Speaker
Description
Cosmic voids identified in the spatial distribution of galaxies provide complementary information to two-point statistics. In particular, constraints on the neutrino mass sum, $\sum m_\nu$, promise to benefit from the inclusion of void statistics. We perform inference on the CMASS NGC sample of SDSS-III/BOSS with the aim of constraining $\sum m_\nu$. We utilize the void size function, the void-galaxy cross power spectrum, and the galaxy auto power spectrum. To extract constraints from these summary statistics we use a simulation-based approach, specifically implicit likelihood inference. We populate approximate gravity-only, particle neutrino cosmological simulations with an expressive halo occupation distribution model. With a conservative scale cut of $k_\text{max}=0.15\,h\text{Mpc}^{-1}$ and a Planck-inspired $\Lambda$CDM prior, we find upper bounds on $\sum m_\nu$ of $0.43$ and $0.35\,\text{eV}$ from the galaxy auto power spectrum and the full data vector, respectively ($95\,\%$ credible interval). We observe hints that the void statistics may be most effective at constraining $\sum m_\nu$ from below. We also substantiate the usual assumption that the void size function is Poisson distributed.
