We study how large fluctuations are spatially correlated in the presence of quantum diffusion during inflation. This is done by computing real-space correlation functions in the stochastic- δ N formalism. We first derive an exact description of physical distances as measured by a local observer at the end of inflation, improving on previous works. Our approach is based on recursive algorithmic methods that consistently include volume-weighting effects. We then propose a “large-volume” approximation under which calculations can be done using first-passage time analysis only, and from which a new formula for the power spectrum in stochastic inflation is derived. We then study the full two-point statistics of the curvature perturbation. Due to the presence of exponential tails, we find that the joint distribution of large fluctuations is of the form P (ζ R 1 , ζ R 2 ) = F ( R 1 , R 2 , r ) P (ζ R 1 ) P ( ζ R 2 ), where ζ R 1 and ζ R 2 denote the curvature perturbation coarse-grained at radii R 1 and R 2 , around two spatial points distant by r . This implies that, on the tail, the reduced correlation function, defined as P (ζ R 1 > ζ c , ζ R 2 > ζ c )/[ P (ζ R 1 > ζ c ) P (ζ R 2 > ζ c )]-1, is independent of the threshold value ζ c . This contrasts with Gaussian statistics where the same quantity strongly decays with ζ c , and shows the existence of a universal clustering profile for all structures forming in the exponential tails. Structures forming in the intermediate (i.e. not yet exponential) tails may feature different, model-dependent behaviours.
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Animali et al. (2024) studied this question.
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