1 code implementation • 11 Jul 2022 • T. Lucas Makinen, Tom Charnock, Pablo Lemos, Natalia Porqueres, Alan Heavens, Benjamin D. Wandelt
We a) demonstrate the high sensitivity of modular graph structure to the underlying cosmology in the noise-free limit, b) show that graph neural network summaries automatically combine mass and clustering information through comparisons to traditional statistics, c) demonstrate that networks can still extract information when catalogues are subject to noisy survey cuts, and d) illustrate how nonlinear IMNN summaries can be used as asymptotically optimal compressed statistics for Bayesian simulation-based inference.
no code implementations • 13 Nov 2020 • Natalia Porqueres, Alan Heavens, Daniel Mortlock, Guilhem Lavaux
In this case, the density field samples are generated with a power spectrum that deviates from the prior, and the method recovers the true lensing power spectrum.
Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics