Interpolation for completely positive maps: numerical solutions

Abstract

We present certain techniques to find completely positive maps between matrix algebras that take prescribed values on given data. To this aim we describe a semidefinite programming approach and another convex minimization method supported by a numerical example.

11 pages

References in corpus (4)

• Extending quantum operations
• Generalized channels: channels for convex subsets of the state space
• Quantum State Tomography with incomplete data: Maximum Entropy and Variational Quantum Tomography
• Physical transformations between quantum states

Cited by in corpus (2)

• Dilations, inclusions of matrix convex sets, and completely positive maps
• Joint measurability of quantum effects and the matrix diamond