by $\rho_{sib}(\vec{p}_1,\vec{p}_2)$ and $\rho_{mix}(\vec{p}_1,\vec{p}_2)$ respectively. The two-particle correlation function $C$ (as commonly defined in nuclear physics) and pair-number density ratio $r$ (as used in the study of quantum correlations or HBT [@starhbt]) are then defined and related by C(\_1,\_2) & = & \_[sib]{}(\_1,\_2) - \_[mix]{}(\_1,\_2)\
& = & \_[mix]{}(\_1,\_2) (r(\_1,\_2) - 1), \[Eq1\] with $r \equiv  \rho_{sib}/ \rho_{mix}$. Difference $r - 1$ is the correlation measure we use. In order to visualize the CD correlation structure in the 4D angular subspace $(\eta_1,\eta_2,\phi_1,\phi_2)$ pair densities can be projected onto separate 2D subspaces ($\eta_1,\eta_2$) and ($\phi_1,\phi_2$). Those projections, discussed further below, discard a substantial amount of the information in the full two-particle space. However, they reveal that significant variation is restricted to [*difference variables*]{} $\eta_\Delta \equiv \eta_1 - \eta_2$ and $\phi_\Delta \equiv \phi_1 - \phi_2$ (the notation is explained in Sec. \[2part\]). For this analysis we therefore [*simultaneously*]{} project the 4D subspace onto those angular difference variables. The resulting 2D distribution is referred to as a [*joint autocorrelation*]{}. An autocorrelation is a projection [*by averaging*]{} [@average] from subspace $(x_1,x_2)$ onto difference variable $x_\Delta = x_1 - x_2$. A [*joint*]{} autocorrelation is a simultaneous projection onto two difference variables. The result of this 