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Accelerated Bayesian inference in cosmology

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If you have a question about this talk, please contact Kazuki Sakurai.

The Cavendish Astrophysics Group develops and employs Bayesian inference methods to analyse cosmological observations, in particular of the cosmic microwave background. Recent work has focussed on developing new methods for greatly accelerating such analyses, in particular by using neural networks and nested sampling methods. I intend to give a brief outline of these approaches, which are generic in nature and may therefore be applied beyond cosmology. Indeed, they have already been applied to some problems in particle physics phenomenology.

This talk is part of the HEP phenomenology joint Cavendish-DAMTP seminar series.

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