English

Galaxy Bispectrum from Massive Spinning Particles

Cosmology and Nongalactic Astrophysics 2018-05-16 v2 High Energy Physics - Phenomenology

Abstract

Massive spinning particles, if present during inflation, lead to a distinctive bispectrum of primordial perturbations, the shape and amplitude of which depend on the masses and spins of the extra particles. This signal, in turn, leaves an imprint in the statistical distribution of galaxies; in particular, as a non-vanishing galaxy bispectrum, which can be used to probe the masses and spins of these particles. In this paper, we present for the first time a new theoretical template for the bispectrum generated by massive spinning particles, valid for a general triangle configuration. We then proceed to perform a Fisher-matrix forecast to assess the potential of two next-generation spectroscopic galaxy surveys, EUCLID and DESI, to constrain the primordial non-Gaussianity sourced by these extra particles. We model the galaxy bispectrum using tree-level perturbation theory, accounting for redshift-space distortions and the Alcock-Paczynski effect, and forecast constraints on the primordial non-Gaussianity parameters marginalizing over all relevant biases and cosmological parameters. Our results suggest that these surveys would potentially be sensitive to any primordial non-Gaussianity with an amplitude larger than fNL1f_{\rm NL}\approx 1, for massive particles with spins 2, 3, and 4. Interestingly, if non-Gaussianities are present at that level, these surveys will be able to infer the masses of these spinning particles to within tens of percent. If detected, this would provide a very clear window into the particle content of our Universe during inflation.

Keywords

Cite

@article{arxiv.1801.07265,
  title  = {Galaxy Bispectrum from Massive Spinning Particles},
  author = {Azadeh Moradinezhad Dizgah and Hayden Lee and Julian B. Muñoz and Cora Dvorkin},
  journal= {arXiv preprint arXiv:1801.07265},
  year   = {2018}
}

Comments

New subsections on the impact of theoretical error and non-Gaussian corrections to the variance added. v2 matches the published version

R2 v1 2026-06-22T23:52:22.052Z