Teaching AI to explain cosmology
Lead Research Organisation:
University College London
Department Name: Physics and Astronomy
Abstract
UCL has been heavily involved in large galaxy surveys: DES & KiDS (both with their observations complete, many results already published, and new analyses underway), DESI (had its first light in October 2019; survey to start in 2020), Euclid & LSST (both to start surveys in 2022). While there is a well-defined Bayesian model-dependent methodology to derive cosmological parameters from the data, the cosmology community is only at the beginning of getting AI algorithms to (i) explain and interpret what the algorithms are actually doing; (ii) incorporating known base-line Physics in the algorithms; and (iii) discovering new Physics (or new systematics) from the data.
People |
ORCID iD |
Benjamin Joachimi (Primary Supervisor) | |
Prabh Bhambra (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ST/P006736/1 | 30/09/2017 | 29/09/2024 | |||
2425038 | Studentship | ST/P006736/1 | 30/09/2020 | 29/09/2024 | Prabh Bhambra |