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Photonics chips on which one can perform Gaussian Boson Sampling have becomeaccessible on the cloud, in particular the X8 chip of Xanadu. In this technicalreport, we study its potential use as a first step towards graph classificationon quantum devices. In order to achieve this goal, we study the generatedsamples of the graph embedding method which leads to feature vectors. This isdone on a restricted class of unweighted, undirected and loop-free graphs.Hardware constraints are matched to properties of graphs that can be encoded.We report experiments on the X8 chip as well as comparisons to numericalsimulations on a classical computer and analytical solutions. We conclude thistechnical report by trying to take photon loss into account and explain theobserved results accordingly.

Towards graph classification with Gaussian Boson Sampling by embedding graphs on the X8 photonic chip