Bayesian Forward Modeling for LIM Surveys and Their Cross-Correlation
Kavli Institute for Theoretical Physics via YouTube
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Explore Bayesian forward modeling techniques for Line Intensity Mapping (LIM) surveys and their cross-correlation applications in this 14-minute conference talk. Learn how to apply Bayesian statistical methods to model and analyze intensity mapping data, focusing on the forward modeling approach that connects theoretical predictions to observational data. Discover the mathematical framework for cross-correlating LIM surveys with other cosmological probes to extract enhanced scientific information. Examine the advantages of Bayesian inference in handling uncertainties and parameter estimation in intensity mapping contexts. Understand how these techniques contribute to multi-probe cosmology studies by enabling robust statistical analysis of large-scale structure observations across different wavelengths and survey methodologies.
Syllabus
Bayesian Forward Modeling for LIM surveys and their Cross-Correlation | Nicholas Kern (Michigan)
Taught by
Kavli Institute for Theoretical Physics