In critical lattice models, distance ($r$) dependent correlation functions contain power laws $r^{-2Δ}$ governed by scaling dimensions $Δ$ of an underlying continuum field theory. In Monte Carlo simulations, the leading dimensions can be extracted by data fitting, which is difficult when two or more powers contribute significantly. Here a method utilizing covariance between multiple lattice operators is developed where the $r$ dependent eigenvalues of the covariance matrix reflect scaling dimensions of individual …