compute_nu_jets_trs#

t3toolbox.backend.sampling_derivatives.compute_nu_jets_trs(tt_cores, xi_jets, trs)#
def compute_nu_jets_trs(
        tt_cores:   typ.Sequence[NDArray],  # len=d, elm_shape=C+(rLi,nUi,rR(i+1))
        xi_jets:    typ.Sequence[NDArray],  # input jets,  len=d, elm_shape=(2,)+W+C+(nUi,)
        trs:        NDArray,                # binomial tensor, shape=(order+1,order+1,order+1)
) -> typ.Tuple[NDArray, ...]:               # nu_jets. len=d, elm_shape=(order+1,)+W+C+(rR(i+1),). nu_jets[i][t]=nu_i^(t)

Right derivative-pushthrough jets.

The mirror image of compute_mu_jets_trs(): reverse the tensor train (tt_reverse swaps bonds and core order), run the left sweep, reverse the result. nu_jets[i] is the right edge variable entering core i (nu_i), stacked over derivative orders.

Parameters:
  • tt_cores (t3toolbox.backend.common.typ.Sequence[NDArray])

  • xi_jets (t3toolbox.backend.common.typ.Sequence[NDArray])

  • trs (NDArray)

Return type:

t3toolbox.backend.common.typ.Tuple[NDArray, Ellipsis]