Figure 2
From: Scaling quantum approximate optimization on near-term hardware
\({\textsc {SWAP}}\) gate scaling with average problem degree \(d_G\) and hardware degree \(d_H\) for 7-vertex graphs. The solid line shows the non-linear least squares fit to \(N_{\textsc {SWAP}}(d_G,d_H) = a d_G/d_H + b\), with \(a=5.9 \pm 0.1\) and \(b = -2.5 \pm 0.2\), with ± indicating the asymptotic standard error of the fit parameters.
