Decoupling Local Primordial non-Gaussianity from Relativistic Effects in the Galaxy Bispectrum

TL;DR

This paper assesses the detectability of relativistic effects and primordial non-Gaussianity in the galaxy bispectrum, emphasizing the importance of including relativistic corrections to avoid biasing measurements of inflationary parameters.

Contribution

It provides the first quantification of how neglecting relativistic effects biases the measurement of local PNG parameter $f_{NL}$ in galaxy bispectrum analyses.

Findings

Relativistic effects can be detected with upcoming surveys.

Neglecting relativistic effects biases $f_{NL}$ measurements by >1.5 sigma.

Detection of relativistic effects is promising with future spectroscopic surveys.

Abstract

Upcoming galaxy surveys aim to map the Universe with unprecedented precision, depth and sky coverage. The galaxy bispectrum is a prime source of information as it allows us to probe primordial non-Gaussianity (PNG), a key factor in differentiating various models of inflation. On the scales where local PNG is strongest, Doppler and other relativistic effects become important and need to be included. We investigate the detectability of relativistic and local PNG contributions in the galaxy bispectrum. We compute the signal-to-noise ratio for the detection of the bispectrum including such effects. Furthermore, we perform information matrix forecasts on the local PNG parameter $f_{\rm NL}$ and on the parametrised amplitudes of the relativistic corrections. Finally, we quantify the bias on the measurement of $f_{\rm NL}$ that arises from neglecting relativistic effects. Our results show that detections of both first- and second-order relativistic effects are promising with forthcoming spectroscopic survey specifications -- and are largely unaffected by the uncertainty in $f_{\rm NL}$. Conversely, we show for the first time that neglecting relativistic corrections in the galaxy bispectrum can lead to $>\!1.5\sigma(f_{\rm NL})$ shift on the detected value of $f_{\rm NL}$, highlighting the importance of including relativistic effects in our modelling.