Large-scale bias and efficient generation of initial conditions for nonlocal primordial non-Gaussianity

Román Scoccimarro, Lam Hui, Marc Manera, Kwan Chuen Chan

    Research output: Contribution to journalArticlepeer-review


    We study the scale dependence of halo bias in generic (nonlocal) primordial non-Gaussian (PNG) initial conditions of the type motivated by inflation, parametrized by an arbitrary quadratic kernel. We first show how to generate nonlocal PNG initial conditions with minimal overhead compared to local PNG models for a general class of primordial bispectra that can be written as linear combinations of separable templates. We run cosmological simulations for the local, and nonlocal equilateral and orthogonal models and present results on the scale dependence of halo bias. We also derive a general formula for the Fourier-space bias using the peak-background split in the context of the excursion-set approach to halos and discuss the difference and similarities with the known corresponding result from local bias models. Our peak-background split bias formula generalizes previous results in the literature to include non-Markovian effects and nonuniversality of the mass function and are in better agreement with measurements in numerical simulations than previous results for a variety of halo masses, redshifts and halo definitions. We also derive for the first time quadratic bias results for arbitrary nonlocal PNG, and show that nonlinear bias loops give small corrections at large scales. The resulting well-behaved perturbation theory paves the way to constrain nonlocal PNG from measurements of the power spectrum and bispectrum in galaxy redshift surveys.

    Original languageEnglish (US)
    Article number083002
    JournalPhysical Review D - Particles, Fields, Gravitation and Cosmology
    Issue number8
    StatePublished - Apr 4 2012

    ASJC Scopus subject areas

    • Nuclear and High Energy Physics
    • Physics and Astronomy (miscellaneous)


    Dive into the research topics of 'Large-scale bias and efficient generation of initial conditions for nonlocal primordial non-Gaussianity'. Together they form a unique fingerprint.

    Cite this