pygsti.tools.optools.compute_povm_map

pygsti.tools.optools.compute_povm_map#

compute_povm_map(model, povmlbl)#

Constructs a gate-like quantity for the POVM within model.

This is done by embedding the k-outcome classical output space of the POVM in the Hilbert-Schmidt space of k by k density matrices by placing the classical probability distribution along the diagonal of the density matrix. Currently, this is only implemented for the case when k equals d, the dimension of the POVM’s Hilbert space.

Parameters:

  • model (Model) – The model supplying the POVM effect vectors and the basis those vectors are in.

  • povmlbl (str) – The POVM label

Returns:

The matrix of the “POVM map” in the model.basis basis.

Return type:

numpy.ndarray