A pedagogical approach to cosmology that integrates theory with computational and data-analysis techniques, to prepare readers for further research.
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Dragan Huterer is a professor of physics at the University of Michigan, where he studies cosmology at the interface of theory and data. He is a leading expert in developing data-driven techniques to understand the nature and origin of 'dark energy,' a component that dominates the dynamics of the universe and causes its accelerated expansion. A fellow of the American Physical Society, he is also a recipient of the University of Michigan's Henry Russel Award and the Humboldt Foundation's Friedrich Wilhelm Bessel Award.
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Hardcover. Condition: new. Hardcover. This new graduate textbook adopts a pedagogical approach to contemporary cosmology that enables readers to build an intuitive understanding of theory and data, and of how they interact, which is where the greatest advances in the field are currently being made. Using analogies, intuitive explanations of complex topics, worked examples and computational problems, the book begins with the physics of the early universe, and goes on to cover key concepts such as inflation, dark matter and dark energy, largescale structure, and cosmic microwave background. Computational and data analysis techniques, and statistics, are integrated throughout the text, particularly in the chapters on late-universe cosmology, while another chapter is entirely devoted to the basics of statistical methods. A solutions manual for end-of-chapter problems is available to instructors, and suggested syllabi, based on different course lengths and emphasis, can be found in the Preface. Online computer code and datasets enhance the student learning experience. A unique graduate cosmology textbook that integrates theory with modern, data-driven, computational techniques. This approach, combined with student-friendly pedagogy, helps the reader build intuitive connections between data and theory. Worked examples, computational problems, data sets, and computer code enhance the learning experience. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781316513590
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