Informative Priors on Primordial Non-Gaussianity Bias $b_{\phi}$ From Galaxy Formation
Anne Moore, Lucia A. Perez, Elisabeth Krause

TL;DR
This paper develops a method to create observation-conditioned priors on the galaxy bias parameter $b_{ m{ extphi}}$, reducing uncertainties and systematic errors in primordial non-Gaussianity constraints from galaxy clustering data.
Contribution
It introduces a framework using simulations to marginalize over galaxy formation uncertainties, improving the accuracy of $b_{ m{ extphi}}$ priors for cosmological analyses.
Findings
Conditioning on the stellar mass function reduces $b_{ m{ extphi}}$ uncertainty by 88%.
Conditioning on the stellar-to-halo mass relationship reduces $b_{ m{ extphi}}$ uncertainty by 97%.
The method remains consistent despite discrepancies in galaxy formation models.
Abstract
Constraining primordial non-Gaussianity via its scale-dependent imprint on galaxy clustering requires knowledge of the bias parameter , which is exactly degenerate with at leading order. To break this degeneracy, current analyses adopt the relation based on the assumption of a universal mass function. This relation is known to break down for physically motivated galaxy selections, introducing systematic errors in the inferred that scale directly with the assumed prior. We present a framework to construct physically motivated, observation-conditioned priors on by marginalizing over galaxy formation uncertainties. We use the CAMELS-SAM simulation suite, augmented by separate Universe simulations, to measure galaxy formation observables, like the stellar…
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