Analytic Gaussian covariance matrices for galaxy <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>N</mml:mi></mml:math> -point correlation functions

We derive analytic covariance matrices for the $N$-Point Correlation Functions (NPCFs) of galaxies in Gaussian limit. Our results are given arbitrary $N$ and projected onto isotropic basis functions Cahn & Slepian (2020), recently shown to facilitate efficient NPCF estimation. A numerical implementation 4PCF is compared sample obtained from a set lognormal simulations, Quijote dark matter halo catalogues, MultiDark-Patchy galaxy mocks, with latter including realistic survey geometry. The formalism gives reasonable predictions covariances estimated mock simulations periodic-box Furthermore, fitting an effective volume number density by maximizing likelihood based on Kullback-Leibler divergence partially compensate effects non-uniform window function.