iqm.benchmarks.compressive_gst.mgst.low_level_jit.dK#
- iqm.benchmarks.compressive_gst.mgst.low_level_jit.dK(X: ndarray, K: ndarray, E: ndarray, rho: ndarray, J: ndarray, y: ndarray, mle: bool = False) ndarray#
Compute the derivative of the objective function with respect to the Kraus tensor K.
This function calculates the derivative of the Kraus operator K, based on the input matrices X, E, and rho, as well as the isometry condition.
Args: X : The input matrix X, of shape (pdim, pdim). K : The Kraus operator K, reshaped to (d, rK, -1). E : A 2D array representing the POVM elements, of shape (n_povm, r). rho : A 1D array representing the density matrix. J : A 2D array representing the indices for which the derivatives will be computed. y : A 2D array of shape (n_povm, len(J)) containing the target values. mle : If True, the log-likelihood objective function is used, otherwise the least squares objective function is used