we see that $\xi_{\textsc{ipr}}$, $\xi_{\textsc{tei}}$ and $\xi_{\textsc{bd}}$ are very good entanglement indicators. We have also found that all these indicators improve with increasing $N$. The performance of the ${\varepsilon}$-indicators depends, of course, on the specific choice of the tomographic section. For instance, ${\varepsilon_{\small\textsc{tei}}}$ and ${\varepsilon_{\small\textsc{bd}}}$ perform marginally better for the slice ${\theta_{\textsc{a}}}= 0, \,{\theta_{\textsc{b}}}= 0$ than for the slice ${\theta_{\textsc{a}}}= 0, \,{\theta_{\textsc{b}}}= \frac{1}{2}\pi$. It is also evident that $\xi_{\textsc{pcc}}$ does not fare as well as the other indicators. This is to be expected, since $\xi_{\textsc{pcc}}$ only captures linear correlations, as already emphasised.

We have verified that the sensitivity of all the indicators decreases with an increase in $\lambda$, the strength of the coupling between the two subsystems (as in Eq. \[eqn:HBEC\]). $\xi_{\textsc{ipr}}$, however, remains closer to $\xi_{\textsc{svne}}$ than the other indicators. This fact is consistent with inferences drawn from our earlier work [@sharmila2] about the relation between the Hamming distance [@HammingInQM] and the efficacy of $\xi_{\textsc{ipr}}$. We recall that the Hamming distance between two bipartite qudits $\ket{u_{1}}\otimes \ket{u_{2}}$ and $\ket{v_{1}}\otimes\ket{v_{2}}$ attains its maximum value of $2$ when ${\langle u_{1}|v_{1} \rangle}=0$ and ${\langle u_{2}|v_{2} \rangle}=0$. A straightforward extension to CV systems implies that the Hamming distance between $\ket{k_{1},N-k_{1}}$ and $\ket{k_{2},N-k_{2}}$ is 