Representations of hypergraph states with neural networks*

Ying Yang(杨莹),Huaixin Cao(曹怀信)

Figure 1. Artificial neural network encoding an NNQS. It is a restricted Boltzmann machine architecture that features a set of N visible artificial neurons (blue disks) and a set of M hidden neurons (yellow disks). For each value ${{\rm{\Lambda }}}_{{k}_{1}{k}_{2}\ldots {k}_{N}}$ of the input observable S, the neural network computes the value of ${{\rm{\Psi }}}_{S,{\rm{\Omega }}}({\lambda }_{{k}_{1}},{\lambda }_{{k}_{2}},\ldots ,{\lambda }_{{k}_{N}})$.