GEO-FPT: a model of the galaxy bispectrum at mildly non-linear scales

JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS(2023)

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摘要
We present GEO-FPT (Geometric Fitted Perturbation Theory), a new model for the galaxy bispectrum anisotropic signal in redshift space, with functional form rooted in perturbation theory. It also models the dependence of the bispectrum with the geometric properties of the triangles in Fourier space, and has a broader regime of validity than state-of-the-art theoretical models based on perturbation theory. We calibrate the free parameters of this model using high-resolution dark matter simulations and perform stringent tests to show that GEO-FPT describes the galaxy bispectrum accurately up to scales of k similar or equal to 0.12hMpc(-1 )for different cosmological models, as well as for biased tracers of the dark matter field, considering a survey volume of 100 (Gpc h(-1))(3). In particular, a joint analysis of the power spectrum and bispectrum anisotropic signals, taking into account their full covariance matrix, reveals that the relevant physical quantities - the BAO peak position (along and across the line-of-sight), and the growth of structure parameters times the amplitude of dark matter fluctuations, f sigma(8) - are recovered in an unbiased way, with an accuracy better than 0.4% and 2% respectively (which is our 2 sigma statistical limit of the systematic error estimate). In addition, the bispectrum signal breaks the f sigma(8) degeneracy without detectable bias: f and sigma(8) are recovered with better than 2.7% and 3.8% accuracy respectively (which is our 2 sigma statistical limit of the systematic error estimate).GEO-FPT boosts the applicability of the bispectrum signal of galaxy surveys beyond the current limitation of k less than or similar to 0.08 h Mpc(-1) and makes the bispectrum a key statistic to unlock the information content from the mildly non-linear regime in the on-going and forthcoming galaxy redshift surveys.
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关键词
baryon acoustic oscillations,cosmological parameters from LSS,galaxy clustering,power spectrum
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