Patterns of Scalable Bayesian Inference

Datasets are growing not just in size but in complexity, creating a demand for rich models and quantification of uncertainty. Bayesian methods are an excellent fit for this demand, but scaling Bayesian inference is a challenge. In response to this challenge, there has been considerable recent work based on varying assumptions about model structure, underlying computational resources, and the importance of asymptotic correctness. As a result, there is a zoo of ideas with few clear overarching principles. In this paper, we seek to identify unifying principles, patterns, and intuitions for scaling Bayesian inference. We review existing work on utilizing modern computing resources with both MCMC and variational approximation techniques. From this taxonomy of ideas, we characterize the general principles that have proven successful for designing scalable inference procedures and comment on the path forward

Polymer physics models of the chromatin spatial organization in the cell nucleus

This PhD thesis concerns the application of polymer physics to investigate the mechanisms underlying the 3D organization of chromosomes in mammalian genomes. Chromosome architecture has in fact a crucial role in vital biological functions and its abnormal folding is often linked to severe human diseases. Yet, a unified quantitative framework describing the spatial chromatin organization is still lacking. The polymer models developed in this work allow to obtain highly accurate 3D reconstructions of specific genomic regions and have been employed in particular to predict the effects on chromosome structure of genetic rearrangements, such as deletions, insertions and duplications, often linked to diseases

Pixel detector performance and study of CP invariance in H to tau tau decays with the ATLAS detector

Following its discovery by the ATLAS and CMS experiments in 2012, the Higgs boson has been studied in a multitude of decay modes. So far, its measured properties match very well with the predictions of the Standard Model of particle physics, which postulates the existence of a scalar field, to which all massive particles must couple. The scalar hypothesis can be tested by studying these couplings in detail. Several models predict an extension of the Higgs sector, which would involve a minimum of four additional Higgs bosons. These can potentially mix with each other, altering the kinematics of how the 125 GeV boson decays. This thesis presents a study of the potential for probing for new physics in Higgs decays into pairs of tau leptons. The correlation between the spin directions of the taus is reconstructed from the kinematics of the tau decay products, resulting in an observable angle, which is sensitive to the charge-parity (CP) state of the Higgs. Successful reconstruction of tau leptons rely on the information from the ATLAS tracking detectors. The innermost part of the detector, consisting of high-granularity pixel sensors, was before the beginning of 2015 operation upgraded with an additional pixel layer, the IBL, positioned extremely close to the collision point. Part of this thesis is devoted to the readout software which converts pixel detector output into data objects used by the event reconstruction algorithms. This software provides the mapping from the subdetector-specific module identification numbers, to the global ATLAS coordinate system. The intense conditions close to the collision point, under the record-breaking luminosity delivered by the LHC during the past three years of running, causes constant damage to the pixel sensors. To both ensure optimal operation of the detector, and to provide numbers to which simulations can be compared, a study has been carried out to measure the bias voltage required to fully deplete the sensors. Dedicated voltage scans have been performed at several occasions, to find the evolution of the depletion voltage over time

Introduction to fast Super-Paramagnetic Clustering

We map stock market interactions to spin models to recover their hierarchical structure using a simulated annealing based Super-Paramagnetic Clustering (SPC) algorithm. This is directly compared to a modified implementation of a maximum likelihood approach to fast-Super-Paramagnetic Clustering (f-SPC). The methods are first applied standard toy test-case problems, and then to a dataset of 447 stocks traded on the New York Stock Exchange (NYSE) over 1249 days. The signal to noise ratio of stock market correlation matrices is briefly considered. Our result recover approximately clusters representative of standard economic sectors and mixed clusters whose dynamics shine light on the adaptive nature of financial markets and raise concerns relating to the effectiveness of industry based static financial market classification in the world of real-time data-analytics. A key result is that we show that the standard maximum likelihood methods are confirmed to converge to solutions within a Super-Paramagnetic (SP) phase. We use insights arising from this to discuss the implications of using a Maximum Entropy Principle (MEP) as opposed to the Maximum Likelihood Principle (MLP) as an optimization device for this class of problems

Design and characterization of functional nanomaterials on surfaces

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Física de la Materia Condensada. Fecha de lectura: 21-10-2020The urgent need for developing new strategies to afford the increasing energy demand remains a challenge for many research fields, such as material science or energy engineering. In this respect, the field of nanoscience has emerged as a powerful field towards the design of functional nanomaterials, synthesized from both organic and inorganic materials. This new scientific discipline has led to the design of novel materials and opened up new avenues for traditional compounds. For instance, transition metal oxides have been proposed as promising catalysts in the oxygen evolution reaction for water splitting, of crucial relevance in clean energy. Additionally, the development of organic electronics, focused on the study of the electronic properties of carbon-based materials, plays an important role in the synthesis and transformation of traditional electronics by designing low-cost, flexible and sustainable electronic devices. In this thesis, we have grown and studied different nanomaterials on metallic surfaces related to energy efficiency, targeting to achieve global sustainability. First, we have studied the catalytic activity of CoO at the atomic scale towards the water splitting reaction. We have grown single bilayer CoO nanoislands, where the co-existence of two distinct phases has been observed. Such polymorphism has been rationalized due to the distinct lattice parameter and the registry with the substrate which induces the modification of its electronic properties, reactivity and, hence, of its catalytic activity. In addition, we have shown the capability to tune the phase by an electric field. Second, we have described the on-surface synthesis of new π-conjugated polymers with important applications in organic electronics. An innovative strategy towards the synthesis of low band gap π-conjugated polymers formed by acene or periacene units has been developed, which allows the control of their electronic structure, resonance form and topological quantum class by tuning the repeating unit size. Our results shed light into the atomistic adsorption and dissociation of water on a CoO model catalyst. Furthermore, we introduced pathways for controlling the electronic properties and quantum topological class of one dimensional polymers on metallic surface

The Amarna South Tombs Cemetery: Biocultural Dynamics of a Disembedded Capital City in New Kingdom Egypt

abstract: The Egyptian New Kingdom city of Akhetaten (modern: Tell el-Amarna, el-Amarna, or simply Amarna) provides a unique opportunity to study ancient biocultural dynamics. It was a disembedded capital removed from the major power bases of Memphis and Thebes that was built, occupied, and abandoned within approximately 20 years (c. 1352–1336 BCE). This dissertation used the recently excavated Amarna South Tombs cemetery to test competing models for the development of disembedded capitals, such as the geographic origin of its migrants and its demographic structure in comparison to contrastive models for the establishment of settlements. The degree to which biological relatedness organized the South Tombs cemetery was also explored. The results suggest that the Nile Valley into the New Kingdom (1539–1186 BCE) was very diverse in dental cervical phenotype and thus highly mobile in respects to gene flow, failing to reject that the Amarna city was populated by individuals and families throughout the Nile Valley. In comparison, the Amarna South Tombs cemetery contained the least amount of dental phenotypic diversity, supporting a founder effect due to migration from larger, more diverse gene pools to the city or the very fact that the city and sample only reflect a 20-year interval with little time to accumulate phenotypic variation. Parts of the South Tombs cemetery also appear to be organized by biological affinity, showing consistent and significant spatial autocorrelation with biological distances generated from dental cervical measurements in male, female, and subadult (10–19 years of age) burials closest to the South Tombs. This arrangement mimics the same orderliness in the residential areas of the Amarna city itself with officials surrounded by families that supported their administration. Throughout the cemetery, adult female grave shaft distances predict their biological distances, signaling a nuclear family dynamic that included many females including mothers, widows, and unwed aunts, nieces, and daughters. A sophisticated paleodemographic model using simulated annealing optimization projected the living population of the South Tombs cemetery, which overall conformed to a transplanted community similar to 19th century mill villages of the United States and United Kingdom.Dissertation/ThesisDoctoral Dissertation Anthropology 201

Methodological review of multicriteria optimization techniques: aplications in water resources

Multi-criteria decision analysis (MCDA) is an umbrella approach that has been applied to a wide range of natural resource management situations. This report has two purposes. First, it aims to provide an overview of advancedmulticriteriaapproaches, methods and tools. The review seeks to layout the nature of the models, their inherent strengths and limitations. Analysis of their applicability in supporting real-life decision-making processes is provided with relation to requirements imposed by organizationally decentralized and economically specific spatial and temporal frameworks. Models are categorized based on different classification schemes and are reviewed by describing their general characteristics, approaches, and fundamental properties. A necessity of careful structuring of decision problems is discussed regarding planning, staging and control aspects within broader agricultural context, and in water management in particular. A special emphasis is given to the importance of manipulating decision elements by means ofhierarchingand clustering. The review goes beyond traditionalMCDAtechniques; it describes new modelling approaches. The second purpose is to describe newMCDAparadigms aimed at addressing the inherent complexity of managing water ecosystems, particularly with respect to multiple criteria integrated with biophysical models,multistakeholders, and lack of information. Comments about, and critical analysis of, the limitations of traditional models are made to point out the need for, and propose a call to, a new way of thinking aboutMCDAas they are applied to water and natural resources management planning. These new perspectives do not undermine the value of traditional methods; rather they point to a shift in emphasis from methods for problem solving to methods for problem structuring. Literature review show successfully integrations of watershed management optimization models to efficiently screen a broad range of technical, economic, and policy management options within a watershed system framework and select the optimal combination of management strategies and associated water allocations for designing a sustainable watershed management plan at least cost. Papers show applications in watershed management model that integrates both natural and human elements of a watershed system including the management of ground and surface water sources, water treatment and distribution systems, human demands,wastewatertreatment and collection systems, water reuse facilities,nonpotablewater distribution infrastructure, aquifer storage and recharge facilities, storm water, and land use