  Measurements of two-particle azimuthal angle correlations are a useful tool
to study the distribution of jet energy loss, however, they are complicated
because of the significant anisotropic flow background. We devise a data-driven
method for subtracting anisotropic flow background in jet-like correlation
analysis. We first require a large recoil momentum ($P_x$) within a given
pseudo-rapidity ($\eta$) range from a high-transverse momentum particle to
enhance in-acceptance population of away-side jet-like correlations. Then we
take the difference of two-particle correlations in the close-region and
far-region with respect to the $\eta$ region of $P_x$ to subtract the
anisotropic flow background. We use a toy model which contains only anisotropic
flow and PYTHIA8 which have jets to demonstrate the validity of our data-driven
method. The results indicate that the data-driven method can subtract
anisotropic flow effectively.
