Statistical Challenges In 21st Century Cosmology Iau S306

The advent of advanced astronomical instruments and huge surveys means that the twenty-first century is witnessing a rapid growth in astrostatistical science. Interpreting the cosmic microwave background, weak and strong gravitational lensing, galaxy clustering and other signatures of the early Universe all require advanced statistical techniques. Led by members of the IAU's newly formed Working Group in Astrostatistics and Astroinformatics, IAU Symposium 306 emphasises the intricate mathematical methods needed to extract scientific insights from large and complicated datasets. It contains contributions on Bayesian methods, weak lensing cosmology, CMB data analysis, cross-correlating datasets, large-scale structure, data mining and machine learning, ongoing surveys and the future Euclid mission. The approaches presented here provide a solid foundation to advance new research methods in cosmology, making it an essential text for the large community of astronomers and statisticians who will analyse and interpret the vast and growing amount of observational data.

Modern astronomy has been characterized by an enormous growth in data acquisition - from new technologies in telescopes, detectors, and computation. One can now compile catalogs of tens or hundreds of millions of stars or galaxies and databases from satellite-based observations are reaching terabit proportions. This wealth of data gives rise to statistical challenges not previously encountered in astronomy. This book is the result of a workshop held at Pennsylvania State University in August 1991 that brought together leading astronomers and statisticians to consider statistical challenges encountered in modern astronomical research. The chapters have all been thoroughly revised in the light of the discussions at the conference, and some of the lively discussion is recorded here as well.

Digital sky surveys, high-precision astrometry from satellite data, deep-space data from orbiting telescopes, and the like have all increased the quantity and quality of astronomical data by orders of magnitude per year for several years. Making sense of this wealth of data requires sophisticated statistical techniques. Fortunately, statistical methodologies have similarly made great strides in recent years. Powerful synergies thus emerge when astronomers and statisticians join in examining astrostatistical problems and approaches. The book begins with an historical overview and tutorial articles on basic cosmology for statisticians and the principles of Bayesian analysis for astronomers. As in earlier volumes in this series, research contributions discussing topics in one field are joined with commentary from scholars in the other. Thus, for example, an overview of Bayesian methods for Poissonian data is joined by discussions of planning astronomical observations with optimal efficiency and nested models to deal with instrumental effects. The principal theme for the volume is the statistical methods needed to model fundamental characteristics of the early universe on its largest scales.

This volume contains a selection of chapters based on papers to be presented at the Fifth Statistical Challenges in Modern Astronomy Symposium. The symposium will be held June 13-15th at Penn State University. Modern astronomical research faces a vast range of statistical issues which have spawned a revival in methodological activity among astronomers. The Statistical Challenges in Modern Astronomy V conference will bring astronomers and statisticians together to discuss methodological issues of common interest. Time series analysis, image analysis, Bayesian methods, Poisson processes, nonlinear regression, maximum likelihood, multivariate classification, and wavelet and multiscale analyses are all important themes to be covered in detail. Many problems will be introduced at the conference in the context of large-scale astronomical projects including LIGO, AXAF, XTE, Hipparcos, and digitized sky surveys.

Modern astronomical research faces a vast range of statistical issues which have spawned a revival in methodological activity among astronomers. The Statistical Challenges in Modern Astronomy II conference brought astronomers and statisticians together to discuss methodological issues of common interest. Time series analysis, image analysis, Bayesian methods, Poisson processes, nonlinear regression, maximum likelihood, multivariate classification, and wavelet and multiscale analyses were all important themes. Many problems were introduced at the conference in the context of large-scale astronomical projects including LIGO, AXAF, XTE, Hipparcos, and digitised sky surveys. As such, this volume will be of interest to researchers and advanced students in both fields - astronomers seeking exposure to recent developments in statistics, and statisticians interested in confronting new problems.

Digital sky surveys, high-precision astrometry from satellite data, deep-space data from orbiting telescopes, and the like have all increased the quantity and quality of astronomical data by orders of magnitude per year for several years. Making sense of this wealth of data requires sophisticated statistical techniques. Fortunately, statistical methodologies have similarly made great strides in recent years. Powerful synergies thus emerge when astronomers and statisticians join in examining astrostatistical problems and approaches. The book begins with an historical overview and tutorial articles on basic cosmology for statisticians and the principles of Bayesian analysis for astronomers. As in earlier volumes in this series, research contributions discussing topics in one field are joined with commentary from scholars in the other. Thus, for example, an overview of Bayesian methods for Poissonian data is joined by discussions of planning astronomical observations with optimal efficiency and nested models to deal with instrumental effects. The principal theme for the volume is the statistical methods needed to model fundamental characteristics of the early universe on its largest scales.

These proceedings comprise current statistical issues in analyzing data in particle physics, astrophysics and cosmology, as discussed at the PHYSTAT05 conference in Oxford. This is a continuation of the popular PHYSTAT series; previous meetings were held at CERN (2000), Fermilab (2000), Durham (2002) and Stanford (2003).In-depth discussions on topical issues are presented by leading statisticians and research workers in their relevant fields. Included are invited reviews and contributed research papers presenting the latest, state-of-the-art techniques./a