Local Tensor Network for Strongly Correlated Projective States

The success of tensor network approaches in simulating strongly correlated quantum systems crucially depends on whether the many-body states that are relevant for the problem can be encoded in a local tensor network. Despite numerous efforts, strongly correlated projective states, including fractional quantum Hall states, have not yet found a local tensor network representation. Here we show that one can encode the calculation of averages of local operators in a Grassmann tensor network which is local. Our construction is explicit and allows the use of physically motivated trial wave functions as starting points in tensor network variational calculations.