We develop a set of machine-learning-based cosmological emulators, to obtain fast model predictions for the angular power spectrum coefficients, characterising tomographic observations of galaxy clustering and weak gravitational lensing from multiband photometric surveys (and their cross-correlation).
Fast emulation of two-point angular statistics for photometric galaxy surveys
Biggio, Luca;
2024
Abstract
We develop a set of machine-learning-based cosmological emulators, to obtain fast model predictions for the angular power spectrum coefficients, characterising tomographic observations of galaxy clustering and weak gravitational lensing from multiband photometric surveys (and their cross-correlation).
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