Kavli Affiliate: Eiichiro Komatsu
| First 5 Authors: Davide Piras, Laura Herold, Luisa Lucie-Smith, Eiichiro Komatsu,
| Summary:
Finding the best parametrization for cosmological models in the absence of
first-principle theories is an open question. We propose a data-driven
parametrization of cosmological models given by the disentangled ‘latent’
representation of a variational autoencoder (VAE) trained to compress cosmic
microwave background (CMB) temperature power spectra. We consider a broad range
of $Lambda$CDM and beyond-$Lambda$CDM cosmologies with an additional early
dark energy (EDE) component. We show that these spectra can be compressed into
5 ($Lambda$CDM) or 8 (EDE) independent latent parameters, as expected when
using temperature power spectra alone, and which reconstruct spectra at an
accuracy well within the Planck errors. These latent parameters have a physical
interpretation in terms of well-known features of the CMB temperature spectrum:
these include the position, height and even-odd modulation of the acoustic
peaks, as well as the gravitational lensing effect. The VAE also discovers one
latent parameter which entirely isolates the EDE effects from those related to
$Lambda$CDM parameters, thus revealing a previously unknown degree of freedom
in the CMB temperature power spectrum. We further showcase how to place
constraints on the latent parameters using Planck data as typically done for
cosmological parameters, obtaining latent values consistent with previous
$Lambda$CDM and EDE cosmological constraints. Our work demonstrates the
potential of a data-driven reformulation of current beyond-$Lambda$CDM
phenomenological models into the independent degrees of freedom to which the
data observables are sensitive.
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