Mitigation of nonlinear galaxy bias with a theoretical-error likelihood

Abstract

Stage-IV galaxy surveys will measure correlations at small cosmological scales with high signal-to-noise ratio. One of the main challenges of extracting information from small scales is devising accurate models, as well as characterizing the theoretical uncertainties associated with any given model. In this work, we explore the mitigation of theoretical uncertainty due to nonlinear galaxy bias in the context of photometric 2×2-point analyses. We consider linear galaxy bias as the fiducial model and derive the contribution to the covariance matrix induced by neglected higher-order bias. We construct a covariance matrix for the theoretical error in galaxy clustering and galaxy-galaxy lensing using simulation-based relations that connect higher-order parameters to linear bias. To test this mitigation model, we apply the modified likelihood to 2×2-point analyses based on two sets of mock data vectors: (1) simulated data vectors, constructed from those same relations between bias parameters, and (2) data vectors based on the AbacusSummit simulation suite. We then compare the performance of the theoretical-error approach to the commonly employed scale cuts methodology. We find most theoretical-error configurations yield results equivalent to the scale cuts in terms of precision and accuracy, and in some cases, especially with the first data set, they produce significantly stronger bounds on cosmological parameters. These results are independent of the maximum scale k max in the analysis with theoretical error. We notice the relative performance of the theoretical-error approach depends mostly on the choice of the covariance-matrix diagonal. The scenarios where linear bias supplemented by theoretical error is unable to recover unbiased cosmology, which are mainly observed with the second data set, are connected to inadequate modeling of the gg-gκ covariance of theoretical error. This form of cross-probe covariance has not been considered in previous works. We additionally highlight a sensitivity of the construction to off-diagonal correlations of theoretical error. In view of its removing the ambiguity in the choice of k max, as well as the possibility of attaining higher precision than the usual scale cuts, we consider this method to be promising for analyses of LSS in upcoming photometric galaxy surveys.