Using Large Scale Structure to test Multifield Inflation

Simone Ferraro; Kendrick M. Smith

doi:10.1103/PhysRevD.91.043506

paper

Using Large Scale Structure to test Multifield Inflation

arXiv:1408.3126 · doi:10.1103/PhysRevD.91.043506

Abstract

Primordial non-Gaussianity of local type is known to produce a scale-dependent contribution to the galaxy bias. Several classes of multi-field inflationary models predict non-Gaussian bias which is stochastic, in the sense that dark matter and halos don't trace each other perfectly on large scales. In this work, we forecast the ability of next-generation Large Scale Structure surveys to constrain common types of primordial non-Gaussianity like $f_{N L}$ , $g_{N L}$ and $τ_{N L}$ using halo bias, including stochastic contributions. We provide fitting functions for statistical errors on these parameters which can be used for rapid forecasting or survey optimization. A next-generation survey with volume $V = 25 h^{- 3}$ Gpc $^{3}$ , median redshift $z = 0.7$ and mean bias $b_{g} = 2.5$ , can achieve $σ (f_{N L}) = 6$ , $σ (g_{N L}) = 1 0^{5}$ and $σ (τ_{N L}) = 1 0^{3}$ if no mass information is available. If halo masses are available, we show that optimally weighting the halo field in order to reduce sample variance can achieve $σ (f_{N L}) = 1.5$ , $σ (g_{N L}) = 1 0^{4}$ and $σ (τ_{N L}) = 100$ if halos with mass down to $M_{min} = 1 0^{11}$ $h^{- 1} M_{⊙}$ are resolved, outperforming Planck by a factor of 4 on $f_{N L}$ and nearly an order of magnitude on $g_{N L}$ and $τ_{N L}$ . Finally, we study the effect of photometric redshift errors and discuss degeneracies between different non-Gaussian parameters, as well as the impact of marginalizing Gaussian bias and shot noise.

17 pages, 6 figures. Comments are welcome. Typo fixed

Using Large Scale Structure to test Multifield Inflation

Abstract

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