Quantum process tomography via completely positive and trace-preserving projection

Abstract

We present an algorithm for projecting superoperators onto the set of completely positive, trace-preserving maps. When combined with gradient descent of a cost function, the procedure results in an algorithm for quantum process tomography: finding the quantum process that best fits a set of sufficient observations. We compare the performance of our algorithm to the diluted iterative algorithm as well as second-order solvers interfaced with the popular CVX package for MATLAB, and find it to be significantly faster and more accurate while guaranteeing a physical estimate.

13pp, 8 figs

References in corpus (8)

• Bloch vectors for qudits
• Diluted maximum-likelihood algorithm for quantum tomography
• Quantum process tomography and Linblad estimation of a solid state qubit
• Random Quantum Operations
• Experimental quantum process tomography of non trace-preserving maps
• Quantum Process Tomography by 2D Fluorescence Spectroscopy
• Tomography of a multimode quantum black box
• Characterization of conditional state-engineering quantum processes by coherent state quantum process tomography

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