compute_sigma_hat_jets

t3toolbox.backend.sampling_derivatives.compute_sigma_hat_jets(right_tt_cores, xi_jets, c, trs)

def compute_sigma_hat_jets(
        right_tt_cores: typ.Sequence[NDArray],  # Q.  len=d, elm_shape=C+(rRi,nUi,rR(i+1))
        xi_jets:        typ.Sequence[NDArray],  # frame input jets, len=d, elm_shape=(2,)+W+C+(nUi,)
        c:              NDArray,                # residual jet (scalar), shape=(order+1)+W+K+C
        trs:            NDArray,                # binomial tensor, shape=(order+1,order+1,order+1)
) -> typ.Tuple[NDArray, ...]:                   # sigma_hats. len=d, elm_shape=(order+1)+W+K+C+(rR(i+1),)

Propagation-only adjoint sweep via Q, seeded at the terminal bond by the residual jet c.

The apply-transpose analog of compute_sigma_tilde_jets(): no deta_tilde per-core source, and the init carry is the c-seed on the terminal bond (rR_d = 1) rather than zeros. sigma_hats[i] is the adjoint of the after-core-i perturbation carry; it carries the tangent stack K (from c). Right-to-left via tt_reverse (mirroring the Q-sweep there).

Parameters:

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

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

• c (NDArray)

• trs (NDArray)

Return type:

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