Neural ratio estimation: the future of supernova cosmology?

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• Matthew Grayling (University of Cambridge)
• Wednesday 24 April 2024, 10:00-11:00
• Martin Ryle Seminar Room, KICC.

If you have a question about this talk, please contact David Yallup.

Simulation-based inference (SBI) has the potential to revolutionise how we do supernova cosmology and let us incorporate arbitrarily complex effects within a Bayesian model. I will present recent work which sought to validate neural ratio estimation (NRE) by comparing NRE -derived posteriors on supernova properties to those obtained with a likelihood-based MCMC approach for the same data, and then discuss how NRE and SBI in general provide a pathway towards a model extending all the way from type Ia supernova light curves to cosmological parameters as part of a single analysis.

This talk is part of the Astro Data Science Discussion Group series.

This talk is included in these lists:

• Astro Data Science Discussion Group
• Cambridge Astronomy Talks
• Combined External Astrophysics Talks DAMTP
• Cosmology, Astrophysics and General Relativity
• Institute of Astronomy Extra Talks
• Institute of Astronomy Talk Lists
• Martin Ryle Seminar Room, KICC

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