compute_eta_jets_trs#
- t3toolbox.backend.sampling_derivatives.compute_eta_jets_trs(tt_cores, mu_jets, nu_jets, trs)#
def compute_eta_jets_trs( tt_cores: typ.Sequence[NDArray], # len=d, elm_shape=C+(rLi,nOi,rR(i+1)) mu_jets: typ.Sequence[NDArray], # len=d, elm_shape=(order+1,)+W+C+(rLi,) nu_jets: typ.Sequence[NDArray], # len=d, elm_shape=(order+1,)+W+C+(rR(i+1),) trs: NDArray, # binomial tensor, shape=(order+1,order+1,order+1) ) -> typ.Tuple[NDArray, ...]: # eta_jets. len=d, elm_shape=(order+1,)+W+C+(nOi,). eta_jets[i][t]=eta_i^(t)
Combine the left and right jets at each free mode via the binomial jet-product.
eta_i^(t) = sum_{r+s=t} C(t,r) mu_{i-1}^(r) . G_i . nu_i^(s), one einsum per core ('trs,rWCa,Caib,sWCb->tWCi') – the same binomial convolution as the pushthrough, with the right jet on the bond and modeileft free.