift trend along a southeast-northwest axis. Lastly, we compare these results from the HRS with the Shapley supercluster and find similar properties and large-scale features.

Microfabrics in carbonate mylonites along a large-scale shear zone (Helvetic Alps)

Carbonate mylonites with varying proportions of second-phase minerals were collected at positions of increasing metamorphic grade along the basal thrust of the Morcles nappe (Helvetic nappes, Switzerland). Variations of temperature, stress, and strain rate, changes in chemistry of solid and fluid phases, and differing degrees of strain localization and annealing were tracked by measuring the shapes, mean sizes, and size distributions of both matrix and second-phase grains, as well as crystal preferred orientation (CPO) of the matrix. Field structures suggest that strain rate was constant along the fault. The mean and distribution of the calcite grain sizes were affected most profoundly by temperature: Increased temperature, presumably accompanied by decreased stress, correlated with larger mean sizes and wider size distributions. At a given location, the matrix grains in mylonites with more second-phase particles are, on average, smaller, have narrower size distributions, and have more elongate shapes. For example, mylonites with 50 vol.% of second phases have matrix grain sizes half that of pure mylonites. Changes in calcite chemistry and the presence of synkinematic fluids seemed to influence microfabric only weakly. Temporal variations in conditions, such as exhumation-induced cooling, apparently provoke changes in temperature, stress, and strain rate along the nappe. These changes result in further strain localization during retrograde conditions and cause the grain size to be reduced by an additional 50%. The matrix CPO strengthens with increasing temperature or strain, but weakens and rotates with increasing second-phase content, These fabric changes suggest differing rates of grain growth, grain size reduction, and development of CPO owing to variations in the deformation conditions and, perhaps, mechanisms. To interpret natural mylonite structures or to extrapolate mechanical data to natural situations requires careful characterization of the microfabric, and, in particular, second-phase minerals. (c) 2007 Elsevier B.V, All rights reserved.

The effects of physiologically plausible connectivity structure on local and global dynamics in large scale brain models.

Functionally relevant large scale brain dynamics operates within the framework imposed by anatomical connectivity and time delays due to finite transmission speeds. To gain insight on the reliability and comparability of large scale brain network simulations, we investigate the effects of variations in the anatomical connectivity. Two different sets of detailed global connectivity structures are explored, the first extracted from the CoCoMac database and rescaled to the spatial extent of the human brain, the second derived from white-matter tractography applied to diffusion spectrum imaging (DSI) for a human subject. We use the combination of graph theoretical measures of the connection matrices and numerical simulations to explicate the importance of both connectivity strength and delays in shaping dynamic behaviour. Our results demonstrate that the brain dynamics derived from the CoCoMac database are more complex and biologically more realistic than the one based on the DSI database. We propose that the reason for this difference is the absence of directed weights in the DSI connectivity matrix.

Dynamics in large scale networks

In this thesis we study the properties of two large dynamic networks, the competition network of advertisers on the Google and Bing search engines and the dynamic network of friend relationships among avatars in the massively multiplayer online game (MMOG) Planetside 2. We are particularly interested in removal patterns in these networks. Our main finding is that in both of these networks the nodes which are most commonly removed are minor near isolated nodes. We also investigate the process of merging of two large networks using data captured during the merger of servers of Planetside 2. We found that the original network structures do not really merge but rather they get gradually replaced by newcomers not associated with the original structures. In the final part of the thesis we investigate the concept of motifs in the Barabási-Albert random graph. We establish some bounds on the number of motifs in this graph.

A study of the large-scale structure of the wind of WR 134

Diverses méthodes ont été utilisées pour étudier les étoiles Wolf-Rayet (WR) dans le but de comprendre les phénomènes physiques variés qui prennent place dans leur vent dense. Pour étudier la variabilité qui n'est pas strictement périodique et ayant des caractéristiques différentes d'une époque à l'autre, il faut observer pendant des périodes de temps suffisamment longues en adopter un échantillonnage temporel élevé pour être en mesure d'identifier les phénomènes physiques sous-jacents. À l'été 2013, des astronomes professionnels et amateurs du monde entier ont contribué à une campagne d'observation de 4 mois, principalement en spectroscopie, mais aussi en photométrie, polarimétrie et en interférométrie, pour observer les 3 premières étoiles Wolf-Rayet découvertes: WR 134 (WN6b), WR 135 (WC8) et WR 137 (WC7pd + O9). Chacune de ces étoiles est intéressante à sa manière, chacune présentant une variété différente de structures dans son vent. Les données spectroscopiques de cette campagne ont été réduites et analysées pour l'étoile présumée simple WR 134 pour mieux comprendre le comportement de sa variabilité périodique à long terme dans le cadre d'une étude des régions d'interactions en corotation (CIRs) qui se retrouvent dans son vent. Les résultats de cette étude sont présentés dans ce mémoire.

Large-scale coupled-cluster calculations

Coupled-cluster theory provides one of the most successful concepts in electronic-structure theory. This work covers the parallelization of coupled-cluster energies, gradients, and second derivatives and its application to selected large-scale chemical problems, beside the more practical aspects such as the publication and support of the quantum-chemistry package ACES II MAB and the design and development of a computational environment optimized for coupled-cluster calculations. The main objective of this thesis was to extend the range of applicability of coupled-cluster models to larger molecular systems and their properties and therefore to bring large-scale coupled-cluster calculations into day-to-day routine of computational chemistry. A straightforward strategy for the parallelization of CCSD and CCSD(T) energies, gradients, and second derivatives has been outlined and implemented for closed-shell and open-shell references. Starting from the highly efficient serial implementation of the ACES II MAB computer code an adaptation for affordable workstation clusters has been obtained by parallelizing the most time-consuming steps of the algorithms. Benchmark calculations for systems with up to 1300 basis functions and the presented applications show that the resulting algorithm for energies, gradients and second derivatives at the CCSD and CCSD(T) level of theory exhibits good scaling with the number of processors and substantially extends the range of applicability. Within the framework of the ’High accuracy Extrapolated Ab initio Thermochemistry’ (HEAT) protocols effects of increased basis-set size and higher excitations in the coupled- cluster expansion were investigated. The HEAT scheme was generalized for molecules containing second-row atoms in the case of vinyl chloride. This allowed the different experimental reported values to be discriminated. In the case of the benzene molecule it was shown that even for molecules of this size chemical accuracy can be achieved. Near-quantitative agreement with experiment (about 2 ppm deviation) for the prediction of fluorine-19 nuclear magnetic shielding constants can be achieved by employing the CCSD(T) model together with large basis sets at accurate equilibrium geometries if vibrational averaging and temperature corrections via second-order vibrational perturbation theory are considered. Applying a very similar level of theory for the calculation of the carbon-13 NMR chemical shifts of benzene resulted in quantitative agreement with experimental gas-phase data. The NMR chemical shift study for the bridgehead 1-adamantyl cation at the CCSD(T) level resolved earlier discrepancies of lower-level theoretical treatment. The equilibrium structure of diacetylene has been determined based on the combination of experimental rotational constants of thirteen isotopic species and zero-point vibrational corrections calculated at various quantum-chemical levels. These empirical equilibrium structures agree to within 0.1 pm irrespective of the theoretical level employed. High-level quantum-chemical calculations on the hyperfine structure parameters of the cyanopolyynes were found to be in excellent agreement with experiment. Finally, the theoretically most accurate determination of the molecular equilibrium structure of ferrocene to date is presented.

Information content: assessing meso-scale structures in complex networks

We propose a novel measure to assess the presence of meso-scale structures in complex networks. This measure is based on the identi?cation of regular patterns in the adjacency matrix of the network, and on the calculation of the quantity of information lost when pairs of nodes are iteratively merged. We show how this measure is able to quantify several meso-scale structures, like the presence of modularity, bipartite and core-periphery con?gurations, or motifs. Results corresponding to a large set of real networks are used to validate its ability to detect non-trivial topological patterns.

Neurite, a finite difference large scale parallel program for the simulation of the electrical signal propagation in neurites under mechanical loading

With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, function of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells has only very recently been proposed (Jerusalem et al., 2013). In this paper, we present the implementation details of Neurite: the finite difference parallel program used in this reference. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite-explicit and implicit-were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between lectrophysiology and mechanics (Jerusalem et al., 2013). This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon, a segmented dendritic tree, and a damaged axon. The capabilities of the program to deal with large scale scenarios, segmented neuronal structures, and functional deficits under mechanical loading are specifically highlighted.