Quijote-PNG: Quasi-maximum likelihood estimation of Primordial Non-Gaussianity in the non-linear dark matter density field

Understand

Future Large Scale Structure surveys are expected to improve over current bounds on primordial non-Gaussianity (PNG), with a significant impact on our understanding of early Universe physics.

• The level of such improvements will however strongly depend on the extent to which late time non-linearities erase the PNG signal on small scales.
• In this work, we show how much primordial information remains in the bispectrum of the non-linear dark matter density field by implementing a new, simulation-based, methodology for joint estimation of PNG amplitudes ($f_{\rm NL}$) and standard $\Lambda$CDM parameters.
• The estimator is based on optimally compressed statistics, which, for a given input density field, combine power spectrum and modal bispectrum measurements, and numerically evaluate their covariance and their response to changes in cosmological parameters.