Title: Very massive tracers and higher derivative biases

Abstract

Most of the upcoming cosmological information will come from analyzing the clustering of the Large Scale Structures (LSS) of the universe through LSS or CMB observations. It is therefore essential to be able to understand their behavior with exquisite precision. The Effective Field Theory of Large Scale Structures (EFTofLSS) provides a consistent framework to make predictions for LSS observables in the mildly non-linear regime. Herein we focus on biased tracers. We argue that in calculations at a given order in the dark matter perturbations, highly biased tracers will underperform because of their larger higher derivative biases. A natural prediction of the EFTofLSS is therefore that by simply adding higher derivative biases, highly massive tracers should perform comparably well. We implement this prediction for the halo-halo and the halo-matter power spectra at one loop, and the halo-halo-halo, halo-halo-matter, and halo-matter-matter bispectra at tree-level, and compare with simulations. We find good agreement with the prediction: at $$z$$ = 0, for all tracers, we are able to match the power spectra up to $k ≃$ 0.28$$h$$ Mpc^-1, as well as a small set of about 10² bispectra triangles up to $k ≃$ 0.17$$h$$ Mpc^-1. We also discuss the limitations of our study and some avenues to pursue to further establish these findings.

Authors:

Fujita, Tomohiro ^[1]; Mauerhofer, Valentin ^[2]; Senatore, Leonardo ^[3]; Vlah, Zvonimir ^[3]; Angulo, Raul ^[4]

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+ Show Author Affiliations

1. Stanford Univ., CA (United States)
2. Stanford Univ., CA (United States); Ecole Polytechnique Federale de Lausanne (Switzlerland)
3. Stanford Univ., CA (United States); Kavli Inst. for Particle Astrophysics and Cosmology (KIPAC); SLAC National Accelerator Lab., Menlo Park, CA (United States)
4. Centro de Estudios de Fisica del Cosmos de Aragon, Teruel (Spain)

Publication Date:

Thu Jan 02 00:00:00 EST 2020

Research Org.:

SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)

Sponsoring Org.:

USDOE

OSTI Identifier:

1633853

Grant/Contract Number:  

AC02-76SF00515; FG02-12ER41854

Resource Type:

Accepted Manuscript

Journal Name:

Journal of Cosmology and Astroparticle Physics

Additional Journal Information:

Journal Volume: 2020; Journal Issue: 01; Journal ID: ISSN 1475-7516

Publisher:

Institute of Physics (IOP)

Country of Publication:

United States

Language:

English

Subject:

79 ASTRONOMY AND ASTROPHYSICS; cosmological perturbation theory; cosmological parameters from LSS; power spectrum