Precision Cosmology with Weak Gravitational Lensing

In recent years, cosmological science has developed a highly predictive model for the universe on large scales that is in quantitative agreement with a wide range of astronomical observations. While the number and diversity of successes of this model provide great confidence that our general picture of cosmology is correct, numerous puzzles remain. In this dissertation, I analyze the potential of planned and near future galaxy surveys to provide new understanding of several unanswered questions in cosmology, and address some of the leading challenges to this observational program. In particular, I study an emerging technique called cosmic shear, the weak gravitational lensing produced by large scale structure. I focus on developing strategies to optimally use the cosmic shear signal observed in galaxy imaging surveys to uncover the physics of dark energy and the early universe. In chapter 1 I give an overview of a few unsolved mysteries in cosmology and I motivate weak lensing as a cosmological probe. I discuss the use of weak lensing as a test of general relativity in chapter 2 and assess the threat to such tests presented by our uncertainty in the physics of galaxy formation. Interpreting the cosmic shear signal requires knowledge of the redshift distribution of the lensed galaxies. This redshift distribution will be significantly uncertain since it must be determined photometrically. In chapter 3 I investigate the influence of photometric redshift errors on our ability to constrain dark energy models with weak lensing. The ability to study dark energy with cosmic shear is also limited by the imprecision in our understanding of the physics of gravitational collapse. In chapter 4 I present the stringent calibration requirements on this source of uncertainty. I study the potential of weak lensing to resolve a debate over a long-standing anomaly in CMB measurements in chapter 5. Finally, in chapter 6 I summarize my findings and conclude with a brief discussion of my outlook on the future of weak lensing studies of cosmology

Operational modal analysis for testing and monitoring of bridges and special structures

Tese de doutoramento. Engenharia Civil. Faculdade de Engenharia. Universidade do Porto. 201

Nuclear structure and reaction studies at SPIRAL

The SPIRAL facility at GANIL, operational since 2001, is described briefly. The diverse physics program using the re-accelerated (1.2 to 25 MeV/u) beams ranging from He to Kr and the instrumentation specially developed for their exploitation are presented. Results of these studies, using both direct and compound processes, addressing various questions related to the existence of exotic states of nuclear matter, evolution of new "magic numbers", tunnelling of exotic nuclei, neutron correlations, exotic pathways in astrophysical sites and characterization of the continuum are discussed. The future prospects for the facility and the path towards SPIRAL2, a next generation ISOL facility, are also briefly presented.Comment: 48 pages, 27 figures. Accepted for publication in Journal of Physics

Self-Organizing Circuit Assembly through Spatiotemporally Coordinated Neuronal Migration within Geometric Constraints

Neurons are dynamically coupled with each other through neurite-mediated adhesion during development. Understanding the collective behavior of neurons in circuits is important for understanding neural development. While a number of genetic and activity-dependent factors regulating neuronal migration have been discovered on single cell level, systematic study of collective neuronal migration has been lacking. Various biological systems are shown to be self-organized, and it is not known if neural circuit assembly is self-organized. Besides, many of the molecular factors take effect through spatial patterns, and coupled biological systems exhibit emergent property in response to geometric constraints. How geometric constraints of the patterns regulate neuronal migration and circuit assembly of neurons within the patterns remains unexplored.We established a two-dimensional model for studying collective neuronal migration of a circuit, with hippocampal neurons from embryonic rats on Matrigel-coated self-assembled monolayers (SAMs). When the neural circuit is subject to geometric constraints of a critical scale, we found that the collective behavior of neuronal migration is spatiotemporally coordinated. Neuronal somata that are evenly distributed upon adhesion tend to aggregate at the geometric center of the circuit, forming mono-clusters. Clustering formation is geometry-dependent, within a critical scale from 200 µm to approximately 500 µm. Finally, somata clustering is neuron-type specific, and glutamatergic and GABAergic neurons tend to aggregate homo-philically.We demonstrate self-organization of neural circuits in response to geometric constraints through spatiotemporally coordinated neuronal migration, possibly via mechanical coupling. We found that such collective neuronal migration leads to somata clustering, and mono-cluster appears when the geometric constraints fall within a critical scale. The discovery of geometry-dependent collective neuronal migration and the formation of somata clustering in vitro shed light on neural development in vivo

Intentional Controlled Islanding in Wide Area Power Systems with Large Scale Renewable Power Generation to Prevent Blackout

Intentional controlled islanding is a solution to prevent blackouts following a large disturbance. This study focuses on determining island boundaries while maintaining the stability of formed islands and minimising load shedding. A new generator coherency identification framework based on the dynamic coupling of generators and Support Vector Clustering method is proposed to address this challenge. A Mixed Integer Linear Programming model is formulated to minimize power flow disruption and load shedding, and ensure the stability of islanding. The proposed algorithm was validated in 39-bus and 118-bus test systems

Bioinformatics

This book is divided into different research areas relevant in Bioinformatics such as biological networks, next generation sequencing, high performance computing, molecular modeling, structural bioinformatics, molecular modeling and intelligent data analysis. Each book section introduces the basic concepts and then explains its application to problems of great relevance, so both novice and expert readers can benefit from the information and research works presented here

Quantitative Analysis of Shallow Earthquake Sequences and Regional Earthquake Behavior: Implications for Earthquake Forecasting

This study is a quantitative investigation and characterization of earthquake sequences in the Central Volcanic Region (CVR) of New Zealand, and several regions in New Zealand and Southern California. We introduce CURATE, a new declustering algorithm that uses rate as the primary indicator of an earthquake sequence, and we show it has appreciable utility for analyzing seismicity. The algorithm is applied to the CVR and other regions around New Zealand. These regions are also compared with the Southern California earthquake catalogue. There is a variety of behavior within these regions, with areas that experience larger mainshock-aftershock (MS-AS) sequences having distinctly different general sequence parameters than those of more swarm dominated regions. The analysis of the declustered catalog shows that Lake Taupo and at least three other North Island regions have correlated variations in rate over periods of ~5 years. These increases in rate are not due to individual large sequences, but are instead caused by a general increase in earthquake and sequence occurrence. The most obvious increase in rate across the four North Island subsets follows the 1995-1996 magmatic eruption at Ruapehu volcano. The fact that these increases are geographically widespread and occur over years at a time suggests that the variations may reflect changes in the subduction system or a broad tectonic process. We examine basic sequence parameters of swarms and MS-AS sequences to provide better information for earthquake forecasting models. Like MS-AS sequences, swarm sequences contain a large amount of decay (decreasing rate) throughout their duration. We have tested this decay and found that 89% of MS-AS sequences and 55% of swarm sequences are better fit with an Omori's law decay than a linear rate. This result will be important to future efforts to forecast lower magnitude ranges or swarm prone areas like the CVR. To look at what types of process may drive individual sequences and may be associated with the rate changes, we examined a series of swarms that occurred to the South of Lake Taupo in 2009. We relocated these earthquakes using double-difference method, hypoDD, to obtain more accurate relative locations and depths. These swarms occur in an area about 20x20 km. They do not show systematic migration between sequences. The last swarm in the series is located in the most resistive area of the Tokaanu geothermal region and had two M =4.4 earthquakes within just four hours of each other. The earthquakes in this swarm have an accelerating rate of occurrence leading up to the first M = 4.4 earthquakes, which migrate upward in depth. The locations of earthquakes following the M = 4.4 event expand away from it at a rate consistent with fluid diffusion. Our statistical investigation of triggering due to large global (M ≥ 7) and regional earthquakes (M ≥ 6) concludes that more detailed (waveform level) investigation of individual sequences will be necessary to conclusively identify triggering, but sequence catalogs may be useful in identifying potential targets for those investigations. We also analyzed the probability that a series of swarms in the central Southern Alps were triggered by the 2009 Dusky Sound Mw = 7.8 and the 2010 Darfield Mw = 7.1 earthquake. There is less than a one-percent chance that the observed sequences occurred randomly in time. The triggered swarms do not show a significant difference to the swarms occurring in that region at other times in the 1.5-year catalog. Waveform cross-correlation was performed on this central Southern Alps earthquake catalog by a fellow PhD student Carolin Boese, and reveals that individual swarms are often composed of a single waveform family or multiple waveform families in addition to earthquakes that did not show waveform similarities. The existence of earthquakes that do not share waveform similarity in the same swarm (2.5 km radius) as a waveform family indicates that similar waveform groups may be unique in their location, but do not necessarily necessitate a unique trigger or driver. In addition to these triggered swarms in the Southern Alps we have also identified two swarms that are potentially triggered by slow-slip earthquakes along the Hikurangi margin in 2009 and 2010. The sequence catalogs generated by the CURATE method may be an ideal tool for searching for earthquake sequences triggered by slow-slip

An Efficient Rapid Method for Generators Coherency Identification in Large Power Systems

With steadily increasing interest in enhancing large power systems’ transient stability, generator coherency identification has become critical for the dynamic equivalents, controlled-islanding, and wide-area control of these systems. This paper presents an approach based on two classical and powerful techniques. The proposed method comprises the slow coherency method followed by the time-domain-based simulation of transient stability to identify the coherent groups of generators. In this regard, various operating conditions of the system are considered to obtain the updated coherency information between groups of generators by analyzing the chosen generator rotor angle. The proposed approach’s merits are tested on the New England IEEE 39-Bus and modified IEEE 118-Bus test systems in the PowerFactory software tools through Python. Corresponding simulation results validate the proposed paradigm’s effectiveness by enhancing the transient stability speed of a large power system without decreasing its coherency behavior accuracy. It is also observed that the proposed scheme tends to be more consistent in determining the coherent groups of generators in the presence of disturbances and different operational conditions.© 2022 the Authors. Published by IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/fi=vertaisarvioitu|en=peerReviewed