${\rm S{\scriptsize IM}BIG}$: The First Cosmological Constraints from Non-Gaussian and Non-Linear Galaxy Clustering
The 3D distribution of galaxies encodes detailed cosmological information on the expansion and growth history of the Universe. We present the first cosmological constraints that exploit non-Gaussian cosmological information on non-linear scales from galaxy clustering, inaccessible with current standard analyses. We analyze a subset of the BOSS galaxy survey using ${\rm S{\scriptsize IM}BIG}$, a new framework for cosmological inference that leverages high-fidelity simulations and deep generative models. We use two clustering statistics beyond the standard power spectrum: the bispectrum and a convolutional neural network based summary of the galaxy field. We infer constraints on $Λ$CDM parameters, $Ω_b$, $h$, $n_s$, $Ω_m$, and $σ_8$, that are 1.6, 1.5, 1.7, 1.2, and 2.3$\times$ tighter than power spectrum analyses. With this increased precision, we derive constraints on the Hubble constant, $H_0$, and $S_8 = σ_8 \sqrt{Ω_m/0.3}$ that are competitive with other cosmological probes, even with a sample that only spans 10% of the full BOSS volume. Our $H_0$ constraints, imposing the Big Bang Nucleosynthesis prior on the baryon density, are consistent with the early time constraints from the cosmic microwave background (CMB). Meanwhile, our $S_8$ constraints are consistent with weak lensing experiments and similarly lie below CMB constraints. Lastly, we present forecasts to show that future work extending ${\rm S{\scriptsize IM}BIG}$ to upcoming spectroscopic galaxy surveys (DESI, PFS, Euclid) will produce leading $H_0$ and $S_8$ constraints that bridge the gap between early and late time measurements and shed light on current cosmic tensions.