Statistical tools in cosmology: model selection and covariance matrix comparison

dc.contributor.advisor1Marra, Valerio
dc.contributor.advisor1IDhttps://orcid.org/0000000277731579
dc.contributor.advisor1Latteshttp://lattes.cnpq.br/6846011112691877
dc.contributor.authorFerreira, Tassia Andrade
dc.contributor.authorIDhttps://orcid.org/0000000340163763
dc.contributor.referee1Sobreira, Flavia
dc.contributor.referee2Vitenti, Mariana Penna Lima
dc.contributor.referee3Makler, Martin
dc.contributor.referee3IDhttps://orcid.org/0000000322062651
dc.contributor.referee3Latteshttp://lattes.cnpq.br/6567844719949395
dc.contributor.referee4Dodelson, Scott
dc.date.accessioned2024-05-30T00:49:45Z
dc.date.available2024-05-30T00:49:45Z
dc.date.issued2021-10-04
dc.description.abstractAlbeit ΛCDM’s fame as the concordance model, there are many interesting myster ies worth exploring, such as the nature of dark energy. Here, we test the viability of several classes of scenarios of the dark sector with linear and non-linear inter acting terms. To do so, we use a Bayesian model selection with data from type Ia supernovae, cosmic chronometers, cosmic microwave background and two sets of baryon acoustic oscillations measurements: 2-dimensional angular measurements (BAO2), and 3-dimensional angle-averaged measurements (BAO3). On the other hand, we consider covariance matrices, which are important tools for parameter estimation. We explore ways of compressing them by analysing their eigenvalues and signal-to-noise ratio, by employing a tomographic compression and, lastly, with the Massively Optimized Parameter Estimation and Data compression (MOPED). We find that MOPED is a powerful tool in the comparison of covariance matrices and, towards that end, we build a python code that uses a fast Monte Carlo simulation to obtain comprehensible values for differences between two covariance matrices. This method thus eliminates the need for a full cosmological analysis as we relate its output to the corresponding parameter constraints.
dc.description.sponsorshipFundação Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Espírito Santo (FAPES)
dc.formatText
dc.identifier.urihttp://repositorio.ufes.br/handle/10/14957
dc.languagepor
dc.publisherUniversidade Federal do Espírito Santo
dc.publisher.countryBR
dc.publisher.courseDoutorado em Astrofísica, Cosmologia e Gravitação
dc.publisher.departmentCentro de Ciências Exatas
dc.publisher.initialsUFES
dc.publisher.programPrograma de Pós-Graduação em Astrofísica, Cosmologia e Gravitação
dc.rightsopen access
dc.subjectcosmologia
dc.subject.br-rjbnsubject.br-rjbn
dc.subject.cnpqAstronomia
dc.titleStatistical tools in cosmology: model selection and covariance matrix comparison
dc.typedoctoralThesis
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