Search for dissertations about: "physics learning"
Showing result 16 - 20 of 126 swedish dissertations containing the words physics learning.
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16. Theoretical prediction of properties of atomistic systems : Density functional theory and machine learning
Abstract : The prediction of ground state properties of atomistic systems is of vital importance in technological advances as well as in the physical sciences. Fundamentally, these predictions are based on a quantum-mechanical description of many-electron systems. READ MORE
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17. Towards Realistic Hyperon Reconstruction in PANDA : From Tracking with Machine Learning to Interactions with Residual Gas
Abstract : The PANDA (anti-Proton ANnihilation at DArmstadt) experiment at FAIR (Facility for Anti-proton and Ion Research) aims to study strong interactions in the confinement domain. In PANDA, a continuous beam of anti-protons will impinge on a fixed hydrogen target inside the High Energy Storage Ring (HESR), a feature intended to attain high interaction rates for various physics studies e. READ MORE
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18. Using a Social Semiotic Perspective to Inform the Teaching and Learning of Physics
Abstract : This thesis examines meaning-making in three different areas of undergraduate physics: the refraction of light; electric circuits; and, electric potential and electric potential energy. In order to do this, a social semiotic perspective was constituted for the thesis to facilitate the analysis of meaning-making in terms of the semiotic resources that are typically used in the teaching and learning of physics. READ MORE
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19. Homology and machine learning for materials informatics
Abstract : Materials informatics is the field of study where materials science is combined with modern data science. This data-driven approach is powered by the growing availability of computational power and storage capability. READ MORE
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20. A Serendipitous Journey through Stochastic Processes
Abstract : In this PhD thesis we will present some new insights in different problems in the field of stochastic processes. A stochastic resonance system is studied using path integral techniques, originally developed in quantum field theory, to recover the optimal means through which noise self-organises before a rare transition from one potential well to the other. READ MORE