Accurate cosmology with galaxy and quasar surveys

Observations of the cosmic microwave background have led to a golden age of cosmology, where precise measurements can be confronted with predictions from cosmological models. Ongoing and future surveys of the distribution of galaxies will continue this revolution: they will enable us to test the laws of gravity, uncover the properties of dark energy and dark matter, and reinforce the connection to high-energy physics. However, current galaxy survey analyses are already limited by our ability to identify and treat observational systematics, and this problem will be even more pronounced in future experiments. Therefore, it is essential to develop novel methods to deal with these complications when testing cosmological models and searching for new physics. This is the focus of this thesis. Firstly, I will present measurements of primordial non-Gaussianity obtained from the clustering of quasars from the Sloan Digital Sky Survey. Primordial non-Gaussianity is a powerful probe of inflation, the leading theory of the initial conditions of the universe, but its effects on the distribution of quasars are mimicked by observational systematics. I will describe a framework to deal with these systematics and robustly measure primordial non-Gaussianity from the clustering of quasars. Secondly, I will present a new set of wavelet transforms on the sphere and the ball. These approaches are highly promising for analysing cosmological and geophysical data and dealing with their systematics in novel ways. Finally, I will examine the recent claims that extra massive neutrinos can resolve the tensions between cosmic microwave background, galaxy survey and supernova observations. I will demon- strate that this conclusion is premature since it is driven by the least robust data sets. Given the growing number of cosmological observables and their varied levels of robustness, combining data sets and dealing with such tensions will become critical in the near future

A clear view of the primordial Universe

Observations of temperature anisotropies in the cosmic microwave background (CMB) and measurements of the large-scale structure of matter have established the standard Lambda cold dark matter model of cosmology. Precise measurements of new observables will test extensions to the standard cosmological model, e.g., a non-zero tensor-to-scalar ratio of primordial perturbations, a running of the spectral index of the primordial power spectrum (both tests of cosmic inflation), or new components like massive neutrinos and warm dark matter (WDM). Two of the most promising observables to test these extensions in upcoming surveys are polarisation anisotropies in the CMB and correlations in the Lyman-alpha forest. Accurate cosmological parameter estimation, however, is only achievable through careful consideration of instrumental and astrophysical systematic effects, either by removing contamination in data or modelling its effect during statistical inference. I present new approaches to controlling contaminants to CMB temperature and polarisation and the Lyman-alpha forest. The primary contamination to the CMB is foreground Galactic radiation, e.g., synchrotron and thermal dust emission. I demonstrate the use of directional wavelets in more accurately reconstructing CMB temperature maps in the presence of these foregrounds, using Planck simulations and data. The complexity of polarised Galactic emissions limits constraints on inflation and neutrinos using CMB polarisation. I show how spin directional wavelets can allow additional morphological information to improve cosmic and foreground component separation. The Lyman-alpha forest probes the primordial power spectrum and the suppression of small-scale clustering by neutrinos or WDM. However, estimation of the shape of the power spectrum is biased by broadened absorption lines formed by high density systems of neutral hydrogen. I present models of their effect, built from Illustris cosmological hydrodynamical simulations. Being functions of absorber column density provides the flexibility to model residual contamination, after the largest absorbers have been removed from data

Complexity in Economic and Social Systems

There is no term that better describes the essential features of human society than complexity. On various levels, from the decision-making processes of individuals, through to the interactions between individuals leading to the spontaneous formation of groups and social hierarchies, up to the collective, herding processes that reshape whole societies, all these features share the property of irreducibility, i.e., they require a holistic, multi-level approach formed by researchers from different disciplines. This Special Issue aims to collect research studies that, by exploiting the latest advances in physics, economics, complex networks, and data science, make a step towards understanding these economic and social systems. The majority of submissions are devoted to financial market analysis and modeling, including the stock and cryptocurrency markets in the COVID-19 pandemic, systemic risk quantification and control, wealth condensation, the innovation-related performance of companies, and more. Looking more at societies, there are papers that deal with regional development, land speculation, and the-fake news-fighting strategies, the issues which are of central interest in contemporary society. On top of this, one of the contributions proposes a new, improved complexity measure

Coordinated Transit Response Planning and Operations Support Tools for Mitigating Impacts of All-Hazard Emergency Events

This report summarizes current computer simulation capabilities and the availability of near-real-time data sources allowing for a novel approach of analyzing and determining optimized responses during disruptions of complex multi-agency transit system. The authors integrated a number of technologies and data sources to detect disruptive transit system performance issues, analyze the impact on overall system-wide performance, and statistically apply the likely traveler choices and responses. The analysis of unaffected transit resources and the provision of temporary resources are then analyzed and optimized to minimize overall impact of the initiating event

Struktura ambiwalencji postaw wobec kobiet - Legitymizacja dyskryminacji płciowej i możliwości zmiany

One way in which sexism is distinct from other types of prejudice is its ambivalent nature. Women are both reviled and revered, depending on whether they fulfill or violate expectations concerning their gender roles. Basing on Ambivalent Sexism Theory (AST; Glick & Fiske, 1995, 1996, 2001), the following thesis explores dimensions that are not subsumed under AST that I consider critical to the perception of women. Specifically, based on data coming from qualitative and quantitative studies conducted in Poland and in the United States, I distinguish two additional springboards for sexism: 1. the belief that the fundamental role of a woman is that of the mother (together with the assumption that women’s goals should be subsumed under others’ goals and needs), and 2. the responsibility for aesthetics that is placed upon women. Subsequently, discriminant and predictive validity of the new dimensions is tested showing that these basic tenets form a richer structure of prejudice not encompassed by the existing sub-dimensions of AST. Theoretical implications of the findings and the universality of new dimensions are discussed