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Book
Asteroseismic Data Analysis : Foundations and Techniques
Authors: ---
ISBN: 1400888204 Year: 2017 Publisher: Princeton, NJ : Princeton University Press,

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Abstract

Studies of stars and stellar populations, and the discovery and characterization of exoplanets, are being revolutionized by new satellite and telescope observations of unprecedented quality and scope. Some of the most significant advances have been in the field of asteroseismology, the study of stars by observation of their oscillations. Asteroseismic Data Analysis gives a comprehensive technical introduction to this discipline. This book not only helps students and researchers learn about asteroseismology; it also serves as an essential instruction manual for those entering the field.The book presents readers with the foundational techniques used in the analysis and interpretation of asteroseismic data on cool stars that show solar-like oscillations. The techniques have been refined, and in some cases developed, to analyze asteroseismic data collected by the NASA Kepler mission. Topics range from the analysis of time-series observations to extract seismic data for stars to the use of those data to determine global and internal properties of the stars. Reading lists and problem sets are provided, and data necessary for the problem sets are available online.The first book to describe in detail the different techniques used to analyze the data on stellar oscillations, Asteroseismic Data Analysis offers an invaluable window into the hearts of stars.Introduces the asteroseismic study of stars and the theory of stellar oscillationsDescribes the analysis of observational (time-domain) dataExamines how seismic parameters are extracted from observationsExplores how stellar properties are determined from seismic dataLooks at the "inverse problem," where frequencies are used to infer internal structures of stars

Keywords

Astroseismology. --- Astero-seismology --- Asteroseismology --- Extraterrestrial seismology --- Stellar oscillations --- Bayesian framework. --- LAWE. --- NASA Kepler mission. --- acoustic glitches. --- asteroseismic analysis. --- asteroseismic data. --- asteroseismic parameters. --- asteroseismology. --- automated detection. --- basic datasets. --- comparing frequencies. --- constructing models. --- direct method. --- energy generation. --- energy. --- exoplanets. --- frequency spectrum. --- frequency splittings. --- frequency-domain properties. --- frequency-power spectrum. --- glitch signatures. --- granulation. --- grid-based modeling. --- inversion techniques. --- inversions. --- linear adiabatic wave equation. --- magnetic activity. --- mass. --- mixed modes. --- mode frequencies. --- model parameters. --- modeling stars. --- momentum. --- observational data. --- observational techniques. --- oscillations. --- peak-bagging analysis. --- period spacings. --- power spectrum. --- pulsators. --- red giants. --- satellite. --- seismic properties. --- solar frequencies. --- solar-like oscillators. --- solar-like pulsations. --- solar-type oscillations. --- spherical symmetry. --- star mass. --- star radius. --- stars. --- stellar models. --- stellar oscillation data. --- stellar oscillations. --- stellar parameters. --- stellar population. --- stellar properties. --- stellar pulsations. --- stellar signals. --- stellar structure. --- stellar structures. --- telescope. --- time-domain data. --- time-series observations.


Book
Social learning : an introduction to mechanisms, methods, and models
Authors: ---
ISBN: 9780691150710 9780691150703 0691150710 0691150702 1299652131 1400846501 Year: 2013 Publisher: Princeton : Princeton University Press,

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Abstract

Many animals, including humans, acquire valuable skills and knowledge by copying others. Scientists refer to this as social learning. It is one of the most exciting and rapidly developing areas of behavioral research and sits at the interface of many academic disciplines, including biology, experimental psychology, economics, and cognitive neuroscience. Social Learning provides a comprehensive, practical guide to the research methods of this important emerging field. William Hoppitt and Kevin Laland define the mechanisms thought to underlie social learning and demonstrate how to distinguish them experimentally in the laboratory. They present techniques for detecting and quantifying social learning in nature, including statistical modeling of the spatial distribution of behavior traits. They also describe the latest theory and empirical findings on social learning strategies, and introduce readers to mathematical methods and models used in the study of cultural evolution. This book is an indispensable tool for researchers and an essential primer for students. Provides a comprehensive, practical guide to social learning research Combines theoretical and empirical approaches Describes techniques for the laboratory and the field Covers social learning mechanisms and strategies, statistical modeling techniques for field data, mathematical modeling of cultural evolution, and more

Keywords

Learning in animals --- Social learning --- Psychology, Comparative --- Research --- Methodology. --- Animal learning --- Animal intelligence --- Learning --- Socialization --- Behavior, Comparative --- Comparative behavior --- Comparative psychology --- Ethology, Comparative --- Intelligence of animals --- Zoology --- Animal behavior --- Animal psychology --- Human behavior --- Instinct --- Aristotle. --- acquisition. --- animal culture. --- animals. --- asocial learning. --- behavior. --- behavioral repertoires. --- behavioral research. --- behavioral trait. --- biological evolution. --- causal modeling. --- child development. --- children. --- controlled diffusion. --- cultural evolution. --- cultural transmission. --- decision making. --- developmental methods. --- diffusion curve analysis. --- diffusion data. --- diffusion experiments. --- diffusion of innovation. --- diffusion. --- ecological hypothesis. --- experimental manipulations. --- fear. --- frequency-dependent biases. --- gene-culture coevolution. --- genetic hypothesis. --- group contrasts approach. --- hierarchical control. --- imitation. --- inadvertent coaching. --- innovation. --- laboratory experiments. --- learning heuristics. --- mathematical methods. --- meta-strategies. --- model-fitting approach. --- modeling. --- network-based diffusion analysis. --- neural circuitry. --- neuroendocrinological studies. --- neutral models. --- observational conditioning. --- observational data. --- observational learning. --- opportunity providing. --- option choice. --- random copying. --- reaction-diffusion models. --- research methods. --- response facilitation. --- social experience. --- social facilitation. --- social foraging theory. --- social learning mechanisms. --- social learning research. --- social learning strategies. --- social learning. --- social network. --- social transmission. --- statistical methods. --- statistical modeling. --- stimulus enhancement. --- success biases. --- translocation experiments. --- transmission chains.

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