English

Constraints on Single-Field Inflation from the BOSS Galaxy Survey

Cosmology and Nongalactic Astrophysics 2022-07-20 v1 General Relativity and Quantum Cosmology High Energy Physics - Phenomenology High Energy Physics - Theory

Abstract

Non-local primordial non-Gaussianity (NLPNG) is a smoking gun of interactions in single-field inflationary models, and can be written as a combination of the equilateral and orthogonal templates. We present the first constraints on these from the redshift-space galaxy power spectra and bispectra of the Baryon Oscillation Spectroscopic Survey (BOSS) data. These are the first such measurements independent of the cosmic microwave background fluctuations. We perform a consistent analysis that includes all necessary nonlinear corrections generated by NLPNG, and vary all relevant cosmological and nuisance parameters in a global fit to the data. Our conservative analysis yields joint limits on the amplitudes of the equilateral and orthogonal shapes, fNLequil=940±600f_{\rm NL}^{\rm equil}=940\pm 600, fNLortho=170±170f_{\rm NL}^{\rm ortho}= -170\pm 170 (both at 68\% CL). These can be used to derive constraints on coefficients of the effective single-field inflationary Lagrangian; in particular, we find that the sound speed of inflaton fluctuations has the bound cs0.013c_s\geq 0.013 at 95\% CL. Fixing the quadratic galaxy bias and cosmological parameters, the constraints can be tightened to fNLequil=260±300f_{\rm NL}^{\rm equil}=260\pm 300, fNLortho=23±120f_{\rm NL}^{\rm ortho}= -23\pm 120 (68\% CL).

Keywords

Cite

@article{arxiv.2201.07238,
  title  = {Constraints on Single-Field Inflation from the BOSS Galaxy Survey},
  author = {Giovanni Cabass and Mikhail M. Ivanov and Oliver H. E. Philcox and Marko Simonović and Matias Zaldarriaga},
  journal= {arXiv preprint arXiv:2201.07238},
  year   = {2022}
}

Comments

6+7 pages, 2+3 figures, 0+1 table, code available at github.com/Michalychforever/CLASS-PT, with custom MontePython likelihoods available at github.com/oliverphilcox/full_shape_likelihoods